problem solving competency assessment

Choosing a problem-solving skills assessment: How and why?

Choosing the right problem-solving skills assessment is more than just a hiring step; it’s an investment in your team’s future. In a survey by the World Economic Forum , problem-solving was ranked as one of the top skills needed in the 2020s workforce. Picking up these skills is pretty straightforward – it’s a lot like what you learned hanging out with roommates in your  student accommodation . You know, just living together and figuring things out as you go . This blog will guide you through the essentials of selecting an assessment that effectively measures this critical skill, ensuring your candidates are equipped to tackle challenges creatively and efficiently in today’s dynamic work environment .

Understanding the importance of problem-solving skills in the workplace

It’s not just about fixing what’s broken but about navigating through challenges and finding innovative solutions. This skill is essential for almost every job, from a manager figuring out how to improve team performance to an IT specialist resolving system glitches.

Now, here’s where a skills assessment becomes a game-changer. Companies can spot the superheroes in their team by using a skills assessment designed to gauge problem-solving abilities . It’s like having a special lens to see who’s really good at untangling complex situations and who might need a bit more training.

Imagine you’re a coach picking players for a puzzle-solving contest. You’d want people who can think quickly, adapt to new problems, and come up with clever solutions, right? That’s what this skills assessment does – it helps identify the employees who can do just that.

So, why does this matter? Well, employees who excel at problem-solving are often the ones driving innovation and efficiency within an organization. They’re the ones who keep things running smoothly, come up with fresh ideas, and help the company adapt and thrive, no matter what challenges come their way.

Criteria for selecting a problem-solving skills assessment

Choosing the right skills assessment for problem-solving is a bit like picking the perfect tool for a job. You want something that fits just right and really gets the job done. When it comes to problem-solving assessments, there are a few key things to look out for.

First, think about what makes an effective assessment. It should be challenging enough to really test someone’s skills but not so tough that it’s discouraging. It’s like a puzzle that’s fun yet makes you think. The assessment should cover different types of problems – some that need quick thinking and others that require deep analysis.

Next, consider the variety of assessments available. You’ve got simulations that put people in real-world scenarios, case studies that make them think through complex situations, and logical reasoning tests that check how well they can think on their feet. Each type has its own way of shining a light on a person’s problem-solving skills.

Remember, the goal is to find a skills assessment that tests problem-solving abilities and feels relevant to the jobs you’re hiring for. It’s about finding that sweet spot where the assessment reflects the challenges employees will face in their roles. This way, you get a clear picture of how well they’ll tackle real-life problems in the workplace.

Aligning assessment with business goals and job requirements

When it comes to finding the right skills assessment for problem-solving , it’s like matching puzzle pieces to the bigger picture of your business. You want to make sure the assessment fits not just the job but also your company’s goals and values.

First, let’s talk about tailoring the assessment to specific job roles. Imagine you’re hiring a project manager. Their problem-solving assessment might focus on handling project delays or managing team conflicts. On the other hand, if you’re hiring a software developer, their assessment might be more about troubleshooting coding issues or optimizing algorithms.

Now, think about your company’s unique culture and values. Your ideal skills assessment should reflect these too. For instance, if creativity is a big deal at your company, include problem-solving scenarios that require out-of-the-box thinking. If teamwork is key, consider assessments that evaluate how well a person collaborates to solve problems.

In short, the assessment should mirror the challenges an employee will face in their role and the qualities your company cherishes. This way, you’re more likely to find candidates who are skilled and a great fit for your business culture.

Implementing the assessment: Best practices

Introducing a new skills assessment into your hiring process is a bit like adding a new recipe to your cookbook. You want to make sure it blends well with your existing ingredients and enhances the overall flavor. Here are some tips to smoothly integrate a problem-solving skills assessment into your hiring process.

First, plan out how the assessment will fit into your existing hiring stages. It’s like figuring out the right time to add a spice to a dish. Decide whether the assessment should come early to screen candidates or later as a deeper evaluation. Ensure it complements other steps like interviews or group activities.

Next, focus on fairness and objectivity. This is crucial. The assessment should be the same for every candidate to ensure a level playing field. Think of it as following a recipe to the letter – every candidate gets the same ingredients and instructions. This way, you’re judging everyone by the same standards.

Remember, clear communication is key. Inform candidates about what to expect from the assessment. It’s like giving diners a menu; they should know what they’re in for. This helps reduce anxiety and allows candidates to perform at their best.

By following these steps, you can ensure your problem-solving skills assessment not only identifies the most capable candidates but also enhances your overall hiring process.

Analyzing and utilizing assessment results

After conducting a problem-solving skills assessment, it’s like having a treasure trove of information about your candidates. Now, it’s time to dive in and make sense of these valuable insights.

First up, analyzing the results. Think of it like reading a map that guides you to the right candidates. Look for patterns and standout performances. Did some candidates excel in creative problem-solving while others shone in logical reasoning? This helps you understand not just who is good, but also how they’re good at solving problems.

But it’s not just about who you hire. These assessment results can be a goldmine for your team’s development too. Maybe you’ll spot areas where many candidates struggled. This could indicate a skill gap in your existing team and highlight areas for training and growth.

Finally, use these insights to enhance your hiring and training processes. It’s like fine-tuning a machine; with each assessment, you learn more about what makes a great problem-solver for your company. This way, you can continuously improve the skills assessment to better match your company’s evolving needs.

In short, the results from your problem-solving skills assessment aren’t just a one-time thing. They’re a resource for making smarter hiring decisions and for guiding ongoing employee development.

In summary, choosing the proper problem-solving skills assessment is key to unlocking the potential of your workforce. It’s not just about finding candidates who can think independently but about fostering a culture of innovative problem-solving that propels your organization forward. By prioritizing these assessments, you invest in individuals who can navigate complex challenges, drive change, and contribute to your business’s overall success and resilience.

Choose Testlify as your new remote assessment tool and assess your candidates quickly. Sign up now with Testlify and check out the vast test library.

Frequently asked questions (FAQs)

A problem-solving skills assessment is a tool used in hiring to evaluate a candidate’s ability to handle challenges and find solutions in work-related scenarios.

These assessments help identify candidates with strong analytical and creative thinking skills, crucial for navigating workplace challenges effectively.

By matching assessment challenges to real job scenarios, businesses can ensure candidates possess skills that align with their specific goals and needs.

Key practices include integrating the assessment smoothly into the hiring process, ensuring fairness, and clearly communicating its purpose to candidates.

Results are used for making informed hiring decisions and identifying skill gaps for employee training, enhancing overall team performance.

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How to assess problem-solving skills

Human beings have been fascinated and motivated by problem-solving for as long as time. Let’s start with the classic ancient legend of Oedipus. The Sphinx aggressively addressed anyone who dared to enter Thebes by posing a riddle. If the traveler failed to answer the riddle correctly, the result was death. However, the Sphinx would be destroyed when the answer was finally correct.

Alas, along came Oedipus. He answered correctly. He unlocked this complex riddle and killed the Sphinx.

However, rationality was hardly defined at that time. Today, though, most people assume that it simply takes raw intelligence to be a great problem solver. However, it’s not the only crucial element.

Introduction to key problem-solving skills

You’ve surely noticed that many of the skills listed in the problem-solving process are repeated. This is because having these abilities and talents are so crucial to the entire course of getting a problem solved. Let’s look at some key problem-solving skills that are essential in the workplace.

Communication, listening, and customer service skills

In all the stages of problem-solving, you need to listen and engage to understand what the problem is and come to a conclusion as to what the solution may be. Another challenge is being able to communicate effectively so that people understand what you’re saying. It further rolls into interpersonal communication and customer service skills, which really are all about listening and responding appropriately.

Data analysis, research, and topic understanding skills

To produce the best solutions, employees must be able to understand the problem thoroughly. This is possible when the workforce studies the topic and the process correctly. In the workplace, this knowledge comes from years of relevant experience.

Dependability, believability, trustworthiness, and follow-through

To make change happen and take the following steps towards problem-solving, the qualities of dependability, trustworthiness, and diligence are a must. For example, if a person is known for not keeping their word, laziness, and committing blunders, that is not someone you’ll depend on when they provide you with a solution, will you?

Leadership, team-building, and decision-making

A true leader can learn and grow from the problems that arise in their jobs and utilize each challenge to hone their leadership skills. Problem-solving is an important skill for leaders who want to eliminate challenges that can otherwise hinder their people’s or their business’ growth. Let’s take a look at some statistics that prove just how important these skills are:

A Harvard Business Review study states that of all the skills that influence a leader’s success, problem-solving ranked third out of 16.

According to a survey by Goremotely.net, only 10% of CEOs are leaders who guide staff by example .

Another  study at Havard Business Review found a direct link between teambuilding as a social activity and employee motivation.

Are you looking for a holistic way to develop leaders in your workplace?

Numerous skills and attributes define a successful one from a rookie when it comes to leaders. Our leadership development plan (with examples!) can help HR leaders identify potential leaders that are in sync with your company’s future goals.

Why is problem solving important in the workplace?

As a business leader, when too much of your time is spent managing escalations, the lack of problem-solving skills may hurt your business. While you may be hiring talented and capable employees and paying them well, it is only when you harness their full potential and translate that into business value that it is considered a successful hire.

The impact of continuing with poor problem-solving skills may show up in your organization as operational inefficiencies that may also manifest in product quality issues, defects, re-work and non-conformance to design specifications. When the product is defective, or the service is not up to the mark, it directly affects your customer’s experience and consequently reflects on the company’s profile.

At times, poor problem-solving skills could lead to missed market opportunities, slow time to market, customer dissatisfaction, regulatory compliance issues, and declining employee morale.

Problem-solving skills are important for individual business leaders as well. Suppose you’re busy responding to frequent incidents that have the same variables. In that case, this prevents you from focusing your time and effort on improving the future success of business outcomes.

Proven methods to assess and improve problem-solving skills

Pre-employment problem-solving skill assessment .

Recent research indicates that up to 85% of resumes contain misleading statements. Similarly, interviews are subjective and ultimately serve as poor predictors of job performance .

To provide a reliable and objective means of gathering job-related information on candidates, you must validate and develop pre-employment problem-solving assessments. You can further use the data from pre-employment tests to make informed and defensible hiring decisions.

Depending on the job profile, below are examples of pre-employment problem-solving assessment tests:

Personality tests: The rise of personality testing in the 20th century was an endeavor to maximize employee potential. Personality tests help to identify workplace patterns, relevant characteristics, and traits, and to assess how people may respond to different situations.

Examples of personality tests include the Big five personality traits test and Mercer | Mettl’s Dark Personality Inventory .

Cognitive ability test: A pre-employment aptitude test assesses individuals’ abilities such as critical thinking, verbal reasoning, numerical ability, problem-solving, decision-making, etc., which are indicators of a person’s intelligence quotient (IQ). The test results provide data about on-the-job performance. It also assesses current and potential employees for different job levels.

Criteria Cognitive Aptitude test , McQuaig Mental Agility Test , and Hogan Business Reasoning Inventory are commonly used cognitive ability assessment tests.

Convergent and divergent thinking methods

American psychologist JP Guilford coined the terms “convergent thinking” and “divergent thinking” in the 1950s.

Convergent thinking involves starting with pieces of information and then converging around a solution. An example would be determining the correct answer to a multiple-choice question.

The nature of the question does not demand creativity but rather inherently encourages a person to consider the veracity of each answer provided before selecting the single correct one.

Divergent thinking, on the other hand, starts with a prompt that encourages people to think critically, diverging towards distinct answers. An example of divergent thinking would be asking open-ended questions.

Here’s an example of what convergent thinking and a divergent problem-solving model would look like.

The 5 whys method , developed by Sakichi Toyoda, is part of the Toyota production system. In this method, when you come across a problem, you analyze the root cause by asking “Why?” five times. By recognizing the countermeasure, you can prevent the problem from recurring. Here’s an example of the 5 whys method.

Source: Kanbanzie

This method is specifically useful when you have a recurring problem that reoccurs despite repeated actions to address it. It indicates that you are treating the symptoms of the problem and not the actual problem itself.

Starbursting

While brainstorming is about the team coming together to try to find answers, starbursting flips it over and asks everyone to think of questions instead. Here’s an example of the starbursting method.

The idea of this method is to go and expand from here, layering more and more questions until you’ve covered every eventuality of the problem.

Use of data analysis to measure improvement in problem-solving skills for your organization

Problem-solving and data analytics are often used together. Supporting data is very handy whenever a particular problem occurs. By using data analytics, you can find the supporting data and analyze it to use for solving a specific problem.

However, we must emphasize that the data you’re using to solve the problem is accurate and complete. Otherwise, misleading data may take you off track of the problem at hand or even make it appear more complex than it is. Moreover, as you gain knowledge about the current problem, it further eases the way to solve it.

Let’s dig deeper into the top 3 reasons data analytics is important in problem-solving.

 1. Uncover hidden details

Modern data analytics tools have numerous features that let you analyze the given data thoroughly and find hidden or repeating trends without needing any extra human effort. These automated tools are great at extracting the depths of data, going back way into the past.

2. Automated models

Automation is the future. Businesses don’t have enough time or the budget to encourage manual workforces to go through loads of data to solve business problems. Instead, the tools can collect, combine, clean, and transform the relevant data all by themselves and finally use it to predict the solutions.

3. Explore similar problems

When you use a data analytics approach to solve problems, you can collect all the data available and store it. It can assist you when you find yourself in similar problems, providing references for how such issues were tackled in the past.

If you’re looking for ways to help develop problem-solving skills in the workplace and want to build a team of employees who can solve their own problems, contact us to learn how we can help you achieve it.

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Problem Solving test

Summary of the problem solving test.

This Problem Solving test evaluates candidates’ ability to define problems and analyze data/textual information to make correct decisions . Our test helps you identify candidates with the analytical skills to assess and respond to complex business situations quickly and accurately.

Covered skills

Creating and adjusting schedules

Interpreting data and applying logic to make decisions

Prioritizing tasks and applying order based on a given set of rules

Analyzing textual and numerical information to draw conclusions

Use the Problem Solving test to hire

Any role that involves managing constantly shifting variables with tight deadlines, including administrative assistants, project managers, customer service managers, web developers, and people working in hospitality or sales.

Sign up for a Free forever plan and use this Problem Solving assessment test for free!

About the Problem Solving test

Effective problem-solving involves the ability to:

Define complex problems

Break it down into manageable parts using verbal and numerical reasoning skills

Develop approaches to solve the (sub)problem using creativity and analytical thinking

Execute flawlessly

Problem-solving abilities are difficult to assess through resume screening alone. A candidate might say they’ve solved several problems in the past, but that doesn’t show their ability to work well under pressure or tell you how sophisticated their problem-solving abilities are.

That’s why our Problem Solving test enables candidates to show off their skills in real time. This problem resolution test presents candidates with typical problem-solving scenarios like 1) scheduling based on a diverse set of conditions, 2) identifying the right sequence of actions based on several business rules, and 3) drawing conclusions based on textual and numerical information

Check out our practice preview questions to see the Problem Solving test in action.

A successful problem solver can quickly identify the key elements of the problem and work through the problem at speed without making mistakes. This multiple-choice test is also useful to check candidates' overall analytical skills.

The test is made by a subject-matter expert

The global IT industry has benefited from Anirban’s talents for over two decades. With a flawless reputation that precedes him, Anirban has earned a status as a sought-after agile project manager and consultant. He’s worked internationally as a Senior Project Manager with companies such as Ericsson, IBM, and T-Mobile.

Anirban’s love for learning helps him keep his skills sharp. He holds an MBA and a degree in engineering, is a certified Scrum Master, and has certifications in Prince2 and ITIL.

Crafted with expert knowledge

TestGorilla’s tests are created by subject matter experts. We assess potential subject-matter experts based on their knowledge, ability, and reputation. Before being published, each test is peer-reviewed by another expert, then calibrated using hundreds of test takers with relevant experience in the subject.

Our feedback mechanisms and unique algorithms allow our subject-matter experts to constantly improve their tests.

What our customers are saying

TestGorilla helps me to assess engineers rapidly. Creating assessments for different positions is easy due to pre-existing templates. You can create an assessment in less than 2 minutes. The interface is intuitive and it’s easy to visualize results per assessment.

VP of engineering, mid-market (51-1000 FTE)

Any tool can have functions—bells and whistles. Not every tool comes armed with staff passionate about making the user experience positive.

The TestGorilla team only offers useful insights to user challenges, they engage in conversation.

For instance, I recently asked a question about a Python test I intended to implement. Instead of receiving “oh, that test would work perfectly for your solution,” or, “at this time we’re thinking about implementing a solution that may or may not…” I received a direct and straightforward answer with additional thoughts to help shape the solution.

I hope that TestGorilla realizes the value proposition in their work is not only the platform but the type of support that’s provided.

For a bit of context—I am a diversity recruiter trying to create a platform that removes bias from the hiring process and encourages the discovery of new and unseen talent.

Chief Talent Connector, small business (50 or fewer FTE)

Use TestGorilla to hire the best faster, easier and bias-free

Our screening tests identify the best candidates and make your hiring decisions faster, easier, and bias-free.

Learn how each candidate performs on the job using our library of 400+ scientifically validated tests.

Test candidates for job-specific skills like coding or digital marketing, as well as general skills like critical thinking. Our unique personality and culture tests allow you to get to know your applicants as real people – not just pieces of paper.

Give all applicants an equal, unbiased opportunity to showcase their skills with our data-driven and performance-based ranking system.

With TestGorilla, you’ll get the best talent from all walks of life, allowing for a stronger, more diverse workplace.

Our short, customizable assessments and easy-to-use interface can be accessed from any device, with no login required.

Add your company logo, color theme, and more to leave a lasting impression that candidates will appreciate.

Watch what TestGorilla can do for you

Create high-quality assessments, fast.

Building assessments is a breeze with TestGorilla. Get started with these simple steps.

Building assessments is quick and easy with TestGorilla. Just pick a name, select the tests you need, then add your own custom questions.

You can customize your assessments further by adding your company logo, color theme, and more. Build the assessment that works for you.

Send email invites directly from TestGorilla, straight from your ATS, or connect with candidates by sharing a direct link.

Have a long list of candidates? Easily send multiple invites with a single click. You can also customize your email invites.

Discover your strongest candidates with TestGorilla’s easy-to-read output reports, rankings, and analytics.

Easily switch from a comprehensive overview to a detailed analysis of your candidates. Then, go beyond the data by watching personalized candidate videos.

View a sample report

The Problem Solving test will be included in a PDF report along with the other tests from your assessment. You can easily download and share this report with colleagues and candidates.

Why are problem solving skills important to employers?

Employers should use problem solving skills assessment tests because nearly every role benefits from staff with positive, troubleshooting mindsets.

Problem solving skills in the workplace mean that employees can respond quickly to challenges, creating processes that mitigate or remove obstacles that prevent the company from achieving its goals.

These challenges can be anything, for example: 

Delays in your supply chain

Conflict between team members

Technological problems

Problem solving skills are especially important in roles such as project management, administrative assistance, and planning work with ever-changing circumstances and tight deadlines.

By asking candidates to pass a problem solving test online during the recruitment process, you ensure that all your recruits have what it takes to troubleshoot problems, improve your productivity, and increase your chances of innovation.

 A problem solving skills test also ensures that you do this with minimal bias, using an objective numerical measure to establish the required skill set and build a shortlist.

You should also explore candidates’ approaches to creative problem solving in more depth with problem solving questions in the interview stage.

Key problem solving abilities to measure with a problem solving test

A strong problem resolution test evaluates candidates’ ability to define problems and analyze data and textual information to make decisions that best serve the business. 

Some of the considerations for problem-solving test questions include:

Creating and adjusting schedules: Candidates should use a problem-solving process to understand what they can realistically achieve within time and how to adjust schedules to account for variable outcomes.

Interpreting data and applying logic to make decisions: Job seekers should have an aptitude for aligning data with business goals and making actionable decisions.

Prioritizing and applying order based on a given set of rules: Applicants can determine which project tasks take priority by using prioritization rules and supporting information.

Analyzing textual and numerical information to draw conclusions: Examining textual and numerical information to reveal patterns, relationships, and trends can help candidates draw accurate conclusions and pick the best choice from a selection of alternative solutions.

What job roles can you hire with our Problem Solving test?

You can – and should – use an ability test of problem solving skills when screening for most roles to reduce time-to-hire, even when hiring globally like Nexus HR.

However, it is especially important when hiring for positions where effective problem-solving is needed – for example, managerial roles, project-focused roles, and jobs where employees frequently work under time limits.

Here are some examples of roles you should use a problem solving assessment for:

Administrative assistants: Employees who can think on their feet can swiftly resolve logistical challenges, manage schedules, and facilitate seamless communication.

Project managers : Problem solving skills are essential to keep projects on track and ensure deadlines are met, even when unexpected changes occur.

Customer service managers: Customer service reps must make prompt decisions to respond to customer queries and solve their issues quickly.

Web developers : Great programmers have the competency to spot problems in their code and identify possible solutions.

Venture capitalists: Venture capitalists must be able to think critically and spot both opportunities and risks in potential investments – problem solving skills are key here.

Hospitality staff : Hotel and restaurant workers thrive when they can identify and effectively respond to customer issues, turning negatives into positive experiences.

Salespeople: Sales professionals benefit from the ability to transform client challenges and objections into opportunities for problem-solving, which often leads to upsells and cross-sells.

Create a multi-measure assessment: 4 tests to pair with the Problem Solving test

Of course, a problem solving test alone can’t tell you if a candidate has all the right skills for the role. Instead, include a problem solving skills test as part of a multi-measure psychometric assessment alongside up to four other essential skills tests to find the best candidates.

Here’s an example of four tests you might include to make a strong multi-measure assessment:

Communication test : Ensure your candidates maintain clear communication with teammates and direct reports, which is essential when discussing problems, brainstorming solutions, and implementing the chosen strategy

Time Management test : Dig deeper into jobseekers’ abilities to respond to time-pressured tasks and manage deadlines

Critical Thinking test : Identify prospects with the cognitive ability and logical reasoning to solve nuanced problems, stay objective, and balance complexities in their decision-making process

Big Five (OCEAN) Personality test : Get insight into what kind of worker a candidate is through five key metrics: openness, conscientiousness, extraversion, agreeableness, and emotional stability.

Note: We haven’t included any role-specific skills tests here because they depend on the position you’re hiring for. However, we highly recommend you add at least one in your five-test assessment to ensure your candidates possess the right skills for the job.

An assessment is the total package of tests and custom questions that you put together to evaluate your candidates. Each individual test within an assessment is designed to test something specific, such as a job skill or language. An assessment can consist of up to 5 tests and 20 custom questions. You can have candidates respond to your custom questions in several ways, such as with a personalized video.

Yes! Custom questions are great for testing candidates in your own unique way. We support the following question types: video, multiple-choice, coding, file upload, and essay. Besides adding your own custom questions, you can also create your own tests.

A video question is a specific type of custom question you can add to your assessment. Video questions let you create a question and have your candidates use their webcam to record a video response. This is an excellent way to see how a candidate would conduct themselves in a live interview, and is especially useful for sales and hospitality roles. Some good examples of things to ask for video questions would be "Why do you want to work for our company?" or "Try to sell me an item you have on your desk right now."

Besides video questions, you can also add the following types of custom questions: multiple-choice, coding, file upload, and essay. Multiple-choice lets your candidates choose from a list of answers that you provide, coding lets you create a coding problem for them to solve, file upload allows your candidates to upload a file that you request (such as a resume or portfolio), and essay allows an open-ended text response to your question. You can learn more about different custom question types here .

Yes! You can add your own logo and company color theme to your assessments. This is a great way to leave a positive and lasting brand impression on your candidates.

