research methods project example

What Is Research Methodology? Types, Process, Examples In Research Design

Research methodology is the backbone of any successful study, providing a structured approach to collecting and analysing data. It encompasses a broad spectrum of methods, each with specific processes and applications, tailored to answer distinct research questions.

This article will explore various types of research methodologies, delve into their processes, and illustrate with examples how they are applied in real-world research.

Understanding these methodologies is essential for any researcher aiming to conduct thorough and impactful studies.

Types Of Research Methodology

Research methodology contains various strategies and approaches to conduct scientific research, each tailored to specific types of questions and data.

Think of research methodology as the master plan for your study. It guides you on why and how to gather and analyse data, ensuring your approach aligns perfectly with your research question.

This methodology includes deciding between qualitative research, which explores topics in depth through interviews or focus groups, or quantitative research, which quantifies data through surveys and statistical analysis.

There is even an option to mix both, and approach called the mixed method.

If you’re analysing the lived experiences of individuals in a specific setting, qualitative methodologies allow you to capture the nuances of human emotions and behaviours through detailed narratives.

Quantitative methodologies would enable you to measure and compare these experiences in a more structured, numerical format.

Choosing a robust methodology not only provides the rationale for the methods you choose but also highlights the research limitations and ethical considerations, keeping your study transparent and grounded.

It’s a thoughtful composition that gives research its direction and purpose, much like how an architect’s plan is essential before the actual construction begins.

Qualitative Research Methodology

Qualitative research dives deep into the social context of a topic. It collects words and textual data rather than numerical data.

Within the family, qualitative research methodologies can be broken down into several approaches:

Ethnography: Deeply rooted in the traditions of anthropology, you immerse yourself in the community or social setting you’re studying when conducting an ethnography study.

Case Study Research: Here, you explore the complexity of a single case in detail. This could be an institution, a group, or an individual. You might look into interviews, documents, and reports, to build a comprehensive picture of the subject.

Grounded Theory: Here, you try to generate theories from the data itself rather than testing existing hypotheses. You might start with a research question but allow your theories to develop as you gather more data.

Narrative Research: You explore the stories people tell about their lives and personal experiences in their own words. Through techniques like in-depth interviews or life story collections, you analyse the narrative to understand the individual’s experiences.

Discourse Analysis: You analyse written or spoken words to understand the social norms and power structures that underlie the language used. This method can reveal a lot about the social context and the dynamics of power in communication.

These methods help to uncover patterns in how people think and interact. For example, in exploring consumer attitudes toward a new product, you would likely conduct focus groups or participant observations to gather qualitative data.

This method helps you understand the motivations and feelings behind consumer choices.

Quantitative Research Methodology

Quantitative research relies on numerical data to find patterns and test hypotheses. This methodology uses statistical analysis to quantify data and uncover relationships between variables.

There are several approaches in quantitative research:

Experimental Research: This is the gold standard when you aim to determine causality. By manipulating one variable and controlling others, you observe changes in the dependent variables.

Survey Research: A popular approach, because of its efficiency in collecting data from a large sample of participants. By using standardised questions, you can gather data that are easy to analyse statistically.

Correlational Research: This approach tries to identify relationships between two or more variables without establishing a causal link. The strength and direction of these relationships are quantified, albeit without confirming one variable causes another.

Longitudinal Studies: You track variables over time, providing a dynamic view of how situations evolve. This approach requires commitment and can be resource-intensive, but the depth of data they provide is unparalleled.

Cross-sectional Studies: Offers a snapshot of a population at a single point in time. They are quicker and cheaper than longitudinal studies.

Mixed Research Methodology

Mixed methods research combines both approaches to benefit from the depth of qualitative data and the breadth of quantitative analysis.

You might start with qualitative interviews to develop hypotheses about health behaviours in a community. Then, you could conduct a large-scale survey to test these hypotheses quantitatively.

This approach is particularly useful when you want to explore a new area where previous data may not exist, giving you a comprehensive insight into both the empirical and social dimensions of a research problem.

Factors To Consider When Deciding On Research Methodology

When you dive into a research project, choosing the right methodology is akin to selecting the best tools for building a house.

It shapes how you approach the research question, gather data, and interpret the results. Here are a couple of crucial factors to keep in mind.

Research Question Compatibility

The type of research question you pose can heavily influence the methodology you choose. Qualitative methodologies are superb for exploratory research where you aim to understand concepts, perceptions, and experiences.

If you’re exploring how patients feel about a new healthcare policy, interviews and focus groups would be instrumental.

Quantitative methods are your go-to for questions that require measurable and statistical data, like assessing the prevalence of a medical condition across different regions.

Data Requirements

Consider what data is necessary to address your research question effectively. Qualitative data can provide depth and detail through:

images, and

This makes qualitative method ideal for understanding complex social interactions or historical contexts.

Quantitative data, however, offers the breadth and is often numerical, allowing for a broad analysis of patterns and correlations.

If your study aims to investigate both the breadth and depth, a mixed methods approach might be necessary, enabling you to draw on the strengths of both qualitative and quantitative data.

Resources and Constraints

While deciding on research methodology, you must evaluate the resources available, including:

funding, and

Quantitative research often requires larger samples and hence, might be more costly and time-consuming.

Qualitative research, while generally less resource-intensive, demands substantial time for data collection and analysis, especially if you conduct lengthy interviews or detailed content analysis.

If resources are limited, adapting your methodology to fit these constraints without compromising the integrity of your research is crucial.

Skill Set and Expertise

Your familiarity and comfort level with various research methodologies will significantly affect your choice.

Conducting sophisticated statistical analyses requires a different skill set than carrying out in-depth qualitative interviews.

If your background is in social science, you might find qualitative methods more within your wheelhouse; whereas, a postgraduate student in epidemiology might be more adept at quantitative methods.

It’s also worth considering the availability of workshops, courses, or collaborators who could complement your skills.

Ethical and Practical Considerations

Different methodologies raise different ethical concerns.

In qualitative research, maintaining anonymity and dealing with sensitive information can be challenging, especially when using direct quotes or detailed descriptions from participants.

Quantitative research might involve considerations around participant consent for large surveys or experiments.

Practically, you need to think about the sampling design to ensure it is representative of the population studied. Non-probability sampling might be quicker and cheaper but can introduce bias, limiting the generalisability of your findings.

By meticulously considering these factors, you tailor your research design to not just answer the research questions effectively but also to reflect the realities of your operational environment.

This thoughtful approach helps ensure that your research is not only robust but also practical and ethical, standing up to both academic scrutiny and real-world application.

What Is Research Methodology? Answered

Research methodology is a crucial framework that guides the entire research process. It involves choosing between various qualitative and quantitative approaches, each tailored to specific research questions and objectives.

Your chosen methodology shapes how data is gathered, analysed, and interpreted, ultimately influencing the reliability and validity of your research findings.

Understanding these methodologies ensures that researchers can effectively write research proposal, address their study’s aims and contribute valuable insights to their field.

Dr Andrew Stapleton has a Masters and PhD in Chemistry from the UK and Australia. He has many years of research experience and has worked as a Postdoctoral Fellow and Associate at a number of Universities. Although having secured funding for his own research, he left academia to help others with his YouTube channel all about the inner workings of academia and how to make it work for you.

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Methodology

Research Methods | Definition, Types, Examples

Research methods are specific procedures for collecting and analysing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

Qualitative vs quantitative : Will your data take the form of words or numbers?
Primary vs secondary : Will you collect original data yourself, or will you use data that have already been collected by someone else?
Descriptive vs experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyse the data .

For quantitative data, you can use statistical analysis methods to test relationships between variables.
For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Methods for collecting data, examples of data collection methods, methods for analysing data, examples of data analysis methods, frequently asked questions about methodology.

Data are the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .


Qualitative
Quantitative		.

You can also take a mixed methods approach, where you use both qualitative and quantitative research methods.

Primary vs secondary data

Primary data are any original information that you collect for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary data are information that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data. But if you want to synthesise existing knowledge, analyse historical trends, or identify patterns on a large scale, secondary data might be a better choice.


Primary
Secondary

Descriptive vs experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.


Descriptive
Experimental

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Research methods for collecting data
Research method	Primary or secondary?	Qualitative or quantitative?	When to use
	Primary	Quantitative	To test cause-and-effect relationships.
	Primary	Quantitative	To understand general characteristics of a population.
Interview/focus group	Primary	Qualitative	To gain more in-depth understanding of a topic.
Observation	Primary	Either	To understand how something occurs in its natural setting.
	Secondary	Either	To situate your research in an existing body of work, or to evaluate trends within a research topic.
	Either	Either	To gain an in-depth understanding of a specific group or context, or when you don’t have the resources for a large study.

Your data analysis methods will depend on the type of data you collect and how you prepare them for analysis.

Data can often be analysed both quantitatively and qualitatively. For example, survey responses could be analysed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that were collected:

From open-ended survey and interview questions, literature reviews, case studies, and other sources that use text rather than numbers.
Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions.

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that were collected either:

During an experiment.
Using probability sampling methods .

Because the data are collected and analysed in a statistically valid way, the results of quantitative analysis can be easily standardised and shared among researchers.