Our team is always here to help. After you sign up, we’ll reach out to guide you through the first steps of setting up your TestGorilla account. If you have any further questions, you can contact our support team via email, chat or call. We also offer detailed guides in our extensive help center .

It depends! We offer five free tests, or unlimited access to our library of 400+ tests with the price based on your company size. Find more information on our pricing plans here , calculate the cost-benefit of using TestGorilla assessments, or speak to one of our sales team for your personalized demo and learn how we can help you revolutionize hiring today.

Yes. You can add up to five tests to each assessment.

We recommend using our assessment software as a pre-screening tool at the beginning of your recruitment process. You can add a link to the assessment in your job post or directly invite candidates by email.

TestGorilla replaces traditional resume screening with a much more reliable and efficient process, designed to find the most skilled candidates earlier and faster.

We offer the following cognitive ability tests : Numerical Reasoning, Problem Solving, Attention to Detail, Reading Comprehension, and Critical Thinking.

Our cognitive ability tests allow you to test for skills that are difficult to evaluate in an interview. Check out our blog on why these tests are so useful and how to choose the best one for your assessment.

Related tests

Attention to detail (textual), verbal reasoning, numerical reasoning, critical thinking, computational thinking, basic math calculations, mechanical reasoning, understanding instructions, attention to detail (visual), intermediate math.

Competency assessment tool: The complete guide

Reading time:

The ability to understand and evaluate the competencies of your workforce is essential. Competency assessment tools play a crucial role in this process, offering a structured approach to pinpointing, assessing, and fostering the development of employees’ skills and abilities.

These tools enable organizations to systematically analyze the strengths and areas for improvement within their workforce, aligning employee capabilities with strategic business goals.

By employing competency assessment tools , companies can make informed decisions about talent management, including hiring, promotions, and succession planning.

These assessments help identify the specific competencies that are critical for success in various roles and determine whether current employees possess these skills or require further development.

This insight is invaluable for creating targeted training and development programs that address skill gaps and prepare employees for future challenges.

Let’s take a closer look at it!

Understanding competency assessment tools

Definition and importance.

Competency assessment tools are systematic approaches designed to evaluate the skills, knowledge, and abilities that are essential for specific roles within an organization.

These tools play a critical role in understanding how the capabilities of employees align with the strategic objectives and operational needs of the organization.

By accurately assessing competencies , companies can identify areas where employees excel and areas where development is needed, facilitating targeted training and development programs.

This alignment ensures that the workforce is fully equipped to meet current challenges and future demands, enhancing overall organizational performance and competitiveness.

Competency assessments also support talent management processes such as recruitment, promotion, and succession planning, ensuring that the right people are in the right roles.

Ultimately, these tools are invaluable for fostering a culture of continuous learning and development , driving employee engagement, and achieving organizational goals.

Types of competency assessment tools

There are several types of competency assessment tools available, each designed to serve different purposes within the framework of talent management and development.

These tools provide comprehensive insights into the skills, knowledge, and behaviors of employees, facilitating informed decision-making in various HR processes. Here’s an overview of some common types of competency-based assessment tools :

Skills assessments: These assessments are focused on evaluating the technical or professional skills required for specific roles. They can be in the form of tests, simulations, or practical tasks that measure either the competency group or the employee’s ability to perform job-related functions.

Behavioral interviews: This type of assessment uses structured interviews to understand how an individual has handled situations in the past. Questions are designed to elicit examples of past behavior, which can indicate how an employee might perform in the future.

360-degree feedback mechanisms: This comprehensive approach gathers feedback on an employee’s performance from a variety of sources, including supervisors, peers, subordinates, and sometimes clients. It provides a well-rounded view of an individual’s competencies, work habits, and interpersonal skills.

Personality and psychometric tests: These tests assess aspects of an individual’s personality and cognitive abilities, such as problem-solving skills, critical thinking, and adaptability. They can help predict an employee’s suitability for certain roles or their leadership potential.

Performance appraisals: Regular performance reviews between managers and their team members can also serve as competency assessments. These appraisals review the employee’s work over a period, assessing achievements and areas for improvement against predefined competencies.

Self-assessments: Encouraging employees to self-evaluate their skills and performance can provide valuable insights into their perceptions of their strengths and development needs. This can inform personal development plans and career progression discussions.

By leveraging these diverse tools and organizational resources, organizations can gain a deep understanding of their workforce’s capabilities, aligning employee development with organizational objectives and ensuring a strategic approach to talent management.

Benefits of using competency assessment tools

Implementing competency assessment tools can significantly enhance organizational effectiveness across several dimensions. Firstly, they lead to improved employee performance.

By identifying specific strengths and areas for development, these tools enable targeted training and development initiatives, allowing employees to hone the skills most relevant to their roles and career aspirations.

This tailored approach to development ensures that employees are not only more competent but also more confident in their abilities, contributing to higher overall performance.

Secondly, competency assessment tools contribute to better hiring decisions. They provide a structured and objective framework for evaluating candidates, ensuring that recruitment efforts are aligned with the specific skills and behaviors required for success in open positions.

This alignment between candidate capabilities and job requirements reduces the risk of poor fit, enhancing the likelihood of long-term success and retention.

Finally, the use of these tools fosters a more engaged workforce. Employees who feel that their development is supported and that they are in roles suited to their strengths are more likely to be engaged with their work.

Moreover, a transparent and fair assessment process contributes to a positive organizational culture, where employees feel valued and understood.

This sense of belonging and recognition is a key driver of employee engagement, leading to higher job satisfaction, loyalty, and motivation.

In sum, the strategic implementation of competency assessment tools can transform talent management practices, leading to a cycle of continuous improvement where both employees and the organization grow together.

Implementing competency assessment tools

Identifying competencies.

The initial step in implementing an effective competency assessment framework involves defining the competencies that are critical for success in each role within the organization.

This process requires a thorough analysis of job functions, responsibilities, and the desired outcomes associated with each position.

Competencies typically encompass a blend of skills, knowledge, behaviors, and attitudes that contribute to an individual’s ability to perform effectively in a specific role.

To define these competencies, organizations often undertake the following actions:

Job analysis: Conduct detailed job analyses to understand the tasks, responsibilities, and outcomes expected from each role. This involves gathering information through observations, interviews with job holders and their managers, and reviewing job descriptions.

Identification of key competencies: From the job analysis, identify the essential skills, knowledge areas, and behavioral attributes that contribute to successful performance. These competencies should align with the organization’s strategic goals and values.

Categorization: Organize the identified competencies into categories such as core competencies (applicable organization-wide), role-specific competencies (necessary for specific positions), and leadership competencies (for management roles).

Validation: Ensure the defined competencies are relevant and comprehensive by seeking feedback from stakeholders across the organization, including HR professionals, managers, and employees.

Documentation and communication: Document the defined competencies and communicate them across the organization to ensure everyone understands the expectations and how they align with organizational goals.

By clearly defining the competencies critical for success in each role, organizations create a solid foundation for their competency assessment initiatives.

This clarity enables more effective hiring, training, development, and performance management processes, ensuring employees are equipped and motivated to contribute to the organization’s success.

Choosing the right tool

Selecting the appropriate competency assessment tool is a critical step that hinges on the specific competencies you aim to evaluate and the context in which the assessment will be utilized.

Different tools are designed to measure various aspects of competency, such as technical skills, behavioral attributes, leadership qualities, or cognitive abilities. Understanding the unique requirements of each role and the competencies that underpin successful performance in those roles is essential for choosing the right competency measurement tool.

For instance, if the goal is to assess technical skills or knowledge, skills assessments or simulations might be most effective.

These tools can provide objective measures of an employee’s ability to perform specific tasks or solve problems relevant to their job function.

On the other hand, if you’re focusing on behavioral competencies or leadership qualities, tools like behavioral interviews, 360-degree feedback, or personality assessments might be more appropriate.

These methods can offer insights into an individual’s work style, interpersonal skills, and ability to lead and motivate others.

The context in which the assessment will be used also plays a significant role in tool selection.

For example, if the assessment is for hiring purposes, you might prioritize tools that are efficient and scalable, like psychometric tests or structured interviews.

If the assessment is for development or succession planning, comprehensive tools that provide detailed feedback, such as 360-degree feedback or performance appraisals, may be more suitable.

Ultimately, selecting the right competency assessment tool involves a careful analysis of the competencies to be assessed and the specific objectives of the assessment process.

By aligning the tool with both the competencies of interest and the intended use case, organizations can ensure more accurate, useful, and actionable assessment outcomes.

Customization and integration

Customizing competency assessment tools to align with the unique needs of your organization and integrating them with existing HR systems are crucial steps for ensuring the success of your talent management strategy.

Tailoring these tools allows for a more precise evaluation of employee competencies about the specific requirements of your organization’s roles, culture, and strategic goals.

This customization process involves adjusting the criteria, questions, and scenarios used in the assessment tools to reflect the real-world challenges and opportunities within your organization.

Integration with existing HR systems is equally important. By seamlessly incorporating competency assessment tools into the broader HR technology ecosystem, organizations can facilitate a more streamlined and efficient process for collecting, analyzing, and acting on competency data.

This integration enables a holistic view of employee performance, potential, and development needs, supporting more informed decision-making in areas such as hiring, promotions, succession planning, and learning and development.

Effective customization and integration require a collaborative effort involving HR professionals, department leaders, IT specialists, and, in some cases, external vendors.

This collaborative approach ensures that the tools not only meet the specific needs of the organization but also work smoothly within the existing technological and operational framework.

Ultimately, by customizing competency assessment tools to fit their unique context and integrating them with existing HR systems, organizations can enhance the accuracy and relevance of their online competency assessments, improve the employee experience, and drive more impactful talent management outcomes.

Best practices in competency assessment

Ensuring objectivity.

Maintaining objectivity throughout the competency assessment process is crucial to ensuring fair and unbiased results.

Objectivity in assessments guarantees that decisions regarding hiring, promotions, and development are based on merit and actual performance or potential, rather than subjective opinions or biases.

This fairness is essential for building trust in the assessment process among employees and for fostering a culture of transparency and equity within the organization.

To achieve objectivity, organizations can employ several strategies:

Use standardized tools: Implement standardized assessment tools that have been validated and are widely recognized for their reliability and objectivity. These tools should be consistently applied across all assessments to ensure comparability of results.

Structured processes: Develop and follow structured processes for administering assessments and interpreting results. This includes using predetermined criteria and scoring systems that are directly linked to the competencies being evaluated.

Training assessors: Ensure that those conducting the assessments are adequately trained in the tools and processes, as well as in recognizing and mitigating their own biases. Regular training sessions can help assessors stay objective and adhere to best practices.

Multiple assessors: Whenever possible, involve multiple assessors in the evaluation process to minimize individual bias. Using diverse assessment panels can help achieve a more balanced and impartial view of an employee’s competencies.

Transparent communication: Communicate the purpose, process, and criteria of the assessment to all participants beforehand. Transparency helps manage expectations and reinforces the objectivity of the process.

Regular review and calibration self-assessment. : Periodically review and calibrate the assessment tools and processes to ensure they remain relevant, fair, and free from bias. This may include analyzing assessment outcomes for patterns that could indicate bias and making necessary adjustments.

By maintaining objectivity throughout the competency assessment process, organizations can ensure that the outcomes are fair, credible, and valuable for both the employees and the organization.

This objectivity is key to identifying the true strengths and development needs within the workforce, enabling strategic talent management, and fostering a positive organizational culture.

Providing feedback

Offering constructive feedback to employees based on assessment results is a fundamental aspect of their development process.

Constructive feedback provides employees with clear insights into their performance, strengths, and areas for improvement, framed in a manner that encourages growth and learning.

This feedback is essential for guiding employees on their development journey, helping them to understand how they can align their skills and competencies with organizational goals and expectations.

To ensure feedback is effective and fosters development, it should be:

Specific: Identify which behaviors or skills contributed to the assessment outcomes. Specific feedback helps employees understand precisely what they did well and where they need improvement.

Actionable: Provide clear guidance on how employees can improve or further develop their skills. This might include recommendations for training programs, mentorship, or specific actions they can take in their current role.

Balanced: Balance positive feedback with areas for improvement. Recognizing strengths reinforces what employees are doing well, boosting confidence and motivation while highlighting areas for growth directs their development efforts.

Timely: Deliver feedback promptly after the assessment to ensure it is relevant and actionable. Timely feedback allows employees to reflect on their recent experiences and apply insights more effectively.

Supportive: Present feedback in a supportive manner that emphasizes growth and potential. Encourage a two-way dialogue, allowing employees to express their views and discuss their development plans.

By offering constructive feedback in this manner, organizations can not only enhance individual employee development but also strengthen their overall talent management strategy.

Employees who receive regular, constructive feedback are more engaged, motivated, and likely to take proactive steps toward their development, contributing to a dynamic and adaptable workforce.

Continuous improvement

Competency assessment should indeed be viewed as an ongoing process, rather than a one-time event.

As organizations grow and evolve, the skills and competencies they require from their workforce also change.

To remain relevant and effective, the tools and approaches used for competency assessment need to adapt to these changing organizational needs.

Regularly reviewing and updating competency frameworks ensures they reflect the current and future strategic direction of the organization.

This might involve incorporating new competencies that align with emerging industry trends, technological advancements, or shifts in business strategy.

Likewise, the assessment tools themselves may need to be updated or replaced to accurately measure these evolving competencies and provide meaningful insights.

Additionally, an ongoing approach to competency assessment allows for continuous learning and development within the workforce.

It enables organizations to identify skill gaps in real time and respond with targeted training and development initiatives.

This proactive approach to talent development not only helps in building a skilled and adaptable workforce but also supports employee engagement and retention by demonstrating a commitment to their growth and career progression.

To facilitate this dynamic approach, organizations can leverage technology and data analytics to monitor workforce competencies and performance continuously.

This data-driven strategy allows for more agile decision-making regarding talent management, workforce planning, and development priorities.

In essence, treating competency assessment as an ongoing process is crucial for maintaining a competitive edge and fostering a culture of continuous improvement and adaptability within the organization.

Challenges in competency assessment

Resistance to change.

Introducing new assessment tools in an organization can sometimes encounter resistance from both employees and managers.

This resistance often stems from a variety of concerns, including fear of the unknown, discomfort with change, and apprehension about how the new tools will affect performance evaluations and career progression.

Employees might worry about the fairness and accuracy of the new assessments, while managers may be concerned about the additional time and effort required to implement and adapt to these tools.

To overcome resistance and ensure the successful implementation of new assessment tools, organizations can adopt several strategies:

Communicate clearly and early: Provide clear and comprehensive information about the new tools, the reasons for their introduction, and the benefits they are expected to bring to both individuals and the organization. Early communication can help alleviate fears and set realistic expectations.

Involve stakeholders in the selection process: Involving employees and managers in the process of selecting new assessment tools can increase buy-in and reduce resistance. Their input can ensure the chosen tools are relevant, user-friendly, and perceived as fair.

Offer training and support: Providing training sessions and support materials for both assessors and those being assessed can help everyone feel more comfortable and confident in using the new tools. Understanding how to use the tools effectively can mitigate concerns about their impact.

Pilot the tools: Implementing a pilot phase allows a small group of employees and managers to test the new tools in a controlled environment. Feedback from the pilot can be used to make adjustments before a full rollout, demonstrating a commitment to getting the implementation right.

Highlight success stories: Sharing positive outcomes and success stories from the use of new assessment tools can help convince skeptics of their value. Demonstrating how the tools have contributed to career development, improved performance, or better talent management can provide tangible examples of their benefits.

Ensure transparency and fairness: Make the assessment process as transparent as possible, and ensure that the tools are applied consistently and fairly across the organization. Transparency and fairness are key to building trust in the new tools.

By addressing concerns proactively and demonstrating the value of new assessment tools, organizations can overcome resistance and harness these tools’ full potential for enhancing talent management and development.

Data security and privacy

Ensuring the security and privacy of assessment data is indeed a significant concern for organizations, especially given the sensitive nature of the information collected during competency assessments .

This data can include personal details, performance evaluations, and potentially sensitive feedback, all of which require protection to maintain trust and comply with legal and ethical standards.

To safeguard this information, organizations should implement comprehensive data security and privacy measures:

Adopt robust data protection policies: Develop and enforce strict data protection policies that outline how assessment data is collected, stored, used, and shared within the organization. These policies should comply with relevant data protection laws and regulations, such as GDPR in the European Union.

Use secure platforms: Ensure that the technology platforms used for conducting assessments and storing data meet high-security standards. This includes encryption of data in transit and at rest, secure authentication mechanisms, and regular security audits.

Limit access: Restrict access to assessment data to authorized personnel only, based on their role and the need to know. Access controls should be strictly enforced to prevent unauthorized access or breaches.

Train employees: Provide training for employees and managers on data privacy and security best practices. Educating stakeholders about their responsibilities and the importance of protecting assessment data can help prevent accidental breaches or misuse of information.

Regularly review and update security measures: As technology evolves and new threats emerge, it’s essential to review and update security measures regularly. This includes staying informed about the latest security threats and implementing new technologies or practices to enhance data protection.

Have a response plan: Prepare for potential data breaches by having an incident response plan in place. This plan should outline the steps to be taken in the event of a breach, including notification procedures and measures to mitigate the impact.

By prioritizing the security and privacy of assessment data, organizations can protect sensitive information, maintain the trust of their employees, and comply with legal obligations.

This proactive approach to data protection is essential for the integrity and success of competency assessment initiatives.

Future of Competency Assessment Tools

Technological advancements.

Emerging technologies, particularly Artificial Intelligence (AI) and machine learning, are poised to revolutionize the way competency assessments are conducted, offering new levels of efficiency, accuracy, and insight.

These technologies have the potential to transform traditional assessment methods by automating processes, personalizing evaluations, and providing deeper analytics on employee competencies.

Automated assessments: AI can automate the administration and scoring of assessments, significantly reducing the time and resources required. This automation ensures a consistent and unbiased evaluation process, allowing for more frequent assessments without additional workload.

Personalized evaluations: Machine learning algorithms can analyze vast amounts of data to create personalized competency assessments for each employee. By considering an individual’s past performance, learning style, and career aspirations, AI can tailor assessments to identify specific development needs and opportunities, enhancing the relevance and effectiveness of the feedback provided.

Predictive analytics: AI and machine learning can identify patterns and predict future performance based on competency assessment results. This predictive capability can help organizations identify potential leaders, pinpoint skill gaps across teams or departments, and better plan for future workforce needs.

Enhanced feedback mechanisms: AI can generate detailed and nuanced feedback, providing employees with actionable insights into their strengths and areas for improvement. This feedback can be delivered more quickly and frequently, supporting continuous development.

Dynamic skill tracking: As the skills required for success in various roles continue to evolve, AI and machine learning can help organizations keep pace by dynamically updating competency models and assessments. This ensures that evaluations remain relevant in the face of changing industry trends and technological advancements.

Bias reduction: While human assessments are susceptible to unconscious bias, AI and machine learning can help mitigate these biases by focusing on objective data. However, it’s important to monitor and adjust algorithms regularly to avoid perpetuating existing biases in the data.

By leveraging AI and machine learning, organizations can make competency assessments more efficient, personalized, and predictive, significantly enhancing talent management strategies.

However, it’s crucial to approach these technologies thoughtfully, ensuring they are used ethically and complemented by human judgment, especially in interpreting results and making decisions based on assessment data.

Integration with HR Systems

The future of human resources management is poised for a significant shift towards greater integration of competency assessment tools with broader HR management systems.

This integration promises to streamline HR processes, enhance decision-making, and provide a more holistic view of employee performance, development needs, and potential.

By embedding competency assessment tools within comprehensive HR management systems, organizations can achieve several key advancements:

Unified talent and competency management system: Integrating competency assessments with HR systems allows for a unified approach to talent management. This means that recruitment, performance management, learning and development, and succession planning can all be informed by consistent, up-to-date competency data.

This integration facilitates more strategic talent management decisions, ensuring that the right people are in the right roles and are equipped with the necessary skills for success.

Real-time data and insights: With competency assessments integrated into HR systems, organizations can access real-time data on their workforce’s skills and competencies. This immediate access supports agile decision-making, enabling HR and managers to quickly identify skill gaps, tailor development programs, and adjust talent strategies in response to changing organizational needs.

Personalized employee development: The integration allows for more personalized development plans based on detailed competency profiles stored within the HR system. Employees can receive targeted training recommendations, career development opportunities, and feedback tailored to their specific strengths and areas for improvement.

Enhanced employee experience: A seamless integration between competency assessments and HR management systems enhances the employee experience by providing a more streamlined and user-friendly interface for engaging with various HR processes. Employees can easily access their competency assessment checklist, results, development resources, and career opportunities, all from a single platform.

Data-driven culture: The comprehensive insights gained from integrating competency assessments with HR systems promote a data-driven culture within the organization. Decisions regarding hiring, promotions, and development are based on objective data, fostering transparency and trust in HR processes.

Efficiency and cost savings: This integration eliminates the need for multiple standalone systems, reducing both operational complexity and costs. It streamlines workflows for HR professionals and managers, freeing up time and resources that can be better spent on strategic talent management activities.

As organizations continue to navigate an increasingly complex and dynamic business environment, the integration of competency assessment tools with broader HR management systems will be crucial for developing agile, skilled, and engaged workforces capable of driving future success.

Competency assessment tools are indispensable for organizations focused on maximizing their human capital.

These tools enable businesses to systematically evaluate and understand the skills, knowledge, and abilities of their workforce, laying the groundwork for strategic talent management and development.

By carefully selecting the right assessment tools, tailoring them to meet specific organizational needs, and adhering to best practices, companies can unlock the full potential of their employees, leading to significant enhancements in performance and productivity.

Choosing the right tools involves evaluating the specific competencies that are crucial for success in various roles within the organization and selecting assessment instruments that accurately measure these competencies.

Customization is key to ensuring that the assessments reflect the unique culture, values, and strategic objectives of the organization, making the results more relevant and actionable.

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Competency assessment guide

Mastering Competency Assessment: A Comprehensive Guide

Published on October 1st, 2023

Competency assessment lies at the heart of effective talent management and organizational success. In this comprehensive guide, we'll navigate through the essential aspects of competency assessment, exploring what it is, its importance, assessment methods, the role of tools, and even providing you with a competency assessment template

What is Competency Assessment?

Competency assessment is a strategic process that evaluates the skills, knowledge, and abilities of individuals within an organization. It goes beyond simply assessing job performance to delve into the core competencies that employees bring to their roles. Competencies can range from technical skills to soft skills, such as communication, leadership, and problem-solving. By assessing competencies, organizations gain a more profound understanding of their workforce's capabilities.

Types of competency assessment

Competency assessment is a versatile process, and there are various types to choose from, depending on the specific needs and goals of an organization. Here are some common types of competency assessments:

• Self-Assessment: Employees evaluate their own competencies and skills. This method provides insights into how individuals perceive their strengths and areas for improvement. It can be a valuable starting point for development discussions.
• Managerial Assessment: Managers assess the competencies of their team members. This approach offers a leadership perspective on employee capabilities. Managerial assessments are often used for performance evaluations and career development planning.
• Peer Assessment: Colleagues evaluate each other's competencies. This 360-degree feedback method can provide a well-rounded view of an employee's skills and how they interact with others in the workplace.
• 360-Degree Assessment: A comprehensive approach that combines self-assessment, managerial assessment, peer assessment, and sometimes customer or client feedback. It offers a holistic view of an employee's competencies and is commonly used for leadership and executive-level assessments.
• Technical Assessments: Used primarily for roles that require specific technical skills, such as coding or data analysis. Candidates are tested on their technical competencies through examinations, coding challenges, or practical tasks.
• Role-Based Competency Assessment: Focuses on the competencies required for a specific job role. Assessments are tailored to the skills and knowledge relevant to that position. This approach is commonly used for job-specific skill assessments.
• Behavioral Assessment: Evaluates competencies related to behavior and soft skills, such as communication, teamwork, leadership, and problem-solving. Behavioral assessments often include scenarios and situational questions to gauge how individuals might react in different work-related situations.
• Skill Tests and Simulations: Practical assessments that require candidates to demonstrate their competencies by completing real or simulated tasks related to the job. These are frequently used in technical and vocational roles.
• Cultural Fit Assessment: Assesses competencies related to an individual's fit with the organization's culture and values. It measures how well a candidate aligns with the desired workplace culture.
• Job Knowledge Assessments: Focus on a candidate's knowledge and expertise related to a specific industry or field. These assessments typically consist of questions or tasks that assess the candidate's understanding of industry-specific topics.