Research methods for analysing data
Research method	Qualitative or quantitative?	When to use
	Quantitative	To analyse data collected in a statistically valid manner (e.g. from experiments, surveys, and observations).
Meta-analysis	Quantitative	To statistically analyse the results of a large collection of studies. Can only be applied to studies that collected data in a statistically valid manner.
	Qualitative	To analyse data collected from interviews, focus groups or textual sources. To understand general themes in the data and how they are communicated.
	Either	To analyse large volumes of textual or visual data collected from surveys, literature reviews, or other sources. Can be quantitative (i.e. frequencies of words) or qualitative (i.e. meanings of words).

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Research methods--quantitative, qualitative, and more: overview.

Quantitative Research
Qualitative Research
Data Science Methods (Machine Learning, AI, Big Data)
Text Mining and Computational Text Analysis
Evidence Synthesis/Systematic Reviews
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About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley.

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more. This guide is an introduction, but if you don't see what you need here, always contact your subject librarian, and/or take a look to see if there's a library research guide that will answer your question.

Suggestions for changes and additions to this guide are welcome!

START HERE: SAGE Research Methods

Without question, the most comprehensive resource available from the library is SAGE Research Methods. HERE IS THE ONLINE GUIDE to this one-stop shopping collection, and some helpful links are below:

SAGE Research Methods
Little Green Books (Quantitative Methods)
Little Blue Books (Qualitative Methods)
Dictionaries and Encyclopedias
Case studies of real research projects
Sample datasets for hands-on practice
Streaming video--see methods come to life
Methodspace- -a community for researchers
SAGE Research Methods Course Mapping

Library Data Services at UC Berkeley

Library Data Services Program and Digital Scholarship Services

The LDSP offers a variety of services and tools ! From this link, check out pages for each of the following topics: discovering data, managing data, collecting data, GIS data, text data mining, publishing data, digital scholarship, open science, and the Research Data Management Program.

Be sure also to check out the visual guide to where to seek assistance on campus with any research question you may have!

Library GIS Services

Other Data Services at Berkeley

D-Lab Supports Berkeley faculty, staff, and graduate students with research in data intensive social science, including a wide range of training and workshop offerings Dryad Dryad is a simple self-service tool for researchers to use in publishing their datasets. It provides tools for the effective publication of and access to research data. Geospatial Innovation Facility (GIF) Provides leadership and training across a broad array of integrated mapping technologies on campu Research Data Management A UC Berkeley guide and consulting service for research data management issues

General Research Methods Resources

Here are some general resources for assistance:

Assistance from ICPSR (must create an account to access): Getting Help with Data , and Resources for Students
Wiley Stats Ref for background information on statistics topics
Survey Documentation and Analysis (SDA) . Program for easy web-based analysis of survey data.

Consultants

D-Lab/Data Science Discovery Consultants Request help with your research project from peer consultants.
Research data (RDM) consulting Meet with RDM consultants before designing the data security, storage, and sharing aspects of your qualitative project.
Statistics Department Consulting Services A service in which advanced graduate students, under faculty supervision, are available to consult during specified hours in the Fall and Spring semesters.

Related Resourcex

IRB / CPHS Qualitative research projects with human subjects often require that you go through an ethics review.
OURS (Office of Undergraduate Research and Scholarships) OURS supports undergraduates who want to embark on research projects and assistantships. In particular, check out their "Getting Started in Research" workshops
Sponsored Projects Sponsored projects works with researchers applying for major external grants.
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Last Updated: Aug 6, 2024 3:06 PM
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The Essential Guide to Doing Your Research Project

Student resources.

Examples of Student Research Projects

How to write a research plan: Step-by-step guide

Last updated

30 January 2024

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Today’s businesses and institutions rely on data and analytics to inform their product and service decisions. These metrics influence how organizations stay competitive and inspire innovation. However, gathering data and insights requires carefully constructed research, and every research project needs a roadmap. This is where a research plan comes into play.

Read this step-by-step guide for writing a detailed research plan that can apply to any project, whether it’s scientific, educational, or business-related.

What is a research plan?

A research plan is a documented overview of a project in its entirety, from end to end. It details the research efforts, participants, and methods needed, along with any anticipated results. It also outlines the project’s goals and mission, creating layers of steps to achieve those goals within a specified timeline.

Without a research plan, you and your team are flying blind, potentially wasting time and resources to pursue research without structured guidance.

The principal investigator, or PI, is responsible for facilitating the research oversight. They will create the research plan and inform team members and stakeholders of every detail relating to the project. The PI will also use the research plan to inform decision-making throughout the project.

Why do you need a research plan?

Create a research plan before starting any official research to maximize every effort in pursuing and collecting the research data. Crucially, the plan will model the activities needed at each phase of the research project .

Like any roadmap, a research plan serves as a valuable tool providing direction for those involved in the project—both internally and externally. It will keep you and your immediate team organized and task-focused while also providing necessary definitions and timelines so you can execute your project initiatives with full understanding and transparency.

External stakeholders appreciate a working research plan because it’s a great communication tool, documenting progress and changing dynamics as they arise. Any participants of your planned research sessions will be informed about the purpose of your study, while the exercises will be based on the key messaging outlined in the official plan.

Here are some of the benefits of creating a research plan document for every project:

Project organization and structure

Well-informed participants

All stakeholders and teams align in support of the project

Clearly defined project definitions and purposes

Distractions are eliminated, prioritizing task focus

Timely management of individual task schedules and roles

Costly reworks are avoided

What should a research plan include?

The different aspects of your research plan will depend on the nature of the project. However, most official research plan documents will include the core elements below. Each aims to define the problem statement , devising an official plan for seeking a solution.

Specific project goals and individual objectives

Ideal strategies or methods for reaching those goals

Required resources

Descriptions of the target audience, sample sizes , demographics, and scopes

Key performance indicators (KPIs)

Project background

Research and testing support

Preliminary studies and progress reporting mechanisms

Cost estimates and change order processes

Depending on the research project’s size and scope, your research plan could be brief—perhaps only a few pages of documented plans. Alternatively, it could be a fully comprehensive report. Either way, it’s an essential first step in dictating your project’s facilitation in the most efficient and effective way.

How to write a research plan for your project

When you start writing your research plan, aim to be detailed about each step, requirement, and idea. The more time you spend curating your research plan, the more precise your research execution efforts will be.

Account for every potential scenario, and be sure to address each and every aspect of the research.

Consider following this flow to develop a great research plan for your project:

Define your project’s purpose

Start by defining your project’s purpose. Identify what your project aims to accomplish and what you are researching. Remember to use clear language.

Thinking about the project’s purpose will help you set realistic goals and inform how you divide tasks and assign responsibilities. These individual tasks will be your stepping stones to reach your overarching goal.

Additionally, you’ll want to identify the specific problem, the usability metrics needed, and the intended solutions.

Know the following three things about your project’s purpose before you outline anything else:

What you’re doing

Why you’re doing it

What you expect from it

Identify individual objectives

With your overarching project objectives in place, you can identify any individual goals or steps needed to reach those objectives. Break them down into phases or steps. You can work backward from the project goal and identify every process required to facilitate it.

Be mindful to identify each unique task so that you can assign responsibilities to various team members. At this point in your research plan development, you’ll also want to assign priority to those smaller, more manageable steps and phases that require more immediate or dedicated attention.

Select research methods

Once you have outlined your goals, objectives, steps, and tasks, it’s time to drill down on selecting research methods . You’ll want to leverage specific research strategies and processes. When you know what methods will help you reach your goals, you and your teams will have direction to perform and execute your assigned tasks.

Research methods might include any of the following:

User interviews : this is a qualitative research method where researchers engage with participants in one-on-one or group conversations. The aim is to gather insights into their experiences, preferences, and opinions to uncover patterns, trends, and data.

Field studies : this approach allows for a contextual understanding of behaviors, interactions, and processes in real-world settings. It involves the researcher immersing themselves in the field, conducting observations, interviews, or experiments to gather in-depth insights.

Card sorting : participants categorize information by sorting content cards into groups based on their perceived similarities. You might use this process to gain insights into participants’ mental models and preferences when navigating or organizing information on websites, apps, or other systems.

Focus groups : use organized discussions among select groups of participants to provide relevant views and experiences about a particular topic.

Diary studies : ask participants to record their experiences, thoughts, and activities in a diary over a specified period. This method provides a deeper understanding of user experiences, uncovers patterns, and identifies areas for improvement.

Five-second testing: participants are shown a design, such as a web page or interface, for just five seconds. They then answer questions about their initial impressions and recall, allowing you to evaluate the design’s effectiveness.

Surveys : get feedback from participant groups with structured surveys. You can use online forms, telephone interviews, or paper questionnaires to reveal trends, patterns, and correlations.

Tree testing : tree testing involves researching web assets through the lens of findability and navigability. Participants are given a textual representation of the site’s hierarchy (the “tree”) and asked to locate specific information or complete tasks by selecting paths.

Usability testing : ask participants to interact with a product, website, or application to evaluate its ease of use. This method enables you to uncover areas for improvement in digital key feature functionality by observing participants using the product.

Live website testing: research and collect analytics that outlines the design, usability, and performance efficiencies of a website in real time.

There are no limits to the number of research methods you could use within your project. Just make sure your research methods help you determine the following:

What do you plan to do with the research findings?