Each type of competency assessment serves a distinct purpose, and organizations may use a combination of these methods to comprehensively evaluate and develop their workforce. The choice of assessment type should align with the organization's goals, the nature of the roles being assessed, and the desired outcomes of the assessment process.

The Importance of Competency Assessment

Competency assessment holds a pivotal role in shaping organizational success. Let's explore its significance:

• Enhancing Talent Optimization: Competency assessment helps organizations strategically place employees in roles that align with their core competencies. This ensures that employees are engaged in work that complements their strengths, leading to improved job satisfaction and performance.
• Targeted Training and Development: Competency assessments reveal skill gaps within the workforce. This data-driven approach guides organizations in crafting targeted training and development programs. By addressing specific skill deficiencies, organizations ensure their workforce is well-prepared to meet evolving industry demands.
• Effective Performance Management: Competency assessments provide an objective framework for evaluating employee performance. This helps organizations recognize and reward high performers while also identifying areas where improvement is needed.
• Informed Recruitment and Selection : Incorporating competency assessments into the recruitment process ensures that candidates possess not only the required qualifications but also the core competencies essential for the role. This minimizes the risk of hiring mismatches and expedites the integration of new hires into the organization.
• Strategic Succession Planning: Identifying and nurturing future leaders is critical for organizational longevity. Competency assessments pinpoint individuals with leadership potential and provide targeted development to prepare them for leadership roles.

Competency Assessment Methods

Competency assessment methods are the tools organizations use to evaluate skills and abilities. In this guide, we'll explore self-assessment, managerial assessment, peer assessment, and technical assessments, uncovering their significance in shaping talent development and decision-making.

1. Self-Assessment:

• Definition: Self-assessment is a method where employees evaluate their own competencies and skills. They reflect on their abilities, knowledge, and strengths, providing insights into how they perceive their professional capabilities.
• Purpose: Self-assessment encourages employees to take ownership of their development. It helps them identify areas for growth, reflect on their career goals, and pinpoint skills they believe they excel in. It's a valuable tool for fostering self-awareness.

2. Managerial Assessment:

• Definition: Managerial assessment involves managers evaluating the competencies of their team members. This assessment provides a leadership perspective on employee capabilities. Managers typically use predefined competency frameworks to assess their employees' performance against specific criteria.
• Purpose: Managerial assessment is often used for performance evaluations, career development planning, and decision-making related to promotions, salary adjustments, or task assignments. It allows managers to align employee strengths with job requirements.

3. Peer Assessment:

• Definition: Peer assessment is a method where colleagues within the same team or organization evaluate each other's competencies. This approach offers a 360-degree view of an employee's skills, as it incorporates the perspectives of coworkers who interact closely with the individual being assessed.
• Purpose: Peer assessments provide a well-rounded view of an employee's competencies and behaviors. They can reveal interpersonal skills, teamwork, and collaborative abilities that might not be evident in self-assessments or managerial assessments. They are often used for personal development and enhancing team dynamics.

4. Technical Assessments:

• Definition: Technical assessments are primarily used for roles that require specific technical skills or expertise, such as programmers, data analysts, or engineers. Candidates are assessed on their practical knowledge and proficiency in the technical aspects of their job roles.
• Purpose: Technical assessments gauge a candidate's ability to perform job-specific tasks and solve technical challenges. These assessments are critical for ensuring that individuals possess the necessary skills to excel in roles that demand technical expertise. They are also used for skill verification during the hiring process.

Each of these competency assessment methods serves unique purposes within an organization. They can be utilized individually or in combination to comprehensively evaluate employee competencies, facilitate professional development, and make informed decisions related to recruitment, promotion, and performance management. The choice of assessment method should align with the specific goals and needs of the organization and the roles being assessed.

Roles of Competency Assessment Tools in recruitment

1. Efficiency in Candidate Evaluation:

Competency assessment tools streamline the candidate evaluation process. They automate many tasks, such as sending assessments, scoring responses, and generating reports. This efficiency significantly reduces the time and effort required to assess candidate competencies, allowing recruiters to focus on higher-value activities.

2. Data-Driven Decision-Making:

These tools provide recruiters with valuable data and analytics. By capturing and analyzing candidate responses, they offer insights into strengths and weaknesses. Recruiters can make more informed decisions based on data rather than gut feeling, leading to better hiring choices.

3. Standardization of Assessments:

Competency assessment tools ensure consistency in assessments. They apply predefined competency frameworks and scoring criteria uniformly to all candidates. This standardization eliminates bias and ensures that each candidate is evaluated fairly and objectively.

4. Customization and Tailoring:

Many tools allow organizations to customize assessments to match specific job roles and industry requirements. Recruiters can select competencies and questions that are directly relevant to the position, ensuring that candidates are assessed for the skills essential for success in the role.

5. Automated Scoring and Reporting:

Competency assessment tools automate the scoring of candidate responses. This ensures accuracy and eliminates the potential for human error. Additionally they generate detailed reports, making it easy for recruiters to compare candidate competencies and make well-informed decisions.

6. Integration with Applicant Tracking Systems (ATS):

Many competency assessment tools seamlessly integrate with ATS platforms. This integration simplifies the recruitment process by allowing recruiters to initiate assessments directly from the applicant's profile and store assessment results alongside other candidate information.

Pankaj Deshmukh

Pankaj Deshmukh is a digital marketing professional working with HireQuotient. He strongly believes in the never-ending process of learning and stays updated with the latest trends in order to produce valuable content.

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Competency Assessment: 8 Testing Methods Explained

Are your HR leaders increasingly worrying about organizational capability? We get it. Companies need to make the most of their employees’ talent and skills, especially as certain hiring budgets dwindle and resources become more precious.

Since every new hire has the potential to either close or widen the organizational skill gaps , one thing hiring managers can do is turn to the humble competency assessment to find talent for current and future jobs.

Competency-based assessments focus candidate selection on specific skills and abilities that actually matter on the job . A well-structured competency assessment can check for core technical skills and look at essential soft skills like teamwork or collaboration, helping your hiring team quickly identify ideal candidates .

Think it’s time to use competency assessments in your talent acquisition strategy? Here’s how.

TL;DR – Key Takeaways

• Competency assessments test for multiple skills and personal attributes . They’re based on the requirements of specific roles. A role-based competency model makes it easy to match the right candidates to the right positions.
• Competence testing is part of a company’s talent assessment strategy . Organizations need strategic workforce planning to avoid skill gaps . With the economy changing rapidly, anyone who lags behind will feel the effects quickly.
• There are different ways to test competencies . Options include skills testing , task-based mentoring, homework, competency-based interviews, feedback from peers, and even self-assessment. Companies usually employ a blend of methods to suit their recruitment process.
• It’s no easy feat designing a role-specific competency assessment. Luckily, we’ve already done that for you! Browse over 180+ role-based assessments in our test library . Combine them with our pre-built video tests and homework assignments to learn everything you need to know about an individual’s skills.

What is a competency assessment?

A competency assessment is an evaluation of an individual’s skills, experience, and specific competencies against job requirements and duties .

Assessments could include skills tests, interviews, homework assignments, and task-based testing. Regardless of the one you choose to use, the overall aim is to generate enough information to determine whether the individual matches the job requirements and can perform well in the role.

Competency assessments play a key role in various parts of the recruitment process:

• During the initial stages of the recruitment process, competency assessments filter the best-fit candidates from the thousands of applicants, helping you identify candidates who match the required skills and have the right personality traits to succeed.
• Internal competency assessments detect the existence of a skills gap. When competency assessments happen continuously, they help companies detect missing skills. If you use them correctly, you can use them to recruit new talent or plan training for existing workers.
• On an individual level, pre-employment testing helps identify an individual’s abilities and weaknesses. It reveals areas for personal development and helps an individual reskill to keep pace with technology or business practices.

Competency assessments aren’t simple skills tests or personality surveys. They’re tools that empower HR leaders and make it possible to build high-performing teams . They provide information about skill levels within an organization and help onboard qualified talent. When used correctly, they provide a consistent method to achieve skill gap closure whenever that’s required, too.

Skills vs. competencies

A skill is the ability to carry out a function or task by putting learning into practice . This could be a technical skill, such as Python coding or writing Machine Learning algorithms, or it could be a soft skill, like giving presentations to external organizations. Skills tend to be transferrable and not connected to roles within an organization.

Competencies describe the ideal attributes of someone occupying a specific role and may include skills, knowledge, experience, or even personality traits. For example, problem-solving is a skill, while problem-solving while working as a civil engineer is a competency.

When used in the hiring process, a competency-based assessment can h elp put the right talent in the right roles . HR managers often turn to competency tests when conducting organization-wide talent gap analysis and workforce planning. Identifying skill gaps in time allows leaders to organize staff training programs to meet business future needs.

Businesses often use competency assessments outside of the hiring process to determine who to hire or promote. But as we will see, understanding competencies also requires the ability to assess and develop critical skills . So, in practice, skills and competencies are closely related.

The 3 main types of competencies

Core competencies.

Core competencies are behaviors or skills that every employee should have. They form the basis for a robust competency framework.

Example : At the Organization for Economic Cooperation and Development (OECD), core competencies include teamwork, flexible thinking, developing talent, client focus, and strategic networking .

Functional competencies

Functional competencies are skills linked to specific job requirements. Functional competencies vary with seniority and the complexity of a given role. Each job usually has 3-5 essential functional competencies.

Example : Functional competencies for a university IT manager could include network management, cybersecurity, managing cloud infrastructure, and applying educational IT .

Behavioral competencies

Behavioral competencies are soft skills that are connected to roles. Roles may require specific personality traits or cultural skills.

Example : Behavioral competencies for a corporate recruiter could include negotiation, communication skills, building relationships, and results-oriented working practices .

Competence vs. competency: What’s the difference?

Competence and competency are often used interchangeably, but they’re actually different concepts.

When we talk about competence, we usually mean general ability and intelligence. Competency is more precise. It relates to the ability to meet the core requirements of an individual’s role .

Imagine you are looking for a social media manager . We can agree that an “incompetent” person probably won’t be suited to the role. But even an intelligent person who lacks great communication skills may struggle to perform to the required level because they lack the right competencies.

In that sense, competency is like applied competence. In the social media example, you may need a “highly competent individual with the ability to communicate, a deep knowledge of social media, and a talent for marketing.”

Our imaginary employee would need to be competent in using Facebook, running marketing campaigns, and writing engaging content. Without those skills, they would not meet the competency criteria for their job.

What is a competency framework?

Competency frameworks set out the necessary skills for every role in an organization . They allow companies to plan competency testing strategies systematically. With the right framework in place, you should know exactly what skills every role requires—from junior assistants to executive managers.

Any organization with a mixture of technical, administrative, and managerial roles needs a competency framework.

Common elements of a competency model include:

• Soft skills that all workers should have
• Desirable soft skills for individual roles
• Technical skills for individual roles
• Strategic or management skills related to meeting corporate goals

A solid framework informs employees about how to develop their skills, clarifies career progression, and uses skill gap analysis to ensure that current and future jobs meet organizational goals.

The OECD is a good example of how to use frameworks. The international research body groups its role-based competency model into three families (executive leadership, research, and administration). These families contain numerous sub-groups containing competencies for every role.

The model above uses a competency model to specify unique technical competencies for different jobs. But it also links to core competencies that every employee needs. It’s a clever mix of general organizational goals and individual requirements. And most organizations can learn from its structure.

Advantages and challenges of competency assessments in hiring

• Equality : A competency test should be completely neutral (or as neutral as possible). Tests are the same for everyone and generate consistent information about whether staff members meet strategic objectives. This skills assessment data feeds into benchmarked decisions to build the perfect organizational skill set.
• Efficiency : Consistent benchmarking allows you to assess candidates or employees at scale . Customized competency tests take the stress out of workforce assessment. You can quickly determine reskilling requirements . You can also reduce the time to hire new employees.
• Relevancy : Competency assessments are focused on the tasks that workers actually carry out . Following a competency test, employees know what they need to learn to improve their productivity. Candidates get valuable insight into what their role could be like in the future.
• Strategy : Companies can combine a competency assessment system with its strategic skills framework. An organization without a plan to integrate new skills will quickly fall behind. Competency tests let you combine traditional job task analysis with deeper learning. You can discover candidates who really suit your organizational needs.
• Lack of flexibility : Sometimes, competency testing can be too specific. This can result in boring tests with little scope for candidates to express themselves. And testing can even hide skill gaps. For instance, candidates could pass an ultra-specific competency test by accidentally guessing correctly.
• Internal alignmen t: Competency assessments must align with a shared understanding of business objectives. Testing competencies that are out of date or irrelevant is useless. Competency assessment data must serve actual business needs, not abstract ideas of a “good” candidate. That’s why job task analysis is essential before starting competence testing.

8 most popular competency assessment methods

Now, we know what competency assessments are and why they matter. But what techniques can you use in your competency assessment system? Here are eight of the most popular ways to use competency analysis as a business tool.

1. Test-based assessment

A job-specific skills assessment is one of the most effective screening methods. It lets you evaluate candidates by skill levels and instantly spot high-performers. You can often combine hard skills with soft skills into one competency assessment, filtering out candidates with just the right mix of skills, experience, and competence for the position. This way, you can spend your valuable time interviewing highly qualified people instead of wasting time with poor-fit applicants!

One of our customers, Proxify , used competency testing early in the hiring process to pinpoint A-level development talent and fast-track them to the next step. Using our library of 20,000+ expert-created questions, Proxify crafted a highly-tailored competency assessment to automate initial screening and shortened their time-to-hire to just 12.5 days.

You can do the same. Our skills tests draw on expert knowledge and cover everything from technical to marketing to finance roles. Clients can build a customized competency test for every role. And they can streamline recruitment while finding higher-quality candidates.

2. Observation-based assessment

Careful observation over time is one of the best ways to understand whether people are suited to a specific role.

Internships are a great example of how observation works as a competency test. Companies can use skills testing to identify interns with the right core competencies. Interns then have the chance to prove they have what it takes to succeed in real-world environments.

Task-based mentoring, also known as collaborative learning, is a fast, reliable way to determine whether a young professional has the potential to grow into their role. Simply pair high performers with your interns and observe how fast they learn on the job! This should also increase the likelihood of an intern progressing to full employment – saving the company time and money.

3. Interview-based assessment

Sometimes, managers can only learn about competencies in a face-to-face environment. Some people “test” well but don’t deliver in person. Avoid this scenario by matching skills tests with competency-based interviews.

As much as they might sound like it, competency-based interviews aren’t social calls. They compare answers from interviewees with competency criteria and generate valuable insights about a candidate’s soft skills. And there are some elements that they need to include:

• Ideal candidate profiles : Interviewers must know the profile of an ideal candidate. This should be linked to core competencies for the specific role.
• Targeted questions : Carefully planned questions test for skills like problem-solving, analytical thinking, and adaptability. Questions should provide information about how well the candidate meets the desired skills profile for the role.
• Candidate evaluation forms : These forms compare the candidate’s interview performance against competency criteria. They have a standard layout, allowing you to compare many candidates objectively.
• Candidate scorecards : Scorecards work alongside evaluation forms. Interviewers use them to rate how well interviewees meet core requirements.

Remember that interviews must be systematic and fair . Systematically build profiles and scorecards that assess competencies. And use standard templates to ensure that all candidates are treated equally.

4. Homework or project-based assessment

Homework assignments tend to be used after initial screening or skills testing but before an additional round of interviews. Recruiters isolate a pool of potential hires and assign take-home tasks to assess their real-world skills in context.

Candidates have a set amount of time to complete each task. Tasks usually involve more complex questions than standard skills tests, providing recruiters with more information about the candidate’s skill set.

Home assignments are also very diverse. Tasks could involve coding challenges , written tests , presentation planning, or making an improvised sales pitch. However, they must always assess the core competencies of the specific role, so careful task selection is vital.

We rely on home assessments to find elite-tier talent, so we know how effective they can be. And it’s easy to try homework in your own processes. Our library features 500+ pre-built task-based assessments that are ready to use and cover a wide range of roles.

5. Portfolio-based assessment

Portfolio-based competency assessment draws on work previously completed by candidates. Examples include graphic designers, creative directors, video producers, artists, musicians, app developers, and marketers. Portfolios tend to work best in positions where individuals need to show off their creativity.

If you use portfolios as a competency test, be clear about what candidates need to provide. Request examples of their work that relate to the role they’re applying for—not just their best work. The portfolio should show that the individual is well-suited to the role and ideally has relevant experience.

Also, don’t rely on portfolios alone. Combine examples of work with relevant skills testing and homework assignments. That way, you will screen out deceptive candidates and double-check for core competencies.

6. Assessment centers or test days

Assessment centers and test days handle large numbers of candidates at one time, making them a great option for assessing graduate recruits .

Companies can administer a standardized competency test for aptitude and core skills and then easily filter out poor-quality candidates. This is almost always better than choosing from a very similar stack of paper resumes.

However, assessment centers work less well when assessing competency for specialist roles. Roles can be unique, with a relatively small pool of potential candidates. Organizations need to follow high-volume testing with more focused competency testing.

7. Self-assessment

If you want to get a full picture of an individual’s competencies, it sometimes helps to ask the person who knows them best: themselves .

Recruiters can request self-assessments of a candidate’s achievements, skills, and abilities as part of the initial application phase. Focus these self-assessments around core competencies. That way, you force candidates to think about how well they are adapted to the role. And they have a chance to convince you about their passion and talent.

Self-assessment isn’t a solution on its own. You need to combine it with skills testing, interviews, and other competency assessments. However, asking candidates about themselves can be extremely informative.

8. 360-degree feedback assessment

In a 360-degree feedback exercise, HR teams ask colleagues, managers, or even customers to assess how well an individual performs in their role. Feedback should be as broad as possible (hence the 360-degree reference).

Naturally, this assessment method is better suited for employee performance management or talent gap analysis than candidate screening . Participants fill out forms listing a series of core competencies. They rate how well the subject meets these competencies, and there may be written sections to provide more detailed feedback.

Submissions remain confidential, but the subject can see the results. This helps them plan their own development. Assessments also inform managers as they inform organizational plans, arrange training, or assess employee roles.

On the negative side, 360-degree feedback tests for opinions, not concrete facts . This makes it prone to bias. It’s hard to ensure that feedback is totally neutral. And constantly asking colleagues to report on their peers is not always beneficial for employee morale.

7 top benefits of using competency-based assessments

#1. find the most qualified candidate.

Competency assessments ensure that your talent acquisition strategies help you select candidates with essential skills, knowledge, and capabilities.

Competency tests help you quickly focus on candidates who are skilled and suitable for specific roles. You can reduce the number of interviews required and learn far more than resumes could ever provide.

#2. Identify company-wide skills gaps

Competency tests identify skills effectively at a time when global skills gaps are challenging recruiters like never before.

The global skills gap is real. According to the World Economic Forum (WEF), 50% of jobs worldwide will require reskilling by 2025 . 70% of the skills predicted to be essential in 2025 did not appear in lists for 2015 or 2020. In that context, precise competency testing is going to be crucial.

Competency assessment helps you identify the best candidates, reducing the need for costly rehiring processes. It also lets you plug the skill gap by reskilling existing employees—a win-win situation.

#3. Predict future job performance

Competency assessments provide an accurate snapshot of how candidates will contribute to your business over the long run. Getting proof of competency early in the recruitment process enables the hiring team to pinpoint candidates who will succeed in the role, as competency is one of the most reliable predictors of future job performance .

Study after study has demonstrated that general cognitive ability combined with job-specific knowledge and skills play a significant role in predicting future performance on the job. You can make confident hiring decisions to fill current skills gaps and raise the bar of your team’s future performance by paying closer attention to your quality of hire .

#4. Understand employee career progression

Competency assessment detects gaps in an individual’s skills and can help them plan their career development. Managers can work with employees to understand their skill gaps, creating lifelong professional development plans to help their ongoing growth.

This approach forms part of a wider talent management strategy, using skills gap analysis to support a culture of continuous learning.

#5. Deliver rapid onboarding

Competency assessment makes it easy to assess the skills of new employees during the onboarding process.

Managers can then create individualized onboarding plans for each new hire. Plans can include training and mentoring, but employees can start in areas where they are already strong.

#6. Improve employee retention

Competency assessment helps companies retain employees and minimize employee turnover . According to the US Department of Labor, 44% of workers are looking to change roles , with many citing poor growth opportunities as a reason for compromising their career objectives.

Employees value employers who offer training programs to develop their skills and progress their careers. Competency testing lets them know where they stand and shows what individuals must do to improve their skills and move up the organizational hierarchy.

#7. Save money on the recruitment process

Competency testing reduces the cost of hiring by speeding up recruitment. Recruiters can spot the best candidates quickly, and fewer interviews are required. Skills-based hiring also reduces the risk of making a bad hire , requiring costly retraining or even a fresh recruitment process.

As an added bonus, competency testing finds candidates who are well-suited to their roles. They tend to work more productively and are less likely to leave due to low job satisfaction. So, over time, your recruitment needs will decrease.

4 ways to m easure the effectiveness of a competency assessment

Competency assessment is a moving target. The skills that companies need constantly change. And assessments that worked last year may not be exactly right for today’s workforce. That’s why it’s vital to know how effective your competency assessments really are.

Monitoring Key Performance Indicators (KPIs) is the best way to ensure your talent acquisition strategy is on the right track. With the right capability analytics, you can ensure that tests and other assessment methods actually measure the specific skills and competencies that matter.

When deciding on competency assessment metrics to track, consider:

• Employee Performance:  How well do employees perform before and after competency-based training exercises? Does including competency tests in your hiring process help you onboard high-performers?
• Employee Satisfaction and Retention:  Have job satisfaction and retention rates changed after introducing competency testing? Or has competency testing actually led to lower employee morale?
• Promotions:  Are competency assessment measures leading to promotions and career development? Do you see a solid correlation between employees acing their competency assessment and getting promoted?
• Recruitment costs : How much money are you saving by using competency testing?

Hire the right candidates with Toggl Hire skills tests

Knowing how to assess candidates is crucial at a time when finding the best talent is becoming harder (and when everybody has access to the internet and AI to help them fluff out their resumes and portfolios). Competency assessments connect the right candidates with the right roles.

Our competency tests take the stress and risk out of hiring. Whether you’re looking to improve your recruitment process or close skills gaps with existing employees, introducing a competency assessment could be exactly what you need to drive sustainable organizational growth.

Create a free Toggl Hire account and start exploring our library of pre-built competency assessments today!

Juste loves investigating through writing. A copywriter by trade, she spent the last ten years in startups, telling stories and building marketing teams. She works at Toggl Hire and writes about how businesses can recruit really great people.