What decisions will this research inform? How can your stakeholders leverage the research data and results?

Recruit participants and allocate tasks

Next, identify the participants needed to complete the research and the resources required to complete the tasks. Different people will be proficient at different tasks, and having a task allocation plan will allow everything to run smoothly.

Prepare a thorough project summary

Every well-designed research plan will feature a project summary. This official summary will guide your research alongside its communications or messaging. You’ll use the summary while recruiting participants and during stakeholder meetings. It can also be useful when conducting field studies.

Ensure this summary includes all the elements of your research project . Separate the steps into an easily explainable piece of text that includes the following:

An introduction: the message you’ll deliver to participants about the interview, pre-planned questioning, and testing tasks.

Interview questions: prepare questions you intend to ask participants as part of your research study, guiding the sessions from start to finish.

An exit message: draft messaging your teams will use to conclude testing or survey sessions. These should include the next steps and express gratitude for the participant’s time.

Create a realistic timeline

While your project might already have a deadline or a results timeline in place, you’ll need to consider the time needed to execute it effectively.

Realistically outline the time needed to properly execute each supporting phase of research and implementation. And, as you evaluate the necessary schedules, be sure to include additional time for achieving each milestone in case any changes or unexpected delays arise.

For this part of your research plan, you might find it helpful to create visuals to ensure your research team and stakeholders fully understand the information.

Determine how to present your results

A research plan must also describe how you intend to present your results. Depending on the nature of your project and its goals, you might dedicate one team member (the PI) or assume responsibility for communicating the findings yourself.

In this part of the research plan, you’ll articulate how you’ll share the results. Detail any materials you’ll use, such as:

Presentations and slides

A project report booklet

A project findings pamphlet

Documents with key takeaways and statistics

Graphic visuals to support your findings

Format your research plan

As you create your research plan, you can enjoy a little creative freedom. A plan can assume many forms, so format it how you see fit. Determine the best layout based on your specific project, intended communications, and the preferences of your teams and stakeholders.

Find format inspiration among the following layouts:

Written outlines

Narrative storytelling

Visual mapping

Graphic timelines

Remember, the research plan format you choose will be subject to change and adaptation as your research and findings unfold. However, your final format should ideally outline questions, problems, opportunities, and expectations.

Research plan example

Imagine you’ve been tasked with finding out how to get more customers to order takeout from an online food delivery platform. The goal is to improve satisfaction and retain existing customers. You set out to discover why more people aren’t ordering and what it is they do want to order or experience.

You identify the need for a research project that helps you understand what drives customer loyalty . But before you jump in and start calling past customers, you need to develop a research plan—the roadmap that provides focus, clarity, and realistic details to the project.

Here’s an example outline of a research plan you might put together:

Project title

Project members involved in the research plan

Purpose of the project (provide a summary of the research plan’s intent)

Objective 1 (provide a short description for each objective)

Objective 2

Objective 3

Proposed timeline

Audience (detail the group you want to research, such as customers or non-customers)

Budget (how much you think it might cost to do the research)

Risk factors/contingencies (any potential risk factors that may impact the project’s success)

Remember, your research plan doesn’t have to reinvent the wheel—it just needs to fit your project’s unique needs and aims.

Customizing a research plan template

Some companies offer research plan templates to help get you started. However, it may make more sense to develop your own customized plan template. Be sure to include the core elements of a great research plan with your template layout, including the following:

Introductions to participants and stakeholders

Background problems and needs statement

Significance, ethics, and purpose

Research methods, questions, and designs

Preliminary beliefs and expectations

Implications and intended outcomes

Realistic timelines for each phase

Conclusion and presentations

How many pages should a research plan be?

Generally, a research plan can vary in length between 500 to 1,500 words. This is roughly three pages of content. More substantial projects will be 2,000 to 3,500 words, taking up four to seven pages of planning documents.

What is the difference between a research plan and a research proposal?

A research plan is a roadmap to success for research teams. A research proposal, on the other hand, is a dissertation aimed at convincing or earning the support of others. Both are relevant in creating a guide to follow to complete a project goal.

What are the seven steps to developing a research plan?

While each research project is different, it’s best to follow these seven general steps to create your research plan:

Defining the problem

Identifying goals

Choosing research methods

Recruiting participants

Preparing the brief or summary

Establishing task timelines

Defining how you will present the findings

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Types of Research Methodologies

Table of Contents

There are mainly three types of research methodologies: quantitative, qualitative, and mixed-methods.

Quantitative Research Methodology

Quantitative research focuses on collecting numerical data and analyzing it statistically. It’s great for measuring things objectively.

For instance, if you’re studying how many people prefer coffee over tea, quantitative research can provide concrete numbers.

Qualitative Research Methodology

Qualitative research, on the other hand, dives deep into understanding people’s experiences, feelings, and behaviors. It’s like peeling an onion layer by layer to reveal the underlying emotions and motivations.

For example, if you want to explore why some students struggle with math, qualitative research can uncover personal stories and perspectives.

Mixed-Methods Research

Sometimes, researchers use a combination of quantitative and qualitative methods, known as mixed-methods research.

This approach offers a more comprehensive understanding of a topic by blending numerical data with rich narratives. It’s like having the best of both worlds.

Factors Influencing Choice of Research Methodology

Several factors influence the choice of research methodology:

Nature of the research question: Is it about measuring something objectively or understanding complex human behaviors?
Availability of resources: Do you have access to the tools and expertise needed for a particular methodology?
Time constraints: How much time do you have to conduct the research?
Ethical considerations: Are there any ethical concerns related to your research methods?

Steps Involved in Research Methodology for Project Topics

Regardless of the chosen methodology, research typically follows these steps:

Problem Definition: Clearly define the research question or problem you want to address.
Literature Review: Explore existing research and theories related to your topic to build a solid foundation.
Selection of Research Design: Choose the appropriate methodology based on your research question and objectives.
Data Collection: Gather relevant data using surveys, interviews, observations, or experiments.
Data Analysis: Analyze the collected data using statistical tools (for quantitative research) or thematic analysis (for qualitative research).
Interpretation of Results: Draw conclusions based on your analysis and discuss their implications.

Best Practices in Research Methodology for Project Topics

To ensure the quality and integrity of your research, follow these best practices:

Ensuring validity and reliability of data: Use reliable measurement tools and sampling techniques to minimize errors.
Ethical considerations in research: Obtain informed consent from participants, protect their privacy, and avoid any form of deception.
Proper documentation and citation: Keep detailed records of your research process and cite all sources properly to avoid plagiarism.
Peer review and feedback: Seek feedback from peers and experts in your field to improve the quality of your research.
The impact of online surveys on response rates and data quality.
Comparing the effectiveness of focus groups and individual interviews in marketing research.
Analyzing the ethical considerations of using social media data for research.
Exploring the potential of big data analytics in social science research.
Evaluating the reliability and validity of mixed-methods research approaches.
Examining the role of cultural sensitivity in international research projects.
Investigating the challenges and opportunities of conducting research in conflict zones.
Analyzing the effectiveness of different strategies for recruiting research participants.
Exploring the use of action research methodologies in addressing real-world problems.
Evaluating the impact of researcher bias on the research process and outcomes.
Investigating the potential of citizen science for collecting and analyzing data.
Exploring the use of virtual reality in conducting research studies.
Analyzing the ethical considerations of conducting research with vulnerable populations.
Evaluating the effectiveness of different strategies for disseminating research findings.
Examining the role of storytelling in qualitative research.
Investigating the use of visual methods in research, such as photography and video.
Analyzing the challenges and opportunities of conducting longitudinal research studies.
Exploring the use of case studies in research projects.
Evaluating the effectiveness of different strategies for coding and analyzing qualitative data.
Examining the role of theory in research design and analysis.
Investigating the use of discourse analysis methodologies in research.
Analyzing the strengths and limitations of quantitative research methods.
Exploring the use of experimental research designs in social science research.
Evaluating the effectiveness of different sampling techniques in research.
Examining the role of research ethics committees in ensuring the ethical conduct of research.
Investigating the challenges and opportunities of conducting research online.
Analyzing the impact of social media on public perceptions of research.
Exploring the use of gamification in research to increase participant engagement.
Evaluating the effectiveness of different strategies for data visualization.
Examining the role of open access in making research findings available to a wider audience.
Investigating the challenges and opportunities of interdisciplinary research collaborations.
Analyzing the impact of political and economic factors on research funding.
Exploring the use of participatory action research methodologies to empower communities.
Evaluating the effectiveness of different strategies for knowledge mobilization.
Examining the role of research in informing policy and practice.
Investigating the use of artificial intelligence in research methodologies.
Analyzing the ethical considerations of using facial recognition technology in research.
Exploring the potential of blockchain technology to improve data security and transparency in research.
Evaluating the effectiveness of different strategies for engaging with stakeholders in research projects.
Examining the role of reflexivity in qualitative research.
Investigating the use of narrative inquiry methodologies in research.
Analyzing the strengths and limitations of case studies as a research method.
Exploring the use of secondary data analysis in research projects.
Evaluating the effectiveness of different strategies for managing and storing research data.
Examining the role of research assistants in the research process.
Investigating the challenges and opportunities of conducting research in developing countries.
Analyzing the impact of climate change on research methodologies.
Exploring the use of citizen science for environmental monitoring.
Evaluating the effectiveness of different strategies for conducting research with indigenous communities.
Examining the role of research in promoting social justice.
Investigating the historical development of research methodologies.
Analyzing the impact of technological advancements on research practices.
Exploring the use of mixed methods research approaches in different disciplines.
Evaluating the effectiveness of different strategies for managing research projects.
Examining the role of research funders in shaping research agendas.
Investigating the challenges and opportunities of conducting research across different cultures.
Analyzing the impact of language barriers on research communication.
Exploring the use of collaborative online platforms for conducting research.
Evaluating the effectiveness of different strategies for promoting research skills development.
Examining the role of research misconduct in undermining public trust in research.
Investigating the challenges and opportunities of conducting research with children.
Analyzing the impact of research on mental health and well-being.
Exploring the use of arts-based research methodologies.
Evaluating the effectiveness of different strategies for recruiting and retaining research participants.
Examining the role of research networks in supporting researchers.
Investigating the challenges and opportunities of conducting research in the private sector.
Exploring the use of open science practices to promote research transparency and reproducibility.
Evaluating the effectiveness of different strategies for mentoring and supporting early-career researchers.
Examining the role of research misconduct in retracting scientific articles.
Investigating the challenges and opportunities of data sharing in research.
Analyzing the impact of open data initiatives on scientific progress.
Exploring the use of crowdsourcing in research to gather data and solve problems.
Evaluating the effectiveness of different strategies for promoting research impact.
Examining the role of alternative research metrics in evaluating the quality of research.
Investigating the use of bibliometrics to analyze research trends and identify emerging areas.
Analyzing the impact of research on public policy and decision-making.
Exploring the use of participatory research methodologies to empower communities.
Evaluating the effectiveness of different strategies for communicating research findings to the public.
Examining the role of social media in disseminating research findings.
Analyzing the impact of humanitarian aid on research practices in developing countries.
Exploring the use of research methodologies to address global challenges, such as climate change and poverty.
Evaluating the effectiveness of different strategies for building research capacity in developing countries.
Examining the role of international research collaborations in promoting global research excellence.
Investigating the challenges and opportunities of conducting research in the field of artificial intelligence.
Analyzing the ethical considerations of using autonomous robots in research.
Exploring the potential of artificial intelligence to automate research tasks.
Evaluating the effectiveness of different strategies for mitigating the risks of bias in artificial intelligence-powered research.
Examining the role of research in shaping the future of work.
Investigating the impact of automation on research jobs.
Exploring the use of new technologies to improve research efficiency and productivity.
Evaluating the effectiveness of different strategies for developing transferable skills for researchers.
Examining the role of lifelong learning in maintaining research expertise.
Investigating the impact of research funding cuts on research quality and innovation.
Exploring the use of alternative funding models, such as crowdfunding and philanthropy, to support research.
Evaluating the effectiveness of different strategies for advocating for increased research funding.
Examining the role of research universities in driving innovation and economic growth.
Investigating the impact of research on social and cultural change.
Exploring the future of research methodologies in an ever-changing world.