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In this article

As an HR professional, ensuring that your organization's workforce is skilled, competent, and aligned with the company's goals is crucial for success. Competency assessment is a powerful tool that allows you to identify and measure the skills, knowledge, and behaviors of your employees, enabling you to make informed decisions about talent management, training, and development.

In this guide, we will delve into the world of competency assessment, exploring its various types, the process of designing a competency framework, different assessment methods, and the benefits it brings to your HR processes.

What is Competency Assessment?

Competency assessment is a systematic process of evaluating an individual's skills, knowledge, behaviors, and abilities against predefined competencies relevant to their job roles. It provides a clear understanding of an employee's strengths and areas for improvement, enabling you to make informed talent management decisions.

Why is Competency Assessment Important?

Competency assessment holds immense significance for HR professionals as it serves as a foundation for effective talent management strategies. Here are some reasons why competency assessment is crucial in HR:

• Identifying Skill Gaps: Competency assessment helps HR identify the gap between the skills employees possess and the skills required for their roles. This information is invaluable for designing targeted training and development programs.
• Enhancing Employee Performance: By understanding individual strengths and areas for improvement, HR can provide targeted coaching and support, leading to enhanced employee performance and job satisfaction.
• Optimizing Recruitment and Selection: Incorporating competency assessment in the hiring process enables HR to select candidates who possess the right competencies for specific roles, resulting in improved employee fit and reduced turnover .
• Enabling Succession Planning: Competency assessment aids in identifying high-potential employees, facilitating effective succession planning and leadership development initiatives.
• Driving Organizational Effectiveness: By aligning employee competencies with organizational goals, HR can drive overall effectiveness, productivity, and competitiveness.

Objectives of Competency Assessment in the Workplace

The primary objectives of competency assessment in the workplace are to:

• Ensure Competent Workforce: Assessing competencies ensures that employees possess the required skills and knowledge to perform their roles effectively.
• Provide Employee Feedback: Competency assessment offers valuable feedback to employees about their performance and development areas, fostering a culture of continuous improvement.
• Support Performance Management: Integrating competency assessment with performance management systems allows HR to objectively evaluate employee contributions and align them with organizational objectives.
• Inform Training and Development: Identifying competency gaps helps HR design targeted training programs that address specific skill deficiencies.
• Facilitate Career Growth: Competency assessment enables employees to identify career advancement opportunities and chart a path for their professional growth within the organization.

Benefits of Implementing Competency Assessment

Implementing competency assessment yields several benefits for both organizations and employees:

• Data-Driven Decision Making: Competency assessment provides objective data that empowers HR to make informed decisions about talent management, resource allocation, and strategic planning.
• Improved Employee Engagement: Engaging employees in the assessment process makes them feel valued and supported, leading to increased job satisfaction and commitment.
• Targeted Training and Development: Addressing competency gaps through targeted development initiatives enhances employee skills and performance, contributing to organizational success.
• Effective Succession Planning: Identifying high-potential employees allows organizations to build a robust pipeline of future leaders, ensuring continuity and stability.
• Enhanced Organizational Performance: A competent workforce aligned with organizational goals drives overall performance, productivity, and competitiveness.

Competency assessment is a vital tool that equips you with valuable insights to optimize talent management strategies and propel their organizations towards success.

Types of Competencies

Competencies are the essential skills and attributes required for employees to perform effectively in their roles. They can be broadly categorized into three types:

Core Competencies

Core competencies are the fundamental skills and characteristics that are essential for all employees, regardless of their specific roles. These competencies align with the organization's values and culture. Examples of core competencies in HR include:

• Communication: The ability to convey information clearly and effectively, both verbally and in writing.
• Problem-Solving: Analyzing situations and finding practical solutions to challenges that arise.
• Teamwork: Collaborating with colleagues to achieve shared goals and outcomes.

Functional Competencies

Functional competencies are job-specific skills and knowledge required for a particular role or function within the organization. These competencies are directly related to the job's responsibilities. For HR professionals, functional competencies may include:

• Recruitment and Selection: Proficiency in sourcing and attracting top talent, as well as conducting interviews and assessments.
• Employee Relations: Skills in managing employee conflicts, disciplinary actions, and employee engagement initiatives.
• Training and Development: Expertise in designing and delivering effective training programs to enhance employee skills.

Behavioral Competencies

Behavioral competencies refer to the personal attributes and characteristics that influence an individual's actions and behavior in the workplace. These competencies play a significant role in determining an employee's fit within the organization's culture. In HR, some essential behavioral competencies include:

• Leadership: The ability to inspire and guide others to achieve their full potential.
• Adaptability: Embracing change and being flexible in responding to evolving business needs.
• Emotional Intelligence: Understanding and managing one's emotions and effectively interacting with others.

How to Design an Effective Competency Framework?

Creating a competency framework is the foundation of a successful competency assessment program. This framework outlines the key competencies required for each job role, sets proficiency levels, and establishes a structured approach to evaluating employee skills. Here are the essential steps to design an effective competency framework for your organization:

1. Job Analysis and Role Identification

Start by conducting a comprehensive job analysis to understand the specific requirements of each role. Identify the core responsibilities, tasks, and skills needed for successful job performance.

2. Identifying Relevant Competencies

Based on the job analysis, determine the core, functional, and behavioral competencies that align with the identified roles.

3. Grouping Competencies and Levels

Organize the competencies into logical groups, such as technical skills, soft skills, and leadership skills. Additionally, define proficiency levels for each competency, indicating the desired skill level for each role.

4. Defining Proficiency Levels

Establish clear definitions for each proficiency level to provide employees and managers with a shared understanding of what each level represents.

5. Mapping Competencies to Job Roles

Associate each competency with specific job roles and responsibilities to create a comprehensive competency matrix.

Designing a competency framework tailored to your organization's needs sets the stage for a successful competency assessment program and ensures that you have a clear roadmap for evaluating employee skills and performance.

How to Conduct Competency Assessments?

Once you have developed a competency framework, the next step is to conduct competency assessments to evaluate employees' skills and capabilities. Various methods and tools can be used for this purpose. Here are some commonly used approaches:

1. Self-Assessment

In a self-assessment, employees evaluate their own competencies based on the defined proficiency levels. This approach encourages self-reflection and helps employees take ownership of their development.

2. Manager Assessment

Managers assess their team members' competencies, providing valuable insights from the perspective of those who closely observe their daily performance.

3. Peer Assessment

In a peer assessment, colleagues evaluate each other's competencies, fostering a collaborative and supportive work environment.

4. Behavioral Interviews

Behavioral interviews involve asking candidates to provide real-life examples of situations where they demonstrated specific competencies. These interviews assess a candidate's past behavior as an indicator of future performance.

5. Assessment Centers

Assessment centers involve simulations, exercises, and role-plays that simulate real work scenarios, allowing employees to showcase their competencies in action.

6. 360-Degree Feedback

360-degree feedback involves gathering feedback from multiple sources, including managers, peers, subordinates, and even external stakeholders, providing a holistic view of an employee's competencies.

Choosing the right assessment method depends on various factors, including the organization's culture, the nature of the roles being assessed, and the resources available for conducting assessments.

How to Implement Competency Assessment in HR Processes?

Now that we have explored the types of competencies and the process of designing a competency framework, let's dive into how competency assessment can be integrated into various HR processes to drive organizational success.

Performance Appraisal and Competency Assessment

Integrating competency assessment into the performance appraisal process allows you to measure how well employees are demonstrating the required competencies in their roles. By aligning competencies with performance evaluations, you can provide more objective and data-driven feedback to employees, fostering a culture of continuous improvement.

During performance appraisals, follow these steps:

• Review the employee's competency levels based on assessment results.
• Identify strengths and areas for improvement.
• Use the assessment data to set specific development goals and action plans.

Competency-Based Training and Development

Competency assessment serves as a foundation for identifying skill gaps and designing targeted training and development programs. By understanding which competencies are lacking or need improvement, you can tailor training initiatives to address specific needs and enhance overall employee performance.

To implement competency-based training and development:

• Analyze assessment data to identify skill gaps and training needs.
• Design learning programs that align with the identified competencies.
• Monitor progress and evaluate the impact of training on competency development.

Recruitment and Competency Assessment

Incorporating competency assessment into the recruitment process helps in identifying candidates who possess the required skills and attributes for the job. By integrating competency-based questions and exercises during interviews, you can make more informed hiring decisions.

During the recruitment process:

• Include competency-based questions to assess candidates ' abilities and experiences.
• Use behavioral interviews to gauge candidates' past performance and potential for success.
• Leverage assessment tools to objectively evaluate candidates ' competencies.

Succession Planning and Talent Management

Competency assessment plays a critical role in identifying potential leaders and high-potential employees for succession planning. By evaluating leadership and strategic competencies, HR can nurture talent and prepare future leaders to take on key roles.

For succession planning and talent management:

• Identify employees with high potential based on their competency assessment results.
• Create tailored development plans to groom high-potential individuals for leadership roles.
• Monitor the progress of the talent pool and adjust development initiatives as needed.

Integrating competency assessment into various HR processes enhances decision-making, streamlines talent management efforts, and contributes to building a skilled and motivated workforce.

Competency Assessment Examples

To better understand how competency assessment works in practice, let's explore some specific examples of competency assessments commonly used in HR:

Example 1: Communication Skills Assessment

Objective: To evaluate an employee's communication skills, both verbal and written, to determine their effectiveness in conveying information and ideas.

Assessment Method: Conduct a combination of self-assessment and 360-degree feedback. The employee rates their communication skills based on predefined competency levels, and peers, managers, and subordinates provide feedback on the employee's communication effectiveness.

Outcomes: The assessment reveals the employee's strengths in communication, such as active listening and clarity in written communication. It also identifies areas for improvement, such as assertiveness and adapting communication styles to different audiences. Based on the assessment results, targeted communication training and coaching can be provided.

Example 2: Leadership Competencies Assessment

Objective: To assess leadership competencies in potential candidates for managerial positions to identify the most suitable candidates for promotion.

Assessment Method: Conduct behavioral interviews, situational judgment tests , and assessment center exercises. The assessment focuses on key leadership competencies, such as strategic thinking, decision-making, and team-building.

Outcomes: The assessment identifies candidates who demonstrate strong leadership potential and have the necessary competencies to lead teams effectively. This information guides HR in selecting the best candidates for managerial roles and supports succession planning efforts.

Example 3: Technical Skills Assessment

Objective: To assess technical competencies required for specific job roles, such as software development or engineering positions.

Assessment Method: Administer practical tests, simulations, and skill-based exercises. Measure performance against predefined technical competency criteria.

Outcomes: The assessment provides insights into employees' technical proficiency, helping HR identify skill gaps and areas that require additional training or upskilling. This enables the organization to build a technically proficient workforce.

Example 4: Customer Service Competencies Assessment

Objective: To evaluate customer service competencies of frontline employees in retail or service-oriented industries.

Assessment Method: Use mystery shopper exercises and customer feedback surveys to assess employee interactions with customers. Measure competencies such as empathy, problem-solving, and responsiveness.

Outcomes: The assessment helps identify employees who excel in customer service, leading to recognition and rewards. It also pinpoints areas for improvement, guiding HR in designing customer service training programs.

Example 5: Change Management Competencies Assessment

Objective: To assess an employee's ability to navigate and manage change effectively within the organization.

Assessment Method: Conduct behavioral interviews and role-playing scenarios that simulate change situations. Evaluate competencies such as adaptability, resilience, and communication during change initiatives.

Outcomes: The assessment provides valuable insights into an employee's readiness to embrace change and lead others through transitions. HR can provide targeted support and resources to build change management capabilities.

These competency assessment examples demonstrate how organizations can tailor assessments to specific job roles, competencies, and organizational goals. By using a combination of assessment methods, you gain a comprehensive understanding of employee skills and potential for growth, enabling them to make informed talent management decisions.

Competency Assessment Challenges and Solutions

While competency assessment offers numerous benefits, its implementation can pose certain challenges. Understanding and addressing these challenges are essential for a successful assessment program. Let's explore common challenges and strategies to overcome them:

1. Lack of Employee Buy-In

Challenge: Some employees may resist competency assessment, fearing that it could lead to negative consequences.

Solution: Communicate the purpose and benefits of competency assessment to employees, emphasizing its role in career development and personal growth. Ensure transparency and encourage open dialogue to alleviate concerns.

2. Limited Resources and Time Constraints

Challenge: HR departments often face resource constraints and tight schedules, making it challenging to conduct extensive assessments.

Solution: Leverage technology to streamline the assessment process and gather feedback efficiently. Utilize automated tools and platforms to save time and resources.

3. Resistance to Change

Challenge: Implementing competency assessment may disrupt existing HR processes, leading to resistance from employees or management.

Solution: Engage stakeholders early in the process, involve them in decision-making, and demonstrate the benefits of competency assessment in improving organizational performance.

By proactively addressing these challenges, you can successfully implement competency assessment initiatives that yield positive outcomes.

Competency Assessment Legal and Ethical Considerations

As HR professionals, it is crucial to ensure that competency assessment processes are conducted ethically and in compliance with legal standards.

Ensuring Fairness and Non-Discrimination

• Avoid using assessment methods or criteria that could lead to bias or discrimination against certain groups.
• Validate assessment tools to ensure they measure relevant competencies accurately and fairly for all individuals.
• Train assessors to remain unbiased and objective during the assessment process.

Protecting Employee Privacy and Data Security

• Obtain informed consent from employees before conducting competency assessments and explain how the data will be used.
• Safeguard assessment data and ensure compliance with data protection regulations.
• Anonymize and aggregate data when reporting assessment results to protect individual privacy.

How to Measure the Effectiveness of Competency Assessment?

To determine the impact of competency assessment on HR outcomes, it is essential to establish key performance indicators (KPIs) and analyze assessment data over time. Some KPIs include:

• Employee Performance Improvement: Measure the change in performance metrics after employees participate in competency-based training and development programs.
• Employee Engagement: Assess changes in employee engagement scores, as competency assessment can boost employees' confidence in their skills and motivate them to excel.
• Talent Retention: Track the retention rates of employees who have received competency-based development opportunities, as improved job satisfaction can contribute to higher retention.
• Leadership Pipeline Strength: Evaluate the success of succession planning efforts by monitoring the number of internal promotions and leadership development program participants.

Analyzing KPIs will help you assess the overall impact of competency assessment on the organization's performance and make data-driven decisions to enhance HR processes.

How to Incorporate Competency Assessment into HR Strategy?

Competency assessment should not be seen as a one-off process but rather as an integral part of the overall HR strategy. Here are some strategies for effectively incorporating competency assessment into your HR practices:

• Continuous Improvement: Regularly review and update the competency framework to align with changing business needs and industry trends.
• Employee Development Roadmap: Integrate competency assessment results into individual development plans to create personalized growth opportunities.
• Performance Feedback: Use competency assessment data to provide constructive feedback to employees and recognize their strengths and achievements.

Competency assessment is a powerful tool that empowers you to make informed decisions about talent management, training, and development. By understanding the different types of competencies, designing an effective competency framework, implementing various assessment methods, and addressing challenges, HR can optimize employee performance and foster a culture of continuous improvement. As technology continues to shape the future of HR, leveraging emerging trends and incorporating competency assessment into HR strategy will be key to staying ahead in the dynamic world of talent management.

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10 Essential Tips to Ace a Competency Assessment

What is a competency assessment.

A competency assessment is a systematic process used to evaluate an individual’s knowledge, skills, abilities, and behaviors in relation to specific competencies required for a particular role or task. It is often conducted to measure an individual’s performance against established standards or benchmarks.

Competencies are the measurable attributes or characteristics that define successful performance in a particular specialism or job role. They can include technical skills, soft skills, knowledge areas, or specific behaviors and aptitudes required for effective job performance.

Why Do Employers Use Competency Assessments?

Competency assessments are an integral part of the recruitment process for many roles. In using a competency assessment, recruiters can practically evaluate competencies that can’t be assessed through an interview or CV alone.

There are several reasons why competency assessments are important:

Providing an objective evaluation : Competency assessments provide a structured, standardized method for evaluating candidates. They focus on specific skills, knowledge, abilities, and behaviors relevant to the job requirements, allowing for a fair and unbiased assessment of candidates’ qualifications.

Assess Job Fit : In evaluating the specific competencies, knowledge, skills, and behaviors that are necessary to perform effectively in a particular role, recruiters can identify candidates who best fit the position and the organization’s needs.

Predicting performance : By evaluating their proficiency in critical competencies, such as problem-solving, communication, teamwork, adaptability, and leadership, employers can gauge how well candidates are likely to perform in similar situations on the job.

Reducing bias: Traditional methods like resume screening and interviews can be influenced by unconscious biases, such as gender, ethnicity, or educational background. Competency assessments focus on objective criteria, reducing the impact of bias and promoting fairness in candidate evaluations.

Time and cost efficiency: By using competency assessments, employers can screen a large pool of applicants and identify the most suitable candidates for the role. This approach saves time and money, enabling recruiters to focus their efforts on individuals with the desired competencies rather than those who do not have the competencies for the role.

What To Expect

Employers use different types of competency assessments to evaluate individuals.

The format of a competency assessment can vary depending on the organization, industry, and specific purpose of the evaluation.

In general, all competency assessments are timed online assessments that can be taken at a time that suits the candidate. The time limit for each competency assessment varies depending on the test. Typical time limits range from 5 minutes to 60 minutes.

What to expect when sitting a competency assessment depends on the type of assessment.

In all competency assessments, candidates are provided with a short set of instructions and practice questions that they must answer. These questions enable candidates to familiarize themselves with the questions’ layout and how they select their preferred answer.

Once these practice questions have been completed, candidates move on to the assessed part of the test, completing as many questions as possible in the allotted time.

Outlined below are the different types of competency assessments, the format, and what is expected for each evaluation.

Self-assessment

A competency self-assessment test typically includes a series of questions or statements designed to assess an individual’s skills, knowledge, abilities, and behaviors related to specific competencies.

Candidates are given a list of statements with statements evaluating a specific competency. The statements are followed by response options or scales. Candidates must rank or rate their proficiency or level of agreement with the response.

Response options can include

• Strongly agree
• Strongly disagree

Common rating scales include Likert scales (e.g., 1 to 5 or 1 to 7) or proficiency levels (e.g., beginner, intermediate, advanced).

Reasoning tests

A reasoning test is a written or practical test to assess specific competencies.

In a reasoning test, candidates are given a set of questions, followed by multiple-choice answers. They must determine which of the multiple-choice answers is correct, selecting this choice as their preferred answer.

It is worth noting that in some reasoning tests, candidates can revisit previous questions; others require candidates to answer questions before moving on to the next question. This depends on the type of reasoning assessment used by the employer.

Upon completion of the reasoning test, candidates either submit their answers or the answers are automatically sent to recruiters for evaluation.

Simulations or Role-plays

Individuals are placed in realistic scenarios to observe their competency in action.

Candidates are given information to read and prepare before discussing role-playing or discussing their responses with the assessor. They may also need to explain their rationale for their response as part of the assessment.

Candidates can typically expect to receive a response on whether they have been successful in a competency test within 48 hours of completing the test, although this can vary by employer.

10 Tips To Ace Your Competency Assessment

While sitting a competency assessment may seem daunting at first, there are several things you can do to ensure your natural abilities, talents, and experience shine through.

Outlined below are some tips to help you ace your competency assessments.

1. Understand the Assessment Criteria

Familiarize yourself with the competency areas and skills that will be assessed. Review the instructions and ensure you understand what is expected before starting the test as once the test has begun, you are unable to ask questions.

Considering the assessment criteria during the test helps contextualize questions such as those asked in situational, simulation or self assessment competency assessments.

2. Create a schedule

Don’t leave your preparation to the last minute. Create a study schedule and allocate ample time to study and practice all the skills and competencies you will be assessed on. This means you can refresh your memory on knowledge areas that will be assessed, spending equal time on all areas being assessed.

3. Review Relevant Material

Review relevant materials covering the assessed competencies, such as textbooks, reference guides, or online resources. Refresh your memory on the key concepts and practical applications that you will be assessed on, such as mathematical or mechanical concepts or principles.

4. Seek Clarification

If you are uncertain about any assessment or have any questions, contact your recruiter for clarification. Understanding what is expected in each assessment will help you prepare effectively and build your confidence going into the test.

5. Practice The Assessments

Practice sample tests. Simulate test conditions so you experience the time pressure you will feel in the test itself.

Becoming familiar with the format, style of questions, and test length helps build your confidence. It also enables you to practice time management skills meaning you effectively manage your time in the actual test and answer as many questions as possible.

6. Use Self-Assessment Tools

Use self-assessment tools or rubrics to evaluate your performance in the competency areas. This will enable you to identify areas where you excel and areas where you may need more practice. Don’t neglect areas that you feel are strength areas. Hone your skills and competencies in these areas to ensure you perform to the best you can.

7. Collaborate with Peers

Create or participate in study groups with peers who are also preparing for competency assessments. Sharing knowledge, discussing concepts, and solving problems together can enhance your understanding and retention. It can also help you see things from a different perspective helping to hone your skills and competencies.

8. Manage Your Time

Develop a study schedule and allocate sufficient time for each competency area. Effective time management will help you cover all the necessary material and prevent last-minute cramming. In the test itself, ensure you know how long you have to complete the test and manage your time accordingly.

9. Ensure you are well rested

Give yourself the best opportunity to perform to the best of your ability by ensuring you are well-rested. This means getting a good night’s sleep before your competency assessments. On test day, make sure you have eaten and are well hydrated. Doing so ensures you are in the right frame of mind to tackle the competency assessments.

10. Stay Calm and Confident

Take confidence in your preparation. On the assessment day, stay calm and maintain confidence in your abilities. Take deep breaths, read the questions or instructions carefully, and approach each task with a clear mind. If you feel one part of the test hasn’t gone well, don’t dwell on it. Move on to the next question and remain focused and confident.

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Why Every Educator Needs to Teach Problem-Solving Skills

Strong problem-solving skills will help students be more resilient and will increase their academic and career success .

Want to learn more about how to measure and teach students’ higher-order skills, including problem solving, critical thinking, and written communication?

Problem-solving skills are essential in school, careers, and life.

Problem-solving skills are important for every student to master. They help individuals navigate everyday life and find solutions to complex issues and challenges. These skills are especially valuable in the workplace, where employees are often required to solve problems and make decisions quickly and effectively.

Problem-solving skills are also needed for students’ personal growth and development because they help individuals overcome obstacles and achieve their goals. By developing strong problem-solving skills, students can improve their overall quality of life and become more successful in their personal and professional endeavors.

Problem-Solving Skills Help Students…

   develop resilience.

Problem-solving skills are an integral part of resilience and the ability to persevere through challenges and adversity. To effectively work through and solve a problem, students must be able to think critically and creatively. Critical and creative thinking help students approach a problem objectively, analyze its components, and determine different ways to go about finding a solution.  

This process in turn helps students build self-efficacy . When students are able to analyze and solve a problem, this increases their confidence, and they begin to realize the power they have to advocate for themselves and make meaningful change.

When students gain confidence in their ability to work through problems and attain their goals, they also begin to build a growth mindset . According to leading resilience researcher, Carol Dweck, “in a growth mindset, people believe that their most basic abilities can be developed through dedication and hard work—brains and talent are just the starting point. This view creates a love of learning and a resilience that is essential for great accomplishment.”

    Set and Achieve Goals

Students who possess strong problem-solving skills are better equipped to set and achieve their goals. By learning how to identify problems, think critically, and develop solutions, students can become more self-sufficient and confident in their ability to achieve their goals. Additionally, problem-solving skills are used in virtually all fields, disciplines, and career paths, which makes them important for everyone. Building strong problem-solving skills will help students enhance their academic and career performance and become more competitive as they begin to seek full-time employment after graduation or pursue additional education and training.

  Resolve Conflicts

In addition to increased social and emotional skills like self-efficacy and goal-setting, problem-solving skills teach students how to cooperate with others and work through disagreements and conflicts. Problem-solving promotes “thinking outside the box” and approaching a conflict by searching for different solutions. This is a very different (and more effective!) method than a more stagnant approach that focuses on placing blame or getting stuck on elements of a situation that can’t be changed.

While it’s natural to get frustrated or feel stuck when working through a conflict, students with strong problem-solving skills will be able to work through these obstacles, think more rationally, and address the situation with a more solution-oriented approach. These skills will be valuable for students in school, their careers, and throughout their lives.

    Achieve Success

We are all faced with problems every day. Problems arise in our personal lives, in school and in our jobs, and in our interactions with others. Employers especially are looking for candidates with strong problem-solving skills. In today’s job market, most jobs require the ability to analyze and effectively resolve complex issues. Students with strong problem-solving skills will stand out from other applicants and will have a more desirable skill set.

In a recent opinion piece published by The Hechinger Report , Virgel Hammonds, Chief Learning Officer at KnowledgeWorks, stated “Our world presents increasingly complex challenges. Education must adapt so that it nurtures problem solvers and critical thinkers.” Yet, the “traditional K–12 education system leaves little room for students to engage in real-world problem-solving scenarios.” This is the reason that a growing number of K–12 school districts and higher education institutions are transforming their instructional approach to personalized and competency-based learning, which encourage students to make decisions, problem solve and think critically as they take ownership of and direct their educational journey.

Problem-Solving Skills Can Be Measured and Taught

Research shows that problem-solving skills can be measured and taught. One effective method is through performance-based assessments which require students to demonstrate or apply their knowledge and higher-order skills to create a response or product or do a task.

What Are Performance-Based Assessments?

With the No Child Left Behind Act (2002), the use of standardized testing became the primary way to measure student learning in the U.S. The legislative requirements of this act shifted the emphasis to standardized testing, and this led to a  decline in nontraditional testing methods .

But   many educators, policy makers, and parents have concerns with standardized tests. Some of the top issues include that they don’t provide feedback on how students can perform better, they don’t value creativity, they are not representative of diverse populations, and they can be disadvantageous to lower-income students.

While standardized tests are still the norm, U.S. Secretary of Education Miguel Cardona is encouraging states and districts to move away from traditional multiple choice and short response tests and instead use performance-based assessment, competency-based assessments, and other more authentic methods of measuring students abilities and skills rather than rote learning. 

Performance-based assessments  measure whether students can apply the skills and knowledge learned from a unit of study. Typically, a performance task challenges students to use their higher-order skills to complete a project or process. Tasks can range from an essay to a complex proposal or design.

Preview a Performance-Based Assessment

Want a closer look at how performance-based assessments work?  Preview CAE’s K–12 and Higher Education assessments and see how CAE’s tools help students develop critical thinking, problem-solving, and written communication skills.

Performance-Based Assessments Help Students Build and Practice Problem-Solving Skills

In addition to effectively measuring students’ higher-order skills, including their problem-solving skills, performance-based assessments can help students practice and build these skills. Through the assessment process, students are given opportunities to practically apply their knowledge in real-world situations. By demonstrating their understanding of a topic, students are required to put what they’ve learned into practice through activities such as presentations, experiments, and simulations. 

This type of problem-solving assessment tool requires students to analyze information and choose how to approach the presented problems. This process enhances their critical thinking skills and creativity, as well as their problem-solving skills. Unlike traditional assessments based on memorization or reciting facts, performance-based assessments focus on the students’ decisions and solutions, and through these tasks students learn to bridge the gap between theory and practice.

Performance-based assessments like CAE’s College and Career Readiness Assessment (CRA+) and Collegiate Learning Assessment (CLA+) provide students with in-depth reports that show them which higher-order skills they are strongest in and which they should continue to develop. This feedback helps students and their teachers plan instruction and supports to deepen their learning and improve their mastery of critical skills.

Explore CAE’s Problem-Solving Assessments

CAE offers performance-based assessments that measure student proficiency in higher-order skills including problem solving, critical thinking, and written communication.

• College and Career Readiness Assessment (CCRA+) for secondary education and
• Collegiate Learning Assessment (CLA+) for higher education.

Our solution also includes instructional materials, practice models, and professional development.

We can help you create a program to build students’ problem-solving skills that includes:

• Measuring students’ problem-solving skills through a performance-based assessment    
• Using the problem-solving assessment data to inform instruction and tailor interventions
• Teaching students problem-solving skills and providing practice opportunities in real-life scenarios
• Supporting educators with quality professional development

Get started with our problem-solving assessment tools to measure and build students’ problem-solving skills today! These skills will be invaluable to students now and in the future.

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An IERI – International Educational Research Institute Journal

• Open access
• Published: 10 December 2014

The acquisition of problem solving competence: evidence from 41 countries that math and science education matters

• Ronny Scherer 1 , 2 &
• Jens F Beckmann 3  

Large-scale Assessments in Education volume  2 , Article number:  10 ( 2014 ) Cite this article

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On the basis of a ‘problem solving as an educational outcome’ point of view, we analyse the contribution of math and science competence to analytical problem-solving competence and link the acquisition of problem solving competence to the coherence between math and science education. We propose the concept of math-science coherence and explore whether society-, curriculum-, and school-related factors confound with its relation to problem solving.

By using the PISA 2003 data set of 41 countries, we apply multilevel regression and confounder analyses to investigate these effects for each country.

Our results show that (1) math and science competence significantly contribute to problem solving across countries; (2) math-science coherence is significantly related to problem solving competence; (3) country-specific characteristics confound this relation; (4) math-science coherence is linked to capability under-utilisation based on science performance but less on math performance.

Conclusions

In sum, low problem solving scores seem a result of an impeded transfer of subjectspecific knowledge and skills (i.e., under-utilisation of science capabilities in the acquisition of problem solving competence), which is characterised by low levels of math-science coherence.

The ability to solve real-world problems and to transfer problem-solving strategies from domain-specific to domain-general contexts and vice versa has been regarded an important competence students should develop during their education in school (Greiff et al. [ 2013 ]; van Merriënboer [ 2013 ]). In the context of large-scale assessments such as the PISA study problem solving competence is defined as the ability to solve cross-disciplinary and real-world problems by applying cognitive skills such as reasoning and logical thinking (Jonassen [ 2011 ]; OECD [ 2004 ]). Since this competence is regarded a desirable educational outcome, especially math and science educators have focused on developing students’ problem solving and reasoning competence in their respective domain-specific contexts (e.g., Kind [ 2013 ]; Kuo et al. [ 2013 ]; Wu and Adams [ 2006 ]). Accordingly, different conceptual frameworks were proposed that describe the cognitive processes of problem solving such as understanding the problem, building adequate representations of the problem, developing hypotheses, conducting experiments, and evaluating the solution (Jonassen [ 2011 ]; OECD [ 2005 ]). In comparing these approaches in math and science, it seems apparent that there is a conceptual overlap between the problem solving models in these two domains. This overlap triggers the question regarding its contribution to the development of students’ cross-curricular problem-solving competence (Abd-El-Khalick et al. [ 2004 ]; Bassok and Holyoak [ 1993 ]; Hiebert et al. [ 1996 ]).

The operationalization and scaling of performance in PISA assessments enables direct contrasting of scores in students’ competences in math and problem solving. Leutner et al. ([ 2012 ]) suggest that discrepancies between math and problem solving scores are indicative of the relative effectiveness of math education (OECD [ 2004 ]). In line with a “Capability-Utilisation Hypothesis”, it is assumed that math scores that negatively deviate from their problem solving counterpart signify an under-utilisation of students’ problem-solving capabilities as indicated by their scores in generic problem solving.

We intend to extend this view in two ways: First, by introducing the concept of math-science coherence we draw the focus on the potential synergistic link between math and science education and its contribution to the acquisition of problem solving competence. Second, the introduction of a Capability Under-Utilisation Index will enable us to extend the focus of the Capability-Utilisation Hypothesis to both, math and science education. The combination of the concept of math-science coherence with the notion of capability-utilisation will help to further explore the facilitating processes involved in the transition of subject-specific knowledge and skills to the acquisition of problem solving competence. These insights are expected to contribute to a better understanding of meaningful strategies to improve and optimize educational systems in different countries.

Theoretical framework

Problem solving as an educational goal.

In the PISA 2003 framework, problem solving is referred to as “an individual’s capacity to use cognitive processes to resolve real, cross-disciplinary situations where the solution path is not immediately obvious” (OECD [ 2004 ], p. 156). This definition is based on the assumption of domain-general skills and strategies that can be employed in various situations and contexts. These skills and strategies involve cognitive processes such as: Understanding and characterizing the problem, representing the problem, solving the problem, reflecting and communicating the problem solution (OECD [ 2003 ]). Problem solving is often regarded a process rather than an educational outcome, particularly in research on the assessment and instruction of problem solving (e.g., Greiff et al. [ 2013 ]; Jonassen [ 2011 ]). This understanding of the construct is based on the assumption that problem solvers need to perform an adaptive sequence of cognitive steps in order to solve a specific problem (Jonassen [ 2011 ]). Although problem solving has also been regarded as a process skill in large-scale assessments such as the PISA 2003 study, these assessments mainly focus on problem solving performance as an outcome that can be used for international comparisons (OECD [ 2004 ]). However, problem solving competence was operationalized as a construct comprised of cognitive processes. In the context of the PISA 2003 study, these processes were referred to as analytical problem solving, which was assessed by static tasks presented in paper-and-pencil format. Analytical problem-solving competence is related to school achievement and the development of higher-order thinking skills (e.g., Baumert et al. [ 2009 ]; OECD [ 2004 ]; Zohar [ 2013 ]). Accordingly, teachers and educators have focused on models of problem solving as guidelines for structuring inquiry-based processes in their subject lessons (Oser and Baeriswyl [ 2001 ]). Van Merriënboer ([ 2013 ]) pointed out that problem solving should not only be regarded a mere instructional method but also as a major educational goal. Recent curricular reforms have therefore shifted towards the development of problem solving abilities in school (Gallagher et al. [ 2012 ]; Koeppen et al. [ 2008 ]). These reforms were coupled with attempts to strengthen the development of transferable skills that can be applied in real-life contexts (Pellegrino and Hilton [ 2012 ]). For instance, in the context of 21 st century skills, researchers and policy makers have agreed on putting emphasis on fostering skills such as critical thinking, digital competence, and problem solving (e.g., Griffin et al. [ 2012 ]). In light of the growing importance of lifelong learning and the increased complexity of work- and real-life problem situations, these skills are now regarded as essential (Griffin et al. [ 2012 ]; OECD [ 2004 ]). Hence, large-scale educational studies such as PISA have shifted towards the assessment and evaluation of problem solving competence as a 21 st century skill.

The PISA frameworks of math and science competence

In large-scale assessments such as the PISA studies, students’ achievement in the domains of science and mathematics play an important role. Moreover, scientific and mathematical literacy are now regarded essential to being a reflective citizen (Bybee [ 2004 ]; OECD [ 2003 ]). Generally, Baumert et al. ([ 2009 ]) have shown that students’ math and science achievements are highly related to domain-general ability constructs such as reasoning or intelligence. In this context, student achievement refers to “the result of domain-specific processes of knowledge acquisition and information processing” (cf. Baumert et al. [ 2009 ], p. 169). This line of argument is reflected in definitions and frameworks of scientific and mathematical literacy, which are conceptualized as domain-specific competences that are hierarchically organized and build upon abilities closely related to problem solving (Brunner et al. [ 2013 ]).

Scientific literacy has been defined within a multidimensional framework, differentiating between three main cognitive processes, namely describing, explaining, and predicting scientific phenomena, understanding scientific investigations, and interpreting scientific evidence and conclusions (OECD [ 2003 ]). In addition, various types of knowledge such as ‘knowledge about the nature of science’ are considered as factors influencing students’ achievements in this domain (Kind [ 2013 ]). We conclude that the concept of scientific literacy encompasses domain-general problem-solving processes, elements of scientific inquiry (Abd-El-Khalick et al. [ 2004 ]; Nentwig et al. [ 2009 ]), and domain-specific knowledge.

The definition of mathematical literacy refers to students’ competence to utilise mathematical modelling and mathematics in problem-solving situations (OECD [ 2003 ]). Here, we can also identify overlaps between cognitive processes involved in mathematical problem solving and problem solving in general: Structuring, mathematizing, processing, interpreting, and validating (Baumert et al. [ 2009 ]; Hiebert et al. [ 1996 ]; Kuo et al. [ 2013 ]; Polya [ 1945 ]). In short, mathematical literacy goes beyond computational skills (Hickendorff [ 2013 ]; Wu and Adams [ 2006 ]) and is conceptually linked to problem solving.

In the PISA 2003 framework, the three constructs of math, science, and problem solving competence overlap conceptually. For instance, solving the math items requires reasoning, which comprises analytical skills and information processing. Given the different dimensions of the scientific literacy framework, the abilities involved in solving the science items are also related to problem solving, since they refer to the application of knowledge and the performance of inquiry processes (OECD [ 2003 ]). This conceptual overlap is empirically supported by high correlations between math and problem solving ( r  = .89) and between science and problem solving ( r  = .80) obtained for the sample of 41 countries involved in PISA 2003 (OECD [ 2004 ]). The relation between math and science competence was also high ( r  = .83). On the one hand, the sizes of the inter-relationships, give rise to the question regarding the uniqueness of each of the competence measures. On the other hand, the high correlations indicate that problem-solving skills are relevant in math and science (Martin et al. [ 2012 ]). Although Baumert et al. ([ 2009 ]) suggest that the domain-specific competences in math and science require skills beyond problem solving (e.g., the application of domain-specific knowledge) we argue from an assessment perspective that the PISA 2003 tests in math, science, and problem solving measure predominantly basic academic skills relatively independent from academic knowledge (see also Bulle [ 2011 ]).

The concept of capability-utilisation

Discrepancies between students’ performance in math/science and problem solving were studied at country level (OECD [ 2004 ]) and were, for example for math and problem solving scores, interpreted in two ways: (1) If students’ perform better in math than in problem solving, they would “have a better grasp of mathematics content […] after accounting for the level of generic problem-solving skills…” (OECD [ 2004 ], p. 55); (2) If students’ estimated problem-solving competence is higher than their estimated math competence, “… this may suggest that students have the potential to achieve better results in mathematics than that reflected in their current performance…” (OECD [ 2004 ], p. 55). Whilst the latter discrepancy constitutes a capability under-utilisation in math, the former suggests challenges in utilising knowledge and skills acquired in domain-specific contexts in domain-unspecific contexts (i.e., transfer problem).

To quantify the degree to which students are able to transfer their problem solving capabilities from domain-specific problems in math or science to cross-curricular problems, we introduce the Capability Under-Utilisation Index (CUUI) as the relative difference between math or science and problem solving scores:

A positive CUUI indicates that the subject-specific education (i.e., math or science) in a country tends to under-utilise its students’ capabilities to problem solve. A negative CUUI indicates that a country’s educational system fails to fully utilise its students’ capabilities to acquire math and science literacy in the development of problem solving. The CUUI reflects the relative discrepancies between the achievement scores in different domains a .

The concept of math-science coherence

In light of the conceptual and empirical discussion on the relationship between math, science, and problem solving competence, we introduce the concept of math-science coherence as follows: First, math-science coherence refers to the set of cognitive processes involved in both subjects and thus represents processes which are related to reasoning and information processing, relatively independent from domain-specific knowledge. Second, math-science coherence reflects the degree to which math and science education is harmonized as a feature of the educational environment in a country. This interpretation is based on the premise that PISA measures students’ competence as educational outcomes (OECD [ 2004 ]). The operationalization of math-science coherence is realized by means of the correlation between math and science scores [ r (M,S)] at the country level. Low math-science coherence indicates that students who are successful in the acquisition of knowledge and skills in math are not necessarily successful in the acquisition of knowledge and skills in science and vice versa.

On the basis of this conceptualization of math-science coherence, we expect a significant and positive relation to problem solving scores, since the conceptual overlap between mathematical and scientific literacy refers to cognitive abilities such as reasoning and information processing that are also required in problem solving (Arts et al. [ 2006 ]; Beckmann [ 2001 ]; Wüstenberg et al. [ 2012 ]). Hence, we assert that math-science coherence facilitates the transfer of knowledge, skills, and insights across subjects resulting in better problem solving performance (OECD [ 2004 ]; Pellegrino and Hilton [ 2012 ]).

We also assume that math-science coherence as well as capability utilisation is linked to characteristics of the educational system of a country. For instance, as Janssen and Geiser ([ 2012 ]) and Blömeke et al. ([ 2011 ]) suggested, the developmental status of a country, measured by the Human Development Index (HDI; UNDP [ 2005 ]), is positively related to students’ academic achievements as well as to teachers’ quality of teaching. Furthermore, the socio-economic status of a country co-determines characteristics of its educational system, which ultimately affects a construct referred to as national intelligence (Lynn and Meisenberg [ 2010 ]). Research also indicated that curricular settings and educational objectives are related to school achievement in general (Bulle [ 2011 ]; Martin et al. [ 2004 ]). Besides these factors, school- and classroom-related characteristics might also confound the relation between math-science coherence and problem solving. For instance, the schools’ autonomy in developing curricula and managing educational resources might facilitate the incorporation of inquiry- and problem-based activities in science lessons (Chiu and Chow [ 2011 ]). These factors have been discussed as being influential to students’ competence development (OECD [ 2004 ], [ 2005 ]). Ewell ([ 2012 ]) implies that cross-national differences in problem solving competence might be related to differences in education and in using appropriate teaching material. These factors potentially confound the relation between math-science coherence and problem solving.

Discrepancies between math and problem solving scores are discussed in relation to quality of education. Although research has found that crossing the borders between STEM subjects positively affects students’ STEM competences (e.g., National Research Council NRC [ 2011 ]), we argue that the PISA analyses have fallen short in explaining cross-country differences in the development of problem solving competence, since they ignored the link between math and science competences and the synergistic effect of learning universally applicable problem-solving skills in diverse subject areas. Hence, we use the concept of math-science coherence to provide a more detailed description of the discrepancies between problem solving and domain-specific competences. In this regard, we argue that the coherence concept indicates the synergistic potential and students’ problem-solving competence the success of transfer.

The present study

The current study is based on the premise that in contrast to math and science competence problem solving competence is not explicitly taught as a subject at school. Problem solving competence, however, is an expected outcome of education (van Merriënboer [ 2013 ]). With the first step in our analyses, we seek to establish whether math and science education are in fact main contributors to the acquisition of problem solving competence. On the basis of this regression hypothesis, we subsequently focus on the question whether there are significant and systematic differences between countries ( Moderation-Hypothesis ). In light of the conceptual overlap due to cognitive processes involved in dealing with math, science and problem solving tasks and the shared item format employed in the assessments, we expect math and science competence scores to substantially predict scores in problem solving competence. Furthermore, since math and science education are differently organized across the 41 countries participating in the PISA 2003 study, differences in the contribution are also expected.

On the basis of these premises, we introduce the concept of math-science coherence, operationalised as the correlation between math and science scores [ r (M,S)], and analyse its relationship to problem solving and the effects of confounders (i.e., country characteristics) as a step of validation. Since math, science, and problem solving competence show a conceptual overlap, we expect problem solving and math-science coherence to be positively related. Countries’ educational systems differ in numerous aspects, their educational structure, and their educational objectives. Countries also differ with regard to the frequency of assessments, the autonomy of schools in setting up curricula and resources, and the educational resources available. Consequently, we expect the relation between math-science coherence and problem solving competence to be confounded by society-, curriculum-, and school-related factors ( Confounding-Hypothesis ).

In a final step, we aim to better understand the mechanisms with which math and science education contributes to the acquisition of problem-solving competence by exploring how math-science coherence, capability utilisation, and problem solving competence are related. We thus provide new insights into factors related to the transfer between students’ domain-specific and cross-curricular knowledge and skills ( Capability-Utilisation Hypothesis ).

In PISA 2003, a total sample of N  = 276,165 students (49.4% female) from 41 countries participated. The entire sample was randomly selected by applying a two-step sampling procedure: First, schools were chosen within a country. Second, students were chosen within these schools. This procedure consequently led to a clustered structure of the data set, as students were nested in 10,175 schools. On average, 27 students per school were chosen across schools within countries. Students’ mean age was 15.80 years ( SD  = 0.29 years) ranging from 15.17 to 16.25 years.

In the PISA 2003 study, different assessments were used in order to measure students’ competence in math, science, and problem solving. These assessments were administered as paper-and-pencil tests within a multi-matrix design (OECD [ 2005 ]). In this section, the assessments and further constructs are described that served as predictors of the contribution of math and science competence to problem solving at the country level.

Student achievement in math, science, and problem solving

In order to assess students’ competence to solve cross-curricular problems (i.e., analytical problem solving requiring information retrieval and reasoning), students had to work on an analytical problem-solving test. This test comprised a total of 19 items (7 items referred to trouble-shooting, 7 items referred to decision-making, and 5 items referred to system analysis and design; see OECD [ 2004 ]). Items were coded according to the PISA coding scheme, resulting in dichotomous and polytomous scores (OECD [ 2005 ]). Based on these scores, models of item response theory were specified in order to obtain person and item parameters (Leutner et al. [ 2012 ]). The resulting plausible values could be regarded as valid indicators of students’ abilities in problem solving (Wu [ 2005 ]). The problem solving test showed sufficient reliabilities between .71 and .89 for the 41 countries.

To assess mathematical literacy as an indicator of math competence , an 85-items test was administered (for details, refer to OECD [ 2003 ]). Responses were dichotomously or polytomously scored. Again, plausible values were obtained as person ability estimates and reliabilities were good (range: 0.83 – 0.93). In the context of mathematical literacy, students were asked to solve real-world problems by applying appropriate mathematical models. They were prompted to “identify and understand the role mathematics plays in the world, to make well-founded judgements and to use […] mathematics […]” (OECD [ 2003 ], p. 24).

Scientific literacy as a proxy for science competence was assessed by using problems referring to different content areas of science in life, health, and technology. The reliability estimates for the 35 items in this test ranged between .68 and .88. Again, plausible values served as indicators of this competence.

Country-specific characteristics

In our analyses, we incorporated a range of country-specific characteristics that can be subdivided into three main categories. These are: society-related factors, curriculum-related factors, and school-related factors. Country-specific estimates of National Intelligence as derived by Lynn and Meisenberg ([ 2010 ]) as well as the Human Development Index (HDI) were subsumed under society-related factors . The HDI incorporates indicators of a country’s health, education, and living standards (UNDP [ 2005 ]). Both variables are conceptualised as factors that contribute to country-specific differences in academic performance.

Holliday and Holliday ([ 2003 ]) emphasised the role of curricular differences in the understanding of between-country variance in test scores. We incorporated two curriculum-related factors in our analyses. First, we used Bulle’s ([ 2011 ]) classification of curricula into ‘progressive’ and ‘academic’. Bulle ([ 2011 ]) proposed this framework and classified the PISA 2003 countries according to their educational model. In her framework, she distinguishes between ‘academic models’ which are primarily geared towards teaching academic subjects (e.g., Latin, Germanic, and East-Asian countries) and ‘progressive models’ which focus on teaching students’ general competence in diverse contexts (e.g., Anglo-Saxon and Northern countries). In this regard, academic skills refer to the abilities of solving academic-type problems, whereas so called progressive skills are needed in solving real-life problems (Bulle [ 2011 ]). It can be assumed that educational systems that focus on fostering real-life and domain-general competence might be more conducive to successfully tackling the kind of problem solving tasks used in PISA (Kind [ 2013 ]). This classification of educational systems should be seen as the two extreme poles of a continuum rather than as a strict dichotomy. In line with the reflections above, we would argue that academic and progressive skills are not exclusively distinct, since both skills utilise sets of cognitive processes that largely overlap (Klahr and Dunbar [ 1988 ]). The fact that curricular objectives in some countries are shifting (e.g., in Eastern Asia) makes a clear distinction between both models even more difficult. Nonetheless, we will use this form of country-specific categorization based on Bulle’s model in our analyses.