Examples of Research Methodology Project Topics

Here are some examples of project topics suited for different research methodologies:

Quantitative Research Topics

The impact of social media usage on mental health among teenagers.
Factors influencing customer satisfaction in the hospitality industry.

Qualitative Research Topics

Exploring the experiences of first-generation college students.
Understanding the challenges faced by small business owners during the COVID-19 pandemic.

Mixed-Methods Research Topics

Assessing the effectiveness of a school bullying prevention program .
Investigating the relationship between exercise habits and stress levels among working adults.

Research methodology is like a compass that guides you through the journey of inquiry. By understanding the different types of methodologies, factors influencing their choice, and best practices, you can embark on your research methodology project topics journey with confidence.

Remember, the key to successful research lies in asking the right questions and choosing the appropriate methodology to find the answers.

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What is Research Methodology? Definition, Types, and Examples

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

Why is research methodology important?

Having a good research methodology in place has the following advantages: 3

Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
You can easily answer any questions about your research if they arise at a later stage.
A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
It also helps ensure that ethical guidelines are followed while conducting research.
A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

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Types of research methodology.

There are three types of research methodology based on the type of research and the data required. 1

Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

Sampling: The most common type is probability sampling.
Interviews: Commonly telephonic or done in-person.
Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
Document review: Reviewing existing research or documents to collect evidence for supporting the research.
Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

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What are data analysis methods.

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

Measures of frequency (count, percent, frequency)
Measures of central tendency (mean, median, mode)
Measures of dispersion or variation (range, variance, standard deviation)
Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

Correlation: To understand the relationship between two or more variables.
Cross-tabulation: Analyze the relationship between multiple variables.
Regression analysis: Study the impact of independent variables on the dependent variable.
Frequency tables: To understand the frequency of data.
Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

Research objectives, aims, and questions —these would help structure the research design.
Review existing literature to identify any gaps in knowledge.
Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

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How to write a research methodology .