Second, we considered whether countries’ science curricula were ‘integrated’ or ‘not integrated’ (Martin et al. [ 2004 ]). In this context, integration refers to linking multiple science subjects (biology, chemistry, earth science, and physics) to a unifying theme or issue (cf. Drake and Reid [ 2010 ], p. 1).

In terms of school-related factors, we used the PISA 2003 scales of ‘Frequency of assessments in schools’, ‘Schools’ educational resources’, and ‘School autonomy towards resources and curricula’ from the school questionnaire. Based on frequency and rating scales, weighted maximum likelihood estimates (WLE) indicated the degree to which schools performed in these scales (OECD [ 2005 ]).

The country-specific characteristics are summarized in the Table 1 .

The PISA 2003 assessments utilised a randomized incomplete block design to select different test booklets which covered the different content areas of math, science, and problem solving (Brunner et al. [ 2013 ]; OECD [ 2005 ]). The test administration took 120 minutes, and was managed for each participating country separately. It was established that quality standards of the assessment procedure were high.

Statistical analyses

In PISA 2003, different methods of obtaining person estimates with precise standard errors were applied. The most accurate procedure produced five plausible values, which were drawn from a person ability distribution (OECD [ 2005 ]). To avoid missing values in these parameters and to obtain accurate estimates, further background variables were used within the algorithms (Wu [ 2005 ]). The resulting plausible values were subsequently used as indicators of students’ competence in math, science, and problem solving. By applying Rubin’s combination rules (Bouhilila and Sellaouti [ 2013 ]; Enders [ 2010 ]), analyses were replicated with each of the five plausible values and then combined. In this multiple imputation procedure, standard errors were decomposed to the variability across and within the five imputations (Enders [ 2010 ]; OECD [ 2005 ]; Wu [ 2005 ]).

Within the multilevel regression analyses for each country, we specified the student level as level 1 and the school level as level 2. Since PISA 2003 applied a random sampling procedure at the student and the school level, we decided to control for the clustering of data at these two levels (OECD [ 2005 ]). In addition to this two-level procedure, we regarded the 41 countries as multiple groups (fixed effects). This decision was based on our assumption that the countries selected in PISA 2003 did not necessarily represent a sample of a larger population (Martin et al. [ 2012 ]). Moreover, we did not regard the effects of countries as interchangeable, because, given the specific characteristics of education and instruction within countries; we argue that the effects of competences in mathematics and science on problem solving have their own distinct interpretation in each country (Snijders and Bosker [ 2012 ]). The resulting models were compared by taking into account the Akaike’s information criteria ( AIC ), Bayesian information criteria ( BIC ), and the sample-size adjusted BIC . Also, a likelihood ratio test of the log-Likelihood values ( LogL ) was applied (Hox [ 2010 ]).

To test the Moderation-Hypothesis, we first specified a two-level regression model with problem solving scores as outcomes at the student level (level 1), which allowed variance in achievement scores across schools (level 2). In this model, math and science scores predicted problem solving scores at the student level. To account for differences in the probabilities of being selected as a student within the 41 countries and to adjust the standard errors of regression parameters, we used the robust maximum likelihood (MLR) estimator and students’ final weights (see also Brunner et al. [ 2013 ]; OECD [ 2005 ]). All analyses were conducted in Mplus 6.0 by using the TYPE = IMPUTATION option (Muthén and Muthén [ 2010 ]). As Hox ([ 2010 ]) suggested, using multilevel regression models without taking into account the clustering of data in schools often leads to biased estimates, since achievement variables often have substantial variance at the school level. Consequently, we allowed for level-2-variance within the scores.

After having established whether success in math and science education contributes to the development in problem solving competence across the 41 countries, we then tested whether cross-country differences in the unstandardized regression coefficients were statistically significant by using a multi-group regression model, in which the coefficients were constrained to be equal across countries. We compared this model with the freely estimated model.

Finally, we conceptualized the correlation between math and science scores as an indicator of the level of coherence in math and science education in a country. In relation to the Confounding-Hypothesis, we tested country-specific characteristics for their potentially confounding effects on the relation between math-science coherence and problem solving competence. Following the recommendations proposed by (MacKinnon et al. [ 2000 ]), the confounding analysis was conducted in two steps: (1) we estimated two regression equations. In the first equation, problem solving scores across the 41 countries were regressed on math-science coherence. In the second equation, the respective country characteristics were added as further predictors; (2) the difference between the regression coefficients for math-science coherence obtained in either equation represented the magnitude of a potential confounder effect.

Lastly, we tested the Capability-Utilisation Hypothesis by investigating the bivariate correlations among the CUU Indices and math-science coherence.

Regressing problem solving on math and science performance

To test the Moderation-Hypothesis, we specified regression models with students’ problem-solving score as the outcome and math and science scores as predictors for each of the 41 countries. Due to the clustering of data in schools, these models allowed for between-level variance. Intraclass correlations (ICC-1) for math, science, and problem solving performance ranged between .03 and .61 for the school level ( M  = .33, SD  = .16).

We specified multilevel regression models for each country separately. These results are reported in Table  2 . The regression coefficients for math on problem solving ranged from .53 to .82 with an average of M( β Math )  = .67 ( SD  = .06). The average contribution of science towards problem solving was M( β Science )  = .16 ( SD  = .09, Min  = -.06, Max  = .30). The combination of the distributions of both parameters resulted in substantial differences in the variance explanations of the problem solving scores across the 41 countries ( M[R 2 ]  = .65, SD  = .15, Min  = .27, Max  = .86). To test whether these differences were statistically significant, we constrained the regression coefficients of math and science competence within the multi-group regression model to be equal across the 41 countries. Compared to the freely estimated model ( LogL  = -4,561,273.3, df  = 492, AIC  = 9,123,530.5, BIC  = 9,128,410.7), the restricted model was empirically not preferred LogL  = -4,564,877.9, df  = 412, AIC  = 9,130,579.8, BIC  = 9,134,917.6; Δχ 2 [80] = 7,209.2, p  < .001. These findings lend evidence for the Moderation-Hypothesis.

From a slightly different perspective, the country-specific amount of variance in problem solving scores that is explained by the variation in math and science performance scores ( R 2 ) is strongly associated with the country’s problem solving score ( r  = .77, p  < .001), which suggests that the contribution of science and math competence to the acquisition of problem solving competence was significantly lower in low-performing countries.

As shown in Table  2 , the regression weights of math and science were significant for all but two countries. Across countries the regression weight for math tended to be higher than the regression weight for science when predicting problem solving competence. This finding indicates a stronger overlap between students’ competences in mathematics and problem solving on the one hand and similarities between the assessments in both domains on the other hand.

Validating the concept of math-science coherence

In order to validate the concept of math-science coherence, which is operationalised as the correlation between math and science scores [ r (M,S)], we explored its relation to problem solving and country characteristics.

Regarding the regression outcomes shown in Table  2 , it is apparent that math-science coherence varied considerably across countries, ranging from .39 to .88 with an average of M(r)  = .70 ( SD  = .13). Interestingly, countries’ level of coherence in math-science education was substantially related to their problem solving scores ( r  = .76, p  < .001). An inspection of Figure  1 reveals that this effect was mainly due to countries that both achieve low problem solving scores and show relatively low levels of math-science coherence (see bottom left quadrant in Figure  1 ), whilst amongst the remaining countries the correlational link between math-science coherence and problem solving score was almost zero ( r  = -.08, p  = .71) b . This pattern extends the moderation perspective on the presumed dependency of problem solving competence from math and science competences.

The relation between math-science coherence and problem solving performance across the 41 countries.

As a result of the moderator analysis, we know that countries not only differ in regard to their average problem-solving scores and level of coherence between math and science, countries also differ in the strengths with which math-science coherence predicts problem solving scores. To better understand the conceptual nature of the link between math-science coherence and problem solving, we now attempt to adjust this relationship for potential confounding effects that country-specific characteristics might have. To this end, we employed linear regression and path analysis with students’ problem-solving scores as outcomes, math-science coherence (i.e., r [M,S]) as predictor, and country characteristics as potential confounders.

To establish whether any of the country characteristics had a confounding effect on the link between math-science coherence and problem solving competence, two criteria had to be met: (1) a reduction of the direct effect of math-science coherence on problem solving scores, and (2) testing the difference between the direct effect within the baseline Model M0 and the effect with the confounding Model M1 (Table  3 ).

Regarding the society-related factors, both the countries’ HDI and their national intelligence were confounders with a positive effect. Furthermore, the countries’ integration of the science curriculum was also positively related to the problem solving performance. Finally, the degree of schools’ autonomy towards educational resources and the implementation of curricula and the frequency of assessments were school-related confounders, the former with a positive effect whilst the latter represents a negative confounder. The direct effect of math-science coherence to problem solving decreased and thus indicated that confounding was present (MacKinnon et al. [ 2000 ]).

These findings provide evidence on the Confounding-Hypothesis and support our expectations on the relation between math-science coherence, problem solving, and country characteristics. We regard these results as evidence for the validity of the math-science coherence measure.

Relating math-science coherence to the capability under-utilisation indices

To advance our understanding of the link between math-science coherence and problem solving scores, we tested the Capability-Utilisation Hypothesis. To this end, we explored the relationship between math-science coherence and the CUU Indices for math and science, respectively. For math competence the average Capability Under-Utilisation Index was rather neutral with M CUUI-Math  = -0.001 ( SD  = 0.02). This suggests that, on average, all countries sufficiently utilise their students’ math capabilities in facilitating the development of problem solving competence (i.e., transfer). It also suggests that math education across participating countries tends to sufficiently utilise generic problem-solving skills (Figure  2 ). The picture is different for science education. Here, the Capability Under-Utilisation Indices and their variation across the participating countries ( M CUUI-Science  = -0.01, SD  = 0.04) suggest that in a range of countries knowledge and skills taught in science education tend to be under-utilised in the facilitation of the acquisition of problem solving competence (Figure  3 ).

The relation between math-science coherence and the capability under-utilisation index for math and problem solving scores across the 41 countries.

The relation between math-science coherence and the capability under-utilisation index for science and problem solving scores across the 41 countries.

For math competence, the relative difference to problem solving was not related to math-science coherence ( r  = .02, p  = .89; Figure  2 ). In contrast, the Capability Under-Utilisation Index for science showed a strong positive correlation with math-science coherence ( r  = .76, p  < .001; Figure  3 ), indicating that low levels of coherence between math and science education were associated with a less effective transfer of domain-specific knowledge and skills to problem solving.

The present study was aimed at investigating the differences in the contribution of math and science competence to problem solving competence across the 41 countries that participated in the PISA 2003 study (Moderation-Hypothesis). To this end, we proposed the concept of math-science coherence and explored its relationship to problem solving competence and how this relationship is confounded by country characteristics (Confounding-Hypothesis). To further extend our understanding of the link between math-science coherence and problem solving, we introduced the concept of capability-utilisation. Testing the Capability-Utilisation Hypothesis enabled us to identify what may contribute to varying levels of math-science coherence and ultimately the development of problem solving competence.

The contribution of math and science competence across countries

Regarding the prediction of problem solving competence, we found that in most countries, math and science competence significantly contributed to students’ performance in analytical problem solving. This finding was expected based on the conceptualizations of mathematical and scientific literacy within the PISA framework referring to shared cognitive processes such as information processing and reasoning (Kind [ 2013 ]; OECD [ 2005 ]), which are regarded as components of problem solving (Bybee [ 2004 ]; Klahr and Dunbar [ 1988 ]; Mayer [ 2010 ]).

It is noteworthy that, for some of the below-average performing countries, science competence did not significantly contribute to the prediction of problem solving competence. It can be speculated that education in these countries is more geared towards math education and modelling processes in mathematical scenarios, whilst the aspect of problem solving in science is less emphasised (Janssen and Geiser [ 2012 ]). The results of multilevel regression analyses supported this interpretation by showing that math competence was a stronger predictor of problem solving competence. On the one hand, this finding could be due to the design of the PISA tests (Adams [ 2005 ]), since math and problem solving items are designed in such a way that modelling real-life problems is required, whereas science items are mostly domain-specific and linked to science knowledge (Nentwig et al. [ 2009 ]; OECD [ 2004 ]). Moreover, one may argue that math and problem solving items allow students to employ different solution strategies, whereas science items offer fewer degrees of freedom for test takers (Nentwig et al. [ 2009 ]). In particular, the shared format of items in math, science, and problem solving may explain an overlap between their cognitive demands. For instance, most of the items were designed in such a way that students had to extract and identify relevant information from given tables or figures in order to solve specific problems. Hence, these items were static and did not require knowledge generation by interaction or exploration but rather the use of given information in problem situations (Wood et al. [ 2009 ]). In contrast to the domain-specific items in math and science, problem solving items did not require the use of prior knowledge in math and science (OECD [ 2004 ]). In addition, some of the math and science items involved cognitive operations that were specific to these domains. For instance, students had to solve a number of math items by applying arithmetic and combinatorial operations (OECD [ 2005 ]). Finally, since items referred to contextual stimuli, which were presented in textual formats, reading ability can be regarded as another, shared demand of solving the items. Furthermore, Rindermann ([ 2007 ]) clearly showed that the shared demands of the achievement tests in large-scale assessments such as PISA were strongly related to students’ general reasoning skills. This finding is in line with the strong relations between math, science, and problem solving competence, found in our study. The interpretation of the overlap between the three competences can also be interpreted from a conceptual point of view. In light of the competence frameworks in PISA, we argue that there are a number of skills that can be found in math, science, and problem solving: information retrieval and processing, knowledge application, and evaluation of results (Griffin et al. [ 2012 ]; OECD [ 2004 ], [ 2005 ]). These skills point out to the importance of reasoning in the three domains (Rindermann [ 2007 ]). Thus, the empirical overlap between math and problem solving can be explained by shared processes of, what Mayer ([ 2010 ]) refers to as, informal reasoning. On the other hand, the stronger effect of math competence could be an effect of the quality of math education. Hiebert et al. ([ 1996 ]) and Kuo et al. ([ 2013 ]) suggested that math education is more based on problem solving skills than other subjects in school (e.g., Polya [ 1945 ]). Science lessons, in contrast, are often not necessarily problem-based, despite the fact that they often start with a set problem. Risch ([ 2010 ]) showed in a cross-national review that science learning was more related to contents and contexts rather than to generic problem-solving skills. These tendencies might lead to a weaker contribution of science education to the development of problem solving competence (Abd-El-Khalick et al. [ 2004 ]).

In sum, we found support on the Moderation-Hypothesis, which assumed systematic differences in the contribution of math and science competence to problem solving competence across the 41 PISA 2003 countries.

The relation to problem solving

In our study, we introduced the concept of math-science coherence, which reflects the degree to which math and science education are harmonized. Since mathematical and scientific literacy show a conceptual overlap, which refers to a set of cognitive processes that are linked to reasoning and information processing (Fensham and Bellocchi [ 2013 ]; Mayer [ 2010 ]), a significant relation between math-science coherence and problem solving was expected. In our analyses, we found a significant and positive effect of math-science coherence on performance scores in problem solving. In this finding we see evidence for the validity of this newly introduced concept of math-science coherence and its focus on the synergistic effect of math and science education on problem solving. The results further suggest that higher levels of coordination between math and science education has beneficial effects on the development of cross-curricular problem-solving competence (as measured within the PISA framework).

Confounding effects of country characteristics

As another step of validating the concept of math-science coherence, we investigated whether country-specific characteristics that are linked to society-, curriculum-, and school-related factors confounded its relation to problem solving. Our results showed that national intelligence, the Human Development Index, the integration of the science curriculum, and schools’ autonomy were positively linked to math-science coherence and problem solving, whilst a schools’ frequency of assessment had a negative confounding effect.

The findings regarding the positive confounders are in line with and also extend a number of studies on cross-country differences in education (e.g., Blömeke et al. [ 2011 ]; Dronkers et al. [ 2014 ]; Janssen and Geiser [ 2012 ]; Risch [ 2010 ]). Ross and Hogaboam-Gray ([ 1998 ]), for instance, found that students benefit from an integrated curriculum, particularly in terms of motivation and the development of their abilities. In the context of our confounder analysis, the integration of the science curriculum as well as the autonomy to allocate resources is expected to positively affect math-science coherence. At the same time, an integrated science curriculum with a coordinated allocation of resources may promote inquiry-based experiments in science courses, which is assumed to be beneficial for the development of problem solving within and across domains. Teaching science as an integrated subject is often regarded a challenge for teachers, particularly when developing conceptual structures in science lessons (Lang and Olson, [ 2000 ]), leading to teaching practices in which cross-curricular competence is rarely taken into account (Mansour [ 2013 ]; van Merriënboer [ 2013 ]).

The negative confounding effect of assessment frequency suggests that high frequencies of assessment, as it presumably applies to both math and science subjects, contribute positively to math-science coherence. However, the intended or unintended engagement in educational activities associated with assessment preparation tends not to be conducive to effectively developing domain-general problem solving competence (see also Neumann et al. [ 2012 ]).

The positive confounder effect of HDI is not surprising as HDI reflects a country’s capability to distribute resources and to enable certain levels of autonomy (Reich et al. [ 2013 ]). To find national intelligence as a positive confounder is also to be expected as the basis for its estimation are often students’ educational outcome measures (e.g., Rindermann [ 2008 ]) and, as discussed earlier, academic achievement measures share the involvement of a set of cognitive processes (Baumert et al. [ 2009 ]; OECD [ 2004 ]).

In summary, the synergistic effect of a coherent math and science education on the development of problem solving competence is substantially linked to characteristics of a country’s educational system with respect to curricula and school organization in the context of its socio-economic capabilities. Math-science coherence, however, also is linked to the extent to which math or science education is able to utilise students’ educational capabilities.

Math-science coherence and capability-utilisation

So far, discrepancies between students’ performance in math and problem solving or science and problem solving have been discussed as indicators of students’ capability utilisation in math or science (Leutner et al. [ 2012 ]; OECD [ 2004 ]). We have extended this perspective by introducing Capability Under-Utilisation Indices for math and science to investigate the effectiveness with which knowledge and skills acquired in the context of math or science education are transferred into cross-curricular problem-solving competence. The Capability Under-Utilisation Indices for math and science reflect a potential quantitative imbalance between math, science, and problem solving performance within a country, whilst the also introduced concept of math-science coherence reflects a potential qualitative imbalance between math and science education.

The results of our analyses suggest that an under-utilisation of problem solving capabilities in the acquisition of science literacy is linked to lower levels of math-science coherence, which ultimately leads to lower scores in problem solving competence. This interpretation finds resonance in Ross and Hogaboam-Gray’s ([ 1998 ]) argumentation for integrating math and science education and supports the attempts of math and science educators to incorporate higher-order thinking skills in teaching STEM subjects (e.g., Gallagher et al. [ 2012 ]; Zohar [ 2013 ]).

In contrast, the CUU Index for math was not related to math-science coherence in our analyses. This might be due to the conceptualizations and assessments of mathematical literacy and problem solving competence. Both constructs share cognitive processes of reasoning and information processing, resulting in quite similar items. Consequently, the transfer from math-related knowledge and skills to cross-curricular problems does not necessarily depend on how math and science education are harmonised, since the conceptual and operational discrepancy between math and problem solving is rather small.

Math and science education do matter to the development of students’ problem-solving skills. This argumentation is based on the assumption that the PISA assessments in math, science, and problem solving are able to measure students’ competence as outcomes, which are directly linked to their education (Bulle [ 2011 ]; Kind [ 2013 ]). In contrast to math and science competence, problem solving competence is not explicitly taught as a subject. Problem solving competence requires the utilisation of knowledge and reasoning skills acquired in specific domains (Pellegrino and Hilton [ 2012 ]). In agreement with Kuhn ([ 2009 ]), we point out that this transfer does not happen automatically but needs to be actively facilitated. In fact, Mayer and Wittrock ([ 2006 ]) stressed that the development of transferable skills such as problem solving competence needs to be fostered within specific domains rather than taught in dedicated, distinct courses. Moreover, they suggested that students should develop a “repertoire of cognitive and metacognitive strategies that can be applied in specific problem-solving situations” (p. 299). Beyond this domain-specific teaching principle, research also proposes to train the transfer of problem solving competence in domains that are closely related (e.g., math and science; Pellegrino and Hilton [ 2012 ]). In light of the effects of aligned curricula (as represented by the concept of math-science coherence), we argue that educational efforts to increase students’ problem solving competence may focus on a coordinated improvement of math and science literacy and fostering problem solving competence within math and science. The emphasis is on coordinated, as the results of our analyses indicated that the coherence between math and science education, as a qualitative characteristic of a country’s educational system, is a strong predictor of problem solving competence. This harmonisation of math and science education may be achieved by better enabling the utilisation of capabilities, especially in science education. Sufficiently high levels of math-science coherence could facilitate the emergence of educational synergisms, which positively affect the development of problem solving competence. In other words, we argue for quantitative changes (i.e., improve science attainment) in order to achieve qualitative changes (i.e., higher levels of curriculum coherence), which are expected to create effective transitions of subject-specific knowledge and skills into subject-unspecific competences to solve real-life problems (Pellegrino and Hilton [ 2012 ]; van Merriënboer [ 2013 ]).

Finally, we encourage research that is concerned with the validation of the proposed indices for different forms of problem solving. In particular, we suggest studying the facilities of the capability-under-utilisation indices for analytical and dynamic problem solving, as assessed in the PISA 2012 study (OECD [ 2014 ]). Due to the different cognitive demands in analytical and dynamic problems (e.g., using existing knowledge vs. generating knowledge; OECD [ 2014 ]), we suspect differences in capability utilisation in math and science. This research could provide further insights into the role of 21 st century skills as educational goals.

a The differences between students’ achievement in mathematics and problem solving, and science and problem solving have to be interpreted relative to the OECD average, since the achievement scales were scaled with a mean of 500 and a standard deviation of 100 for the OECD countries (OECD [ 2004 ], p. 55). Although alternative indices such as country residuals may also be used in cross-country comparisons (e.g., Olsen [ 2005 ]), we decided to use CUU indices, as they reflect the actual differences in achievement scores.

b In addition, we checked whether this result was due to the restricted variances in low-performing countries and found that neither ceiling nor floor effects in the problem solving scores existed. The problem solving scale differentiated sufficiently reliably in the regions below and above the OECD mean of 500.

Abd-El-Khalick F, Boujaoude S, Duschl R, Lederman NG, Mamlok-Naaman R, Hofstein A, Niaz M, Treagust D, Tuan H-L: Inquiry in science education: International perspectives. Science Education 2004, 88: 397–419. doi:10.1002/sce.10118 10.1002/sce.10118

Article   Google Scholar  

Adams RJ: Reliability as a measurement design effect. Studies in Educational Evaluation 2005, 31: 162–172. doi:10.1016/j.stueduc.2005.05.008 10.1016/j.stueduc.2005.05.008

Arts J, Gijselaers W, Boshuizen H: Understanding managerial problem solving, knowledge use and information processing: Investigating stages from school to the workplace. Contemporary Educational Psychology 2006, 31: 387–410. doi:10.1016/j.cedpsych.2006.05.005 10.1016/j.cedpsych.2006.05.005

Bassok M, Holyoak K: Pragmatic knowledge and conceptual structure: determinants of transfer between quantitative domains. In Transfer on trial: intelligence, cognition, and instruction . Edited by: Detterman DK, Sternberg RJ. Ablex, Norwood, NJ; 1993:68–98.

Google Scholar  

Baumert J, Lüdtke O, Trautwein U, Brunner M: Large-scale student assessment studies measure the results of processes of knowledge acquisition: evidence in support of the distinction between intelligence and student achievement. Educational Research Review 2009, 4: 165–176. doi:10.1016/j.edurev.2009.04.002 10.1016/j.edurev.2009.04.002

Beckmann JF: Zur Validierung des Konstrukts des intellektuellen Veränderungspotentials [On the validation of the construct of intellectual change potential] . logos, Berlin; 2001.

Blömeke S, Houang R, Suhl U: TEDS-M: diagnosing teacher knowledge by applying multidimensional item response theory and multiple-group models. IERI Monograph Series: Issues and Methodologies in Large-Scale Assessments 2011, 4: 109–129.

Bouhilila D, Sellaouti F: Multiple imputation using chained equations for missing data in TIMSS: a case study. Large-scale Assessments in Education 2013, 1: 4.

Brunner M, Gogol K, Sonnleitner P, Keller U, Krauss S, Preckel F: Gender differences in the mean level, variability, and profile shape of student achievement: Results from 41 countries. Intelligence 2013, 41: 378–395. doi:10.1016/j.intell.2013.05.009 10.1016/j.intell.2013.05.009

Bulle N: Comparing OECD educational models through the prism of PISA. Comparative Education 2011, 47: 503–521. doi: 10.1080/03050068.2011.555117 10.1080/03050068.2011.555117

Bybee R: Scientific Inquiry and Science Teaching. In Scientific Inquiry and the Nature of Science . Edited by: Flick L, Lederman N. Springer & Kluwers, New York, NY; 2004:1–14. doi:10.1007/978–1-4020–5814–1_1

Chiu M, Chow B: Classroom discipline across forty-One countries: school, economic, and cultural differences. Journal of Cross-Cultural Psychology 2011, 42: 516–533. doi:10.1177/0022022110381115 10.1177/0022022110381115

Drake S, Reid J: Integrated curriculum: Increasing relevance while maintaining accountability. Research into Practice 2010, 28: 1–4.

Dronkers J, Levels M, de Heus M: Migrant pupils’ scientific performance: the influence of educational system features of origin and destination countries. Large-scale Assessments in Education 2014, 2: 3.

Enders C: Applied Missing Data Analysis . The Guilford Press, New York, NY; 2010.

Ewell P: A world of assessment: OECD’s AHELO initiative. Change: The Magazine of Higher Learning 2012, 44: 35–42. doi:10.1080/00091383.2012.706515 10.1080/00091383.2012.706515

Fensham P, Bellocchi A: Higher order thinking in chemistry curriculum and its assessment. Thinking Skills and Creativity 2013, 10: 250–264. doi:10.1016/j.tsc.2013.06.003 10.1016/j.tsc.2013.06.003

Gallagher C, Hipkins R, Zohar A: Positioning thinking within national curriculum and assessment systems: perspectives from Israel, New Zealand and Northern Ireland. Thinking Skills and Creativity 2012, 7: 134–143. doi:10.1016/j.tsc.2012.04.005 10.1016/j.tsc.2012.04.005

Greiff S, Holt D, Funke J: Perspectives on problem solving in educational assessment: analytical, interactive, and collaborative problem solving. The Journal of Problem Solving 2013, 5: 71–91. doi:10.7771/1932–6246.1153 10.7771/1932-6246.1153

Griffin P, Care E, McGaw B: The changing role of education and schools. In Assessment and Teaching of 21st Century Skills . Edited by: Griffin P, McGaw B, Care E. Springer, Dordrecht; 2012:1–15. 10.1007/978-94-007-2324-5_1

Chapter   Google Scholar  

Hickendorff M: The language factor in elementary mathematics assessments: Computational skills and applied problem solving in a multidimensional IRT framework. Applied Measurement in Education 2013, 26: 253–278. doi:10.1080/08957347.2013.824451 10.1080/08957347.2013.824451

Hiebert J, Carpenter T, Fennema E, Fuson K, Human P, Murray H, Olivier A, Wearne D: Problem Solving as a Basis for Reform in Curriculum and Instruction: The Case of Mathematics. Educational Researcher 1996, 25: 12–21. doi:10.3102/0013189X025004012 10.3102/0013189X025004012

Holliday W, Holliday B: Why using international comparative math and science achievement data from TIMSS is not helpful. The Educational Forum 2003, 67: 250–257. 10.1080/00131720309335038

Hox J: Multilevel Analysis . 2nd edition. Routlegde, New York, NY; 2010.

Janssen A, Geiser C: Cross-cultural differences in spatial abilities and solution strategies: An investigation in Cambodia and Germany. Journal of Cross-Cultural Psychology 2012, 43: 533–557. doi:10.1177/0022022111399646 10.1177/0022022111399646

Jonassen D: Learning to solve problems . Routledge, New York, NY; 2011.

Kind P: Establishing Assessment Scales Using a Novel Disciplinary Rationale for Scientific Reasoning. Journal of Research in Science Teaching 2013, 50: 530–560. doi:10.1002/tea.21086 10.1002/tea.21086

Klahr D, Dunbar K: Dual Space Search during Scientific Reasoning. Cognitive Science 1988, 12: 1–48. doi:10.1207/s15516709cog1201_1 10.1207/s15516709cog1201_1

Koeppen K, Hartig J, Klieme E, Leutner D: Current issues in competence modeling and assessment. Journal of Psychology 2008, 216: 61–73. doi:10.1027/0044–3409.216.2.61

Kuhn D: Do students need to be taught how to reason? Educational Research Review 2009, 4: 1–6. doi:10.1016/j.edurev.2008.11.001 10.1016/j.edurev.2008.11.001

Kuo E, Hull M, Gupta A, Elby A: How Students Blend Conceptual and Formal Mathematical Reasoning in Solving Physics Problems. Science Education 2013, 97: 32–57. doi:10.1002/sce.21043 10.1002/sce.21043

Lang M, Olson J: Integrated science teaching as a challenge for teachers to develop new conceptual structures. Research in Science Education 2000, 30: 213–224. doi:10.1007/BF02461629 10.1007/BF02461629

Leutner D, Fleischer J, Wirth J, Greiff S, Funke J: Analytische und dynamische Problemlösekompetenz im Lichte internationaler Schulleistungsstudien [Analytical and dynamic problem-solvng competence in international large-scale studies]. Psychologische Rundschau 2012, 63: 34–42. doi:10.1026/0033–3042/a000108 10.1026/0033-3042/a000108

Lynn R, Meisenberg G: National IQs calculated and validated for 108 nations. Intelligence 2010, 38: 353–360. doi:10.1016/j.intell.2010.04.007 10.1016/j.intell.2010.04.007

MacKinnon D, Krull J, Lockwood C: Equivalence of the mediation, confounding, and suppression effect. Prevention Science 2000, 1: 173–181. doi:10.1023/A:1026595011371 10.1023/A:1026595011371

Mansour N: Consistencies and inconsistencies between science teachers’ beliefs and practices. International Journal of Science Education 2013, 35: 1230–1275. doi:10.1080/09500693.2012.743196 10.1080/09500693.2012.743196

Martin M, Mullis I, Gonzalez E, Chrostowski S: TIMSS 2003 International Science Report . IEA, Chestnut Hill, MA; 2004.

Martin AJ, Liem GAD, Mok MMC, Xu J: Problem solving and immigrant student mathematics and science achievement: Multination findings from the Programme for International Student Assessment (PISA). Journal of Educational Psychology 2012, 104: 1054–1073. doi:10.1037/a0029152 10.1037/a0029152

Mayer R: Problem solving and reasoning. In International Encyclopedia of Education . 3rd edition. Edited by: Peterson P, Baker E, McGraw B. Elsevier, Oxford; 2010:273–278. doi:10.1016/B978–0-08–044894–7.00487–5 10.1016/B978-0-08-044894-7.00487-5

Mayer R, Wittrock MC: Problem solving. In Handbook of Educational Psychology . 2nd edition. Edited by: Alexander PA, Winne PH. Lawrence Erlbaum, New Jersey; 2006:287–303.

Muthén B, Muthén L: Mplus 6 . Muthén & Muthén, Los Angeles, CA; 2010.

Successful K-12 STEM Education . National Academies Press, Washington, DC; 2011.

Nentwig P, Rönnebeck S, Schöps K, Rumann S, Carstensen C: Performance and levels of contextualization in a selection of OECD countries in PISA 2006. Journal of Research in Science Teaching 2009, 8: 897–908. doi:10.1002/tea.20338 10.1002/tea.20338

Neumann K, Kauertz A, Fischer H: Quality of Instruction in Science Education. In Second International Handbook of Science Education (Part One . Edited by: Fraser B, Tobin K, McRobbie C. Springer, Dordrecht; 2012:247–258.

The PISA 2003 Assessment Frameworks . OECD, Paris; 2003.

Problem solving for tomorrow’s world . OECD, Paris; 2004.

PISA 2003 Technical Report . OECD, Paris; 2005.

PISA 2012 Results : Creative Problem Solving – Students’ Skills in Tackling Real-Life Problems (Vol. V) . OECD, Paris; 2014.

Olsen RV: An exploration of cluster structure in scientific literacy in PISA: Evidence for a Nordic dimension? NorDiNa. ᅟ 2005, 1 (1):81–94.

Oser F, Baeriswyl F: Choreographies of Teaching: Bridging Instruction to Learning. In Handbook of Research on Teaching . 4th edition. Edited by: Richardson V. American Educational Research Association, Washington, DC; 2001:1031–1065.

Pellegrino JW, Hilton ML: Education for Life and Work – Developing Transferable Knowledge and Skills in the 21st Century . The National Academies Press, Washington, DC; 2012.

Polya G: How to solve it: a new aspect of mathematical method . Princeton University Press, Princeton, NJ; 1945.

Reich J, Hein S, Krivulskaya S, Hart L, Gumkowski N, Grigorenko E: Associations between household responsibilities and academic competencies in the context of education accessibility in Zambia. Learning and Individual Differences 2013, 27: 250–257. doi:10.1016/j.lindif.2013.02.005 10.1016/j.lindif.2013.02.005

Rindermann H: The g-factor of international cognitive ability comparisons: The homogeneity of results in PISA, TIMSS, PIRLS and IQ-tests across nations. European Journal of Personality 2007, 21: 661–706. doi:10.1002/per.634

Rindermann H: Relevance of education and intelligence at the national level for the economic welfare of people. Intelligence 2008, 36: 127–142. doi:10.1016/j.intell.2007.02.002 10.1016/j.intell.2007.02.002

Risch B: Teaching Chemistry around the World . Waxmann, Münster; 2010.

Ross J, Hogaboam-Gray A: Integrating mathematics, science, and technology: effects on students. International Journal of Science Education 1998, 20: 1119–1135. doi:10.1080/0950069980200908 10.1080/0950069980200908

Snijders TAB, Bosker RJ: Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling . 2nd edition. Sage Publications, London; 2012.

Human Development Report 2005 . UNDP, New York, NY; 2005.

Van Merriënboer J: Perspectives on problem solving and instruction. Computers & Education 2013, 64: 153–160. doi:10.1016/j.compedu.2012.11.025 10.1016/j.compedu.2012.11.025

Wood RE, Beckmann JF, Birney D: Simulations, learning and real world capabilities. Education Training 2009, 51 (5/6):491–510. doi:10.1108/00400910910987273 10.1108/00400910910987273

Wu M: The role of plausible values in large-scale surveys. Studies in Educational Evaluation 2005, 31: 114–128. doi:10.1016/j.stueduc.2005.05.005 10.1016/j.stueduc.2005.05.005

Wu M, Adams R: Modelling Mathematics Problem Solving Item Responses using a Multidimensional IRT Model. Mathematics Education Research Journal 2006, 18: 93–113. doi:10.1007/BF03217438 10.1007/BF03217438

Wüstenberg S, Greiff S, Funke J: Complex problem solving: More than reasoning? Intelligence 2012, 40: 1–14. doi:10.1016/j.intell.2011.11.003 10.1016/j.intell.2011.11.003

Zohar A: Scaling up higher order thinking in science classrooms: the challenge of bridging the gap between theory, policy and practice. Thinking Skills and Creativity 2013, 10: 168–172. doi:10.1016/j.tsc.2013.08.001 10.1016/j.tsc.2013.08.001

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Scherer, R., Beckmann, J.F. The acquisition of problem solving competence: evidence from 41 countries that math and science education matters. Large-scale Assess Educ 2 , 10 (2014). https://doi.org/10.1186/s40536-014-0010-7

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Competencies for Complexity: Problem Solving in the Twenty-First Century

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• Daniel V. Holt 6  

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In this chapter, we present a view of problem solving as a bundle of skills, knowledge and abilities that are required to deal effectively with complex non-routine situations in different domains. This includes cognitive aspects of problem solving, such as causal reasoning, model building, rule induction, and information integration. These abilities are comparatively well covered by existing tests and relate to existing theories. However, non-cognitive components, such as motivation, self-regulation and social skills, which are clearly important for real-life problem solving have only just begun to be covered in assessment. We conclude that currently there is no single assessment instrument that captures problem solving competency in a comprehensive way and that a number of challenges must be overcome to cover a construct of this breadth effectively. Research on some important components of problem solving is still underdeveloped and will need to be expanded before we can claim a thorough, scientifically backed understanding of real-world problem solving. We suggest that a focus on handling and acting within complex systems (systems competency) may be a suitable starting point for such an integrative approach.

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Alison, L., van den Heuvel, C., Waring, S., Power, N., Long, A., O’Hara, T., & Crego, J. (2013). Immersive simulated learning environments for researching critical incidents: A knowledge synthesis of the literature and experiences of studying high-risk strategic decision making. Journal of Cognitive Engineering and Decision Making, 7 (3), 255–272. doi: 10.1177/1555343412468113 .

Article   Google Scholar  

Barth, C. M., & Funke, J. (2010). Negative affective environments improve complex solving performance. Cognition & Emotion, 24 , 1259–1268. doi: 10.1080/02699930903223766 .

Betsch, T., & Haberstroh, S. (Eds.). (2005). The routines of decision making . Mahwah: Erlbaum.

Google Scholar  

Brehmer, B. (1996). Man as a stabiliser of systems: From static snapshots of judgment processes to dynamic decision making. Thinking and Reasoning, 2 , 225–238. doi: 10.1080/135467896394528 .

Brehmer, B. (2005). Micro-worlds and the circular relation between people and their environment. Theoretical Issues in Ergonomics Science, 6(1), 73–93. doi: 10.1080/14639220512331311580 .

Broadbent, D. E., & Aston, B. (1978). Human control of a simulated economic system. Ergonomics, 21 , 1035–1043.

Chang, E. C., D’Zurilla, T. J., & Sanna, L. J. (Eds.). (2004). Social problem solving: Theory, research, and training . Washington, DC: APA.

Csapó, B., & Funke, J. (Eds.). (2017). The nature of problem solving. Using research to inspire 21st centurylearning . Paris: OECD Publishing. doi: 10.1787/9789264273955-en .

Danner, D., Hagemann, D., Holt, D. V., Hager, M., Schankin, A., Wüstenberg, S., & Funke, J. (2011). Measuring performance in a complex problem solving task: Reliability and validity of the tailorshop simulation. Journal of Individual Differences, 32 , 225–233. doi: 10.1027/1614-0001/a000055 .

Dörner, D. (1975). Wie Menschen eine Welt verbessern wollten [How people wanted to improve a world]. Bild der Wissenschaft, 12 , 48–53.

Dörner, D. (1997). The logic of failure. Recognizing and avoiding error in complex situations . New York: Basic Books.

Dörner, D., & Reither, F. (1978). Über das Problemlösen in sehr komplexen Realitätsbereichen [On problem solving in very complex domains of reality]. Zeitschrift für Experimentelle und Angewandte Psychologie, 25 , 527–551.

Dörner, D., & Funke, J. (2017). Complex problem solving: What it is and what it is not. Frontiers in Psychology, 8, 1153. doi: 10.3389/fpsyg.2017.01153 .

Duncker, K. (1935). Zur Psychologie des produktiven Denkens [On the psychology of productive thinking] . Berlin: Julius Springer.

Edwards, W. (1962). Dynamic decision theory and probabilistic information processing. Human Factors, 4 , 59–73.

Fiedler, K. (2001). Affective states trigger processes of assimilation and accomodation. In L. L. Martin & G. L. Clore (Eds.), Theories of mood and cognition: A user’s guidebook (pp. 85–98). Mahwah: Erlbaum.

Fischer, A. (2015). Assessment of problem solving skills by means of multiple complex systems – Validity of finite automata and linear dynamic systems . Dissertation, Heidelberg: Heidelberg University.

Fischer, A., & Neubert, J. C. (2015). The multiple faces of complex problems: A model of problem solving competency and its implications for training and assessment. Journal of Dynamic Decision Making, 1 (6), 1–14. https://doi.org/10.11588/jddm.2015.1.23945 .

Fischer, A., Greiff, S., Wuestenberg, S., Fleischer, J., Buchwald, F., & Funke, J. (2015). Assessing analytic and interactive aspects of problem solving competency. Learning and Individual Differences, 39 , 172–179. doi: 10.1016/j.lindif.2015.02.008 .

Fleck, J. I., & Weisberg, R. W. (2013). Insight versus analysis: Evidence for diverse methods in problem solving. Journal of Cognitive Psychology, 25 , 436–463. doi: 10.1080/20445911.2013.779248 .

Forgas, J. P. (2007). When sad is better than happy: Negative affect can improve the quality and effectiveness of persuasive messages and social influence strategies. Journal of Experimental Social Psychology, 43 , 513–528. doi: 10.1016/j.jesp.2006.05.006 .

Frensch, P. A., & Funke, J. (1995a). Definitions, traditions, and a general framework for understanding complex problem solving. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European perspective (pp. 3–25). Hillsdale: Erlbaum.

Frensch, P. A., & Funke, J. (Eds.). (1995b). Complex problem solving: The european perspective . Hillsdale: Erlbaum.

Funke, J. (2010). Complex problem solving: A case for complex cognition? Cognitive Processing, 11 (2), 133–142. doi: 10.1007/s10339-009-0345-0 .

Funke, J. (2014a). Analysis of minimal complex systems and complex problem solving require different forms of causal cognition. Frontiers in Psychology, 5 , 739. doi: 10.3389/fpsyg.2014.00739 .

Funke, J. (2014b). Problem solving: What are the important questions? In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th annual conference of the cognitive science society (pp. 493–498). Austin: Cognitive Science Society.

Funke, J., Fischer, A., & Holt, D. V. (2017). When less is less: Solving multiple simple problems is not complex problem solving – A comment on Greiff et al. (2015). Journal of Intelligence, 5 (1), 5. doi: 10.3390/jintelligence5010005 .

Greiff, S., & Neubert, J. C. (2014). On the relation of complex problem solving, personality, fluid intelligence, and academic achievement. Learning and Individual Differences, 36 , 37–48. doi: 10.1016/j.lindif.2014.08.003 .

Greiff, S., Fischer, A., Wüstenberg, S., Sonnleitner, P., Brunner, M., & Martin, R. (2013a). A multitrait-multimethod study of assessment instruments for complex problem solving. Intelligence, 41 , 579–596. doi: 10.1016/j.intell.2013.07.012 .

Greiff, S., Holt, D. V., & Funke, J. (2013b). Perspectives on problem solving in educational assessment: Analytical, interactive, and collaborative problem solving. Journal of Problem Solving, 6 , 71–91. doi: 10.7771/1932-6246.1153 .

Greiff, S., Fischer, A., Stadler, M., & Wüstenberg, S. (2015). Assessing complex problem-solving skills with multiple complex systems. Thinking & Reasoning, 21 (3), 356–382. https://doi.org/10.1080/13546783.2014.989263 .

Griffin, P., & Care, E. (2015). The ATC21S method. In P. Griffin & E. Care (Eds.), Assessment and teaching of 21st century skills: Methods and approach (pp. 3–33). Dordrecht: Springer.

Heckman, J. J., & Rubinstein, Y. (2001). The importance of noncognitice skills: Lessons from the GED testing program. American Economic Review, 91 (2), 145–149.

Heppner, P. P. (2008). Expanding the conceptualization and measurement of applied problem solving and coping: From stages to dimensions to the almost forgotten cultural context. American Psychologist, 63 , 803–805. doi: 10.1037/0003-066X.63.8.805 .

Huber, O. (2012). Risky decisions: Active risk management. Current Directions in Psychological Science, 21 (1), 26–30. doi: 10.1177/0963721411422055 .

Isen, A. M., Daubman, K. A., & Nowicki, G. P. (1987). Positive affect facilitates creative problem solving. Journal of Personality and Social Psychology, 52 , 1122–1131.

Klein, G. (2008). Naturalistic decision making. Human Factors, 50 , 456–460. doi: 10.1518/001872008X288385 .

Kriz, W. C. (2003). Creating effective learning environments and learning organizations through gaming simulation design. Simulation & Gaming, 34 (4), 495–511. doi: 10.1177/1046878103258201 .

Kriz, W. C. (2008). A systemic-constructivist approach to the facilitation and debriefing of simulations and games. Simulation & Gaming, 41 , 663–680. doi: 10.1177/1046878108319867 .

Leutner, D., Fleischer, J., Wirth, J., Greiff, S., & Funke, J. (2012). Analytische und dynamische Problemlösekompetenz im Lichte internationaler Schulleistungsvergleichsstudien: Untersuchungen zur Dimensionalität [Analytical and dynamic problem-solving competence from an international educational studies perspective. Analysis of dimensionality]. Psychologische Rundschau, 63 , 34–42. doi: 10.1026/0033-3042/a000108 .

MacKinnon, A. J., & Wearing, A. J. (1980). Complexity and decision making. Behavioral Science, 25 , 285–296.

McCarthy, J. (1956). The inversion of functions defined by Turing machines. In C. E. Shannon & J. McCarthy (Eds.), Automata studies (AM-34) . Princeton: Princeton University Press.

Newell, A., & Simon, H. A. (1972). Human problem solving . Englewood Cliffs: Prentice-Hall.

O’Neil, H. F., Chuang, S., & Chung, G. K. W. K. (2003). Issues in the computer-based assessment of collaborative problem solving. Assessment in Education: Principles, Policy & Practice, 10 (3), 361–373. doi: 10.1080/0969594032000148190 .

OECD. (2013). PISA 2012 assessment and analytical framework. Mathematics, reading, science, problem solving and financial literacy . Paris: OECD.

Book   Google Scholar  

OECD. (2014). PISA 2012 results: Creative problem solving: Students’ skills in tackling real-life problems (Vol. V). Paris: OECD Publishing.

Rittel, H. W. J., & Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4 , 155–169.

Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124 (2), 262–274. doi: 10.1037/0033-2909.124.2.262 .

Schoppek, W., & Fischer, A. (2015). Complex problem solving – single ability or complex phenomenon? Frontiers in Psychology, 6 (1669), 1–4. https://doi.org/10.3389/fpsyg.2015.01669 .

Selten, R., Pittnauer, S., & Hohnisch, M. (2012). Dealing with dynamic decision problems when knowledge of the environment is limited: An approach based on goal systems. Journal of Behavioral Decision Making, 25 (5), 443–457. doi: 10.1002/bdm.738 .

Spering, M., Wagener, D., & Funke, J. (2005). The role of emotions in complex problem-solving. Cognition & Emotion, 19 (8), 1252–1261. doi: 10.1080/02699930500304886 .

Sternberg, R. J., & Frensch, P. A. (Eds.). (1991). Complex problem solving: Principles and mechanisms . Hillsdale: Erlbaum.

Strohschneider, S., & Güss, D. (1999). The fate of the Moros: A cross-cultural exploration of strategies in complex and dynamic decision making. International Journal of Psychology, 34 , 235–252.

Treffinger, D. J., Isaksen, S. G., & Dorval, K. B. (1994). Creative problem solving: An overview. In M. A. Runco (Ed.), Problem finding, problem solving and creativity (pp. 223–236). Norwood: Ablex.

Vester, F. (2007). The art of interconnected thinking. Ideas and tools for tackling complexity . Munich: MCB-Verlag.

Vollmeyer, R., & Rheinberg, F. (2000). Does motivation affect performance via persistence? Learning and Instruction, 10 , 293–309. doi: 10.1016/S0959-4752(99)00031-6 .

Willis, S. L. (1996). Everyday problem solving. In J. E. Birren, K. W. Schaie, et al. (Eds.), Handbook of the psychology of aging (4th ed., pp. 287–307). San Diego: Academic.

Wood, C. (2006). The development of creative problem solving in chemistry. Chemistry Education Research and Practice, 7 (2), 96–113. doi: 10.1039/b6rp90003h .

Zelazo, P. D., Carter, A., Reznick, J. S., & Frye, D. (1997). Early development of executive function: A problem-solving framework. Review of General Psychology, 1 (2), 198–226.

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Acknowledgment

The authors wish to thank Bruce Beswick, Esther Care, and Mark Wilson for extensive and helpful comments to earlier versions of this manuscript. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest. The research was supported by a grant from the German Research Foundation (DFG) to the first author (Az. Fu 173/14).

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Funke, J., Fischer, A., Holt, D.V. (2018). Competencies for Complexity: Problem Solving in the Twenty-First Century. In: Care, E., Griffin, P., Wilson, M. (eds) Assessment and Teaching of 21st Century Skills. Educational Assessment in an Information Age. Springer, Cham. https://doi.org/10.1007/978-3-319-65368-6_3

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6 Employee Competency Assessment Best Practices

March 5, 2024 6 min read

Organizations that strive for excellence must have a robust and agile way to assess the capabilities, knowledge, and skills of their diverse workforce. An effective employee competency assessment is a critical tool to help organizations pre-assess, evaluate, and continuously monitor their workforce. In this blog, we’ll uncover what a competency assessment is, the features to look for, and six tips to make the most of this powerful tool.

What is an Employee Competency Assessment?

An employee competency assessment is a foundational workforce evaluation tool. At Vector Solutions, our Competency Assessment tool is integrated within our Learning Management System (LMS) . This tool allows companies to evaluate an individual’s knowledge specific to their job roles and responsibilities.

That information then helps organizations identify the strengths and weaknesses of their workforce, any skills gaps, and identify where additional training is required.

Here’s why this functionality is so important to modern workforce management:

• Strategic evaluation. At its essence, an Employee Competency Assessment strategically evaluates the proficiency of individuals within an organization. It goes beyond a one-time snapshot, offering a continuous monitoring mechanism to track employees’ growth and development over time.
• Informed decision-making. Using insights from competency assessments allows organizations to make informed decisions on training initiatives, skill development programs, and strategic workforce planning.
• Agile workforce development. The agility of an organization lies in its ability to adapt and grow. Competency assessments contribute to this by streamlining employee evaluations and follow-up actions for more targeted development efforts.

Key Takeaway: Employee Competency Assessments are not just about gauging current abilities but are integral to ongoing workforce development. This tool allows you to get the right training to the right employee at the right time—and do so more efficiently.

Types of Employee Competency Assessments

There are three main ways to use employee competency assessments: pre-screening new hires and pre- and post-training of existing employees.

• Evaluating job applicants. Many companies choose to use employee evaluations as part of their hiring process. One type of pre-screening evaluation is a competency exam. This helps organizations understand what baseline knowledge a job applicant already has, what they might need to be trained on, and whether they are a good fit for the role. Strategic use of competency assessments in the hiring process can save you time and money on hiring the right people. And it can help you curate a better onboarding training program for new hires.
• Pre-training assessments. Quizzing employees on a topic prior to assigning them training can be a huge time saver. In some cases, an employee might already have sufficient knowledge on a subject and can effectively “test out” of certain optional training. Or you might discover large gaps in knowledge, giving you an opportunity to revamp and modify your training program.
• Post-training assessments. Last, you can use these assessments to validate that your employees have learned what they were supposed to from their assigned training. If not, this allows you to assign additional training.

Want to learn more about how Vector Solutions’ Competency Tool can work for your business? Download our free product brochure below ⬇️

Competency Assessment Tool Product Brochure

Learn how Vector Solutions’ Competency Assessment tool can help you improve onboarding, retention, and hiring processes.

6 Competency Assessment Best Practices

So, how can you get the most out of your employee competency assessments? These six best practices can help ensure you strike the right cadence and align your assessments with business objectives.

1. Start with Goals in Mind

Always start by asking: why are we conducting this assessment? It’s important to understand what you hope to learn and have a plan for what you’ll do with the assessment results. Clearly define your goals ahead of time so you can be ready with a roadmap for next steps. This also helps ensure that your training goals are aligning with your broader company objectives.

2. Align with Organizational Values

Especially if you plan to conduct pre-hiring assessments, it’s important to align the goal of the assessment and the subject matter to your company values. This helps ensure that you aren’t just measuring knowledge competencies but that the employee will align with your operating principles.

3. Include Stakeholder Input

Involve key stakeholders, including managers, team leaders, and employees, in the competency assessment process. Their insights may provide a more comprehensive understanding of an individual’s performance and potential areas for growth.

Your employees can also share helpful insights on the broader training program—are courses and assessments assigned in a way that sets them up for success? Do they have sufficient time? Where do they need additional assistance?

Ask your employees what they think and modify your training program accordingly.

4. Conduct Regular Assessments

Remember that there are many ways to use competency assessments effectively. Conduct regular assessments throughout your training process to ensure the effectiveness of training at your organization.

Remember that employees forget as much as 70% of their training within 24 hours . So, it’s important to not just conduct assessments immediately after an employee completes training, but at various intervals after the fact.

5. Keep Assessments Succinct

Avoid overwhelming participants with lengthy assessments. Keep them focused and engaged by prioritizing key competencies. A concise assessment not only respects participants’ time but also enhances the accuracy of results.

We recommend including around 10 to 15 questions per assessment. Remember that most of your employees are deskless and lose productivity by being pulled out of work for longer periods of time. Asking fewer, but more impactful, questions ensures employees can complete assessments in a timely manner while still proving their knowledge.

6. Provide Constructive Feedback

Establish a feedback mechanism that accompanies competency assessments. Offer constructive feedback to individuals, highlighting not just areas of improvement but also acknowledging and reinforcing their strengths. This encourages a culture of continuous learning and development.

Why Choose Vector’s Employee Competency Assessments?

“It’s about what can we do to identify your gaps individually and then fill in those gaps so that you can be more effective in what you do. That’s not only a benefit to the plant, it’s a benefit to the individual.” — Sr. Maintenance Manager

Our employee Competency Assessment tool can be added to our award-winning LMS and used to:

• Save time creating assessments, finding skills gaps, assigning training, and reporting on results.
• Improve assessments using Vector’s Question Bank—pre-built questions based directly on our eLearning courses.
• Customize training and assessments to fit your organization’s needs and goals.
• Improve insights and analysis by automating reporting and removing manual tracking processes.

Vector Solutions Competency Assessment

Create a stronger workforce training program using Vector Solutions’ Competency Assessment tool. Pre-assess knowledge and skills, automatically assign training to close gaps, and verify retention of critical information.

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30 Examples: Self Evaluation Comments for Problem Solving

Self-evaluation is an essential aspect of professional development. It helps you to identify areas of improvement and measure your progress towards achieving your goals. By evaluating your problem-solving skills, you can identify your strengths and weaknesses and take steps to improve your performance.

Problem Solving Self-Evaluation Comments Examples

• I was able to identify the root cause of the problem and develop a solution that addressed it effectively.
• I was able to think outside the box and come up with a creative solution to a complex problem.
• I was able to collaborate effectively with my team members to solve a challenging problem.
• I was able to prioritize tasks and allocate resources efficiently to solve a problem within a tight deadline.
• I was able to remain calm and composed under pressure while solving a critical problem.
• I was able to analyze data and information to identify patterns and trends that helped me solve a problem.
• I was able to communicate clearly and effectively with stakeholders to understand their needs and solve their problems.
• I was able to adapt to changing circumstances and adjust my problem-solving approach accordingly.
• I was able to learn from my mistakes and apply those lessons to future problem-solving situations.
• I was able to use critical thinking skills to evaluate multiple options and select the best solution to a problem.
• I was able to break down a complex problem into smaller, more manageable parts and solve each part individually.
• I was able to identify potential obstacles and develop contingency plans to overcome them while solving a problem.
• I was able to leverage my technical expertise to solve a problem that required specialized knowledge.
• I was able to use my creativity and innovation to develop a unique solution to a problem.
• I was able to gather and analyze feedback from stakeholders to continuously improve my problem-solving approach.
• I was able to use my leadership skills to motivate and guide my team members towards a successful problem-solving outcome.
• I was able to effectively manage competing priorities and still solve a problem within the given timeline.
• I was able to use my communication skills to explain complex technical solutions to non-technical stakeholders.
• I was able to use my analytical skills to identify patterns and trends that helped me solve a problem more efficiently.
• I was able to use my problem-solving skills to identify opportunities for process improvements and implement them successfully.
• I was able to use my research skills to gather information that helped me solve a problem more effectively.
• I was able to use my project management skills to break down a large-scale problem into smaller, more manageable tasks.
• I was able to use my negotiation skills to reach a mutually beneficial solution to a problem.
• I was able to remain objective and unbiased while evaluating potential solutions to a problem.
• I was able to use my attention to detail to identify small but critical issues that were contributing to a larger problem.
• I was able to use my interpersonal skills to build strong relationships with stakeholders and work collaboratively towards a solution.
• I was able to use my problem-solving skills to find a solution that balanced the needs of multiple stakeholders.
• I was able to use my persistence and determination to keep working towards a solution even when faced with obstacles.
• I was able to use my time management skills to prioritize tasks and allocate my time efficiently while solving a problem.
• I was able to use my empathy and understanding of others’ perspectives to develop a solution that met everyone’s needs.

Improving Problem Solving Skills

To become a better problem solver, you need to develop critical thinking skills, effective communication skills, prioritize tasks, and use brainstorming techniques. Here are some tips to help you improve your problem-solving skills:

Developing Critical Thinking Skills

Critical thinking is the ability to analyze a situation, identify problems, and come up with creative solutions. To develop critical thinking skills, you need to:

• Ask questions: Don’t be afraid to ask questions to clarify the problem or gather more information.
• Challenge assumptions: Don’t accept things at face value. Question assumptions and look for evidence to support them.
• Evaluate evidence: Look for evidence that supports or contradicts your assumptions. Evaluate the quality and reliability of the evidence.
• Consider alternative perspectives: Try to see the problem from different angles and consider alternative solutions.

Effective Communication Skills

Effective communication is essential for problem-solving because it helps you:

• Understand the problem: Good communication skills help you clarify the problem and understand what is expected of you.
• Collaborate with others: Effective communication skills help you work with others to find solutions.
• Express your ideas clearly: Clear communication helps you convey your ideas and solutions to others.

To improve your communication skills, you need to:

• Listen actively: Listen to others and try to understand their perspective.
• Speak clearly: Speak clearly and concisely to avoid confusion.
• Use nonverbal cues: Pay attention to body language and other nonverbal cues to understand what others are saying.

Prioritizing Tasks

Prioritizing tasks is essential for effective problem-solving because it helps you:

• Focus on the most important tasks: Prioritizing helps you focus on the tasks that will have the most significant impact.
• Manage your time: Prioritizing helps you manage your time more effectively.
• Avoid procrastination: Prioritizing helps you avoid procrastination by breaking down large tasks into smaller, more manageable ones.

To prioritize tasks effectively, you need to:

• Identify the most important tasks: Identify the tasks that will have the most significant impact.
• Break down large tasks: Break large tasks into smaller, more manageable ones.
• Set deadlines: Set deadlines for each task to help you stay on track.

Brainstorming Techniques

Brainstorming is a technique used to generate creative ideas and solutions. To brainstorm effectively, you need to:

• Generate a lot of ideas: Don’t be afraid to come up with as many ideas as possible, even if they seem silly or unrealistic.
• Encourage creativity: Encourage creative thinking by allowing everyone to contribute ideas.
• Avoid criticism: Don’t criticize or judge ideas during the brainstorming process.

To brainstorm effectively, you can use techniques like mind mapping, free writing, or group brainstorming sessions.

Time Management and Productivity

Managing time effectively.

One of the biggest challenges when it comes to problem-solving is managing your time effectively. It’s easy to get bogged down in the details and lose track of the big picture. To avoid this, set specific goals and deadlines for yourself. Make a to-do list and prioritize your tasks based on their importance and urgency. Use a timer or a stopwatch to keep track of how much time you spend on each task, and try to minimize distractions as much as possible.

For example, if you’re working on a project that requires a lot of research, set a goal to finish the research phase by the end of the day. Break the research down into smaller tasks, such as reading a certain number of articles or books, and set deadlines for each task. This will help you stay on track and ensure that you’re making progress towards your goal.

Overcoming Overwhelm

Feeling overwhelmed is a common problem when it comes to problem-solving. When you’re faced with a complex problem, it’s easy to feel like you don’t know where to start. To overcome this, break the problem down into smaller, more manageable parts. Identify the key issues or questions that need to be addressed, and focus on one at a time.

For example, if you’re trying to solve a problem with a product or service, start by identifying the key issues that are causing the problem. Once you’ve identified these issues, break them down into smaller, more manageable parts. Focus on one issue at a time, and come up with a plan to address it. Once you’ve addressed all of the key issues, you’ll have a better understanding of the problem as a whole, and you’ll be better equipped to come up with a solution.

Being Proactive

Being proactive is an important part of problem-solving. Instead of waiting for problems to arise, take a proactive approach and try to anticipate potential problems before they occur. This will help you stay ahead of the curve and avoid potential roadblocks.

For example, if you’re working on a project with a tight deadline, don’t wait until the last minute to start working on it. Instead, start working on it as soon as possible, and set specific goals and deadlines for yourself. This will help you stay on track and ensure that you’re making progress towards your goal. Additionally, be proactive in identifying potential roadblocks or issues that could arise, and come up with a plan to address them before they become a problem.

Performance Review and Goal Setting

Setting objectives.

When preparing for a performance review, it’s important to set specific objectives that will guide the conversation. Start by reflecting on your current role and responsibilities, and consider areas where you could improve or grow. These objectives should be measurable and achievable, and should align with your personal and professional goals.

For example, one objective might be to improve your communication skills by attending a workshop or taking an online course. Another objective might be to take on more leadership responsibilities within your team or department.

Measuring Performance

During the performance review, your manager will likely evaluate your progress towards meeting your objectives. It’s important to come prepared with concrete examples of how you’ve worked towards your goals, as well as any challenges or obstacles you’ve faced.

For example, if your objective was to improve your project management skills, you might share how you’ve successfully led a project from start to finish, or how you’ve implemented new tools or processes to streamline your workflow. If you’ve faced challenges, be honest about what went wrong and what you learned from the experience.

Creating an Action Plan

After reviewing your performance, you and your manager should work together to create an action plan for the next review period. This plan should include specific goals and objectives, as well as a timeline for achieving them. It’s also important to identify any resources or support you may need to reach your goals.

For example, if your objective is to improve your technical skills, you might discuss opportunities for additional training or mentorship. If your goal is to take on more leadership responsibilities, you might discuss ways to gain experience through shadowing or cross-functional projects.

Overall, the performance review and goal setting process is an important opportunity to reflect on your progress and set a course for future growth and development. By setting specific, measurable objectives and working collaboratively with your manager, you can ensure that you’re on track to achieve your personal and professional goals.

When writing self-evaluation comments, it is important to be honest and objective. Avoid making exaggerated or false claims about your abilities or achievements. Instead, focus on specific examples that demonstrate your skills and accomplishments.

• 30 Examples: Innovation and Creativity Self Evaluation Comments
• 45 Self Evaluation Sample Answers: Strengths and Weaknesses
• Authenticity: How to Be Your Authentic Self (Examples & Strategies)
• What is Problem Solving? (Steps, Techniques, Examples)
• What is Self Compassion? (Exercises, Methods, Examples)
• How to Cultivate Self-Discipline: Essential Strategies

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Medical Safety Expert

About the role.

Major accountabilities:

• Perform medical review of ICSRs including (SUSARs, cases from special countries), assessment of Literature cases and authoring of enhanced MAC. • Support safety lead for authoring medical assessment letters based on the bi-annual/six monthly line listing. • Perform literature review of assigned articles (CQC, pre-screening and SICO) and assist safety lead in review of articles for inclusion in PBRER, DSUR, IB etc. • Provide rotating support to the TAs as per the business needs, (i.e. co-authoring safety documents, assisting in providing safety input to regulatory and clinical documents). • Assist the TA Safety Leads in monitoring the safety profile of products including but not limited to the activities such as literature review, medical review of individual cases, including collecting additional follow-up information as necessary, medical evaluation of quality defects. • Together with the Safety Leads, co-author of the PBRER. Provides medical inputs to the sections 9, 15, 16, 17, 18, including analytical input to PBRER for risks defined in the RMP. Perform follow up activities on HA assessment reports. • Co-authors and contributes to the medical sections of Development Safety Update Report (DSUR), Investigator Brochures (IB), labelling documents (e.g. CDS, (SMPC, USPI, Japanese PI), Product Guidance Documents (PGD) and Expert Statements. • Supports the preparation and review of Investigator Notifications (INs). • Provide support signal detection and signal evaluation activities for assigned products. • Provide support for the preparation of Health Authority queries.

• Assists Safety Leads in evaluating and writing other safety related documents including but not limited to Clinical Overview, Development Safety Profiling Plan (d-SPP) and RMP. • Provides safety input to Addendum to Clinical Overview (ACO) for license renewal. • Provides support as needed for new indication submission (regulatory document safety input). • Supports the safety lead for preparation and participation on internal review meetings like, SMT, MSRB and GLC. • Act as Subject Matter Expert (SME) for Medical Function process and provide support during audit and inspections. • Collaborate with other Global Line Functions across Novartis and Third Parties to meet joint accountabilities. • Contribute to PV&PV initiatives as well as cross-functional projects to optimize medical review processes and quality. • Contribute to development and optimization of training materials. Deliver training to the Novartis staff and external.

Minimum Requirement :

• Bachelor of Science in Pharmacy /Bachelor of Science in Nursing / PharmD/PhD in relevant field or Medical Degree (MBBS or MD) required. Minimum 3yrs of experience in the pharmaceutical industry or related. Experience in safety document or medical writing including experience coding with MedDRA and WHO dictionaries. • Excellent understanding of clinical trial methodology, ICH GCP, GVP guidelines and medical terminology • Attention to detail and quality focused • Strong organizational and project management skills • Strong communication skills, and the ability to operate effectively in an international environment • Excellent understanding of Human physiology, pharmacology, clinical study objectives, and the drug development process • Strong technical understanding of Biomedical/Biostatics concepts and problem-solving skills • Good presentation skills • Strong computer skills including, but not limited to, creation of spreadsheets, templates, presentations and working with safety databases/applications. • Ability to work independently, under pressure, demonstrating initiative and flexibility through effective innovative leadership ability.

Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture

Join our Novartis Network: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up: https://talentnetwork.novartis.com/network

Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards

Accessibility and accommodation

Novartis is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to perform the essential functions of a position, please send an e-mail to [email protected] and let us know the nature of your request and your contact information. Please include the job requisition number in your message.

Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.

PENGEMBANGAN MODEL PEDAGOGI DIGITAL DALAM PEMBELAJARAN MATEMATIKA TERINTEGRASI COMPUTATIONAL THINKING UNTUK MENINGKATKAN KEMAMPUAN PROBLEM SOLVING SISWA SEKOLAH MENENGAH PERTAMA

Vita Nova Anwar, - (2024) PENGEMBANGAN MODEL PEDAGOGI DIGITAL DALAM PEMBELAJARAN MATEMATIKA TERINTEGRASI COMPUTATIONAL THINKING UNTUK MENINGKATKAN KEMAMPUAN PROBLEM SOLVING SISWA SEKOLAH MENENGAH PERTAMA. S3 thesis, Universitas Pendidikan Indonesia.

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ABSTRAK Vita Nova Anwar (2024). Pengembangan Model Pedagogi Digital dalam Pembelajaran Matematika Terintegrasi Computational Thinking untuk Meningkatkan Kemampuan Problem Solving Siswa SMP Penggunaan teknologi yang melibatkan keterampilan computational thinking merupakan kualifikasi yang diperlukan pada abad 21 ini. Computational thinking erat kaitannya dengan pembelajaran matematika. Dalam memecahkan masalah matematika yang kompleks penting untuk mengikuti langkah-langkah penyelesaian masalah sesuai tahapan computational thinking. Sehingga diperlukan model pembelajaran yang sesuai untuk mendukung hal tersebut. Penelitian ini bertujuan untuk mengembangkan model pedagogi digital dalam pembelajaran matematika terintegrasi computational thinking untuk meningkatkan kemampuan problem solving siswa SMP. Penelitian ini adalah penelitian pengembangan yang mengikuti model Plomp meliputi preliminary research, prototyping phase, dan assesment phase yang diuraikan secara deskriptif. Penelitian dilaksanakan pada dua sekolah SMP di kota Padang yang melibatkan 56 orang siswa kelas VIII. Aktivitas computational thinking yang dikembangkan dalam pembelajaran matematika terdiri dari aktivitas langsung dan aktivitas digital yang berbantukan teknologi. Instrumen penelitian adalah lembar validasi, lembar penilaian kepraktisan oleh guru, dan soal tes kemampuan problem solving. Hasil uji validitas menunjukkan bahwa dari segi konten, bahasa, penyajian dan kegrafikan sudah memenuhi kriteria valid dan sangat valid. Hasil uji praktikalitas memenuhi kriteria sangat praktis. Hasil uji efektivitas menunjukkan bahwa terdapat peningkatan kemampuan problem solving siswa. ABSTRACT Vita Nova Anwar (2024). Development of a Digital Pedagogical Model on Integration of Computational Thinking in Mathematics Learning to Improve Students' Problem Solving Abilities The use of technology involving computational thinking skills is a required qualification today. Computational thinking is closely related to mathematics learning. In solving complex mathematical problems, it is important to follow the problem solving steps according to the stages of computational thinking. So an appropriate learning model is needed to support this. This research aims to develop a digital pedagogy model in mathematics learning integrated with computational thinking to improve problem solving abilities of junior high school students. This research is development research that follows the Plomp model including preliminary research, prototyping phase, and assessment phase which are described descriptively. The research was carried out at two schools in Padang, involving 56 students in grade VIII. The research instruments were a validation sheet, a practicality assessment sheet by the teacher, and problem solving ability test questions. The results of the validity test show that in terms of content, language, presentation and graphics it meets the valid and very valid criteria. The results of the practicality test carried out are very practical criteria. The results of the effectiveness test show that there is an increase in students' problem solving abilities.

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