A research methodology should include the following components: 3,9

Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
Research method —this can be quantitative, qualitative, or mixed-method.
Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
Sampling —this involves selecting a representative subset of the population being studied.
Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
Data analysis —describe the data analysis methods you will use once you’ve collected the data.
Research limitations —mention any limitations you foresee while conducting your research.
Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

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Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

Research design
Data collection procedures
Data analysis methods
Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

Participants should not be subjected to harm.
Respect for the dignity of participants should be prioritized.
Full consent should be obtained from participants before the study.
Participants’ privacy should be ensured.
Confidentiality of the research data should be ensured.
Anonymity of individuals and organizations participating in the research should be maintained.
The aims and objectives of the research should not be exaggerated.
Affiliations, sources of funding, and any possible conflicts of interest should be declared.
Communication in relation to the research should be honest and transparent.
Misleading information and biased representation of primary data findings should be avoided.

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

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Research methodologies. Pfeiffer Library website. Accessed August 15, 2023. https://library.tiffin.edu/researchmethodologies/whatareresearchmethodologies
Types of research methodology. Eduvoice website. Accessed August 16, 2023. https://eduvoice.in/types-research-methodology/
The basics of research methodology: A key to quality research. Voxco. Accessed August 16, 2023. https://www.voxco.com/blog/what-is-research-methodology/
Sampling methods: Types with examples. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/types-of-sampling-for-social-research/
What is qualitative research? Methods, types, approaches, examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-qualitative-research-methods-types-examples/
What is quantitative research? Definition, methods, types, and examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-quantitative-research-types-and-examples/
Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/data-analysis-in-research/#Data_analysis_in_qualitative_research
Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023. https://www.phdmonster.com/factors-to-consider-while-choosing-the-right-research-methodology/
What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

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Home » Research Design – Types, Methods and Examples

Research Design – Types, Methods and Examples

Table of Contents

Research Design

Definition:

Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.

Types of Research Design

Types of Research Design are as follows:

Descriptive Research Design

This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.

Correlational Research Design

Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.

Quasi-experimental Research Design

Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.

Case Study Research Design

Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.

Longitudinal Research Design

Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.

Structure of Research Design

The format of a research design typically includes the following sections:

Introduction : This section provides an overview of the research problem, the research questions, and the importance of the study. It also includes a brief literature review that summarizes previous research on the topic and identifies gaps in the existing knowledge.
Research Questions or Hypotheses: This section identifies the specific research questions or hypotheses that the study will address. These questions should be clear, specific, and testable.
Research Methods : This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques.
Data Collection: This section describes how the data will be collected, including the sample size, data collection procedures, and any ethical considerations.
Data Analysis: This section describes how the data will be analyzed, including the statistical techniques that will be used to test the research questions or hypotheses.
Results : This section presents the findings of the study, including descriptive statistics and statistical tests.
Discussion and Conclusion : This section summarizes the key findings of the study, interprets the results, and discusses the implications of the findings. It also includes recommendations for future research.
References : This section lists the sources cited in the research design.

Example of Research Design

An Example of Research Design could be:

Research question: Does the use of social media affect the academic performance of high school students?

Research design:

Research approach : The research approach will be quantitative as it involves collecting numerical data to test the hypothesis.
Research design : The research design will be a quasi-experimental design, with a pretest-posttest control group design.
Sample : The sample will be 200 high school students from two schools, with 100 students in the experimental group and 100 students in the control group.
Data collection : The data will be collected through surveys administered to the students at the beginning and end of the academic year. The surveys will include questions about their social media usage and academic performance.
Data analysis : The data collected will be analyzed using statistical software. The mean scores of the experimental and control groups will be compared to determine whether there is a significant difference in academic performance between the two groups.
Limitations : The limitations of the study will be acknowledged, including the fact that social media usage can vary greatly among individuals, and the study only focuses on two schools, which may not be representative of the entire population.
Ethical considerations: Ethical considerations will be taken into account, such as obtaining informed consent from the participants and ensuring their anonymity and confidentiality.

How to Write Research Design

Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:

Define the research question or hypothesis : Before beginning your research design, you should clearly define your research question or hypothesis. This will guide your research design and help you select appropriate methods.
Select a research design: There are many different research designs to choose from, including experimental, survey, case study, and qualitative designs. Choose a design that best fits your research question and objectives.
Develop a sampling plan : If your research involves collecting data from a sample, you will need to develop a sampling plan. This should outline how you will select participants and how many participants you will include.
Define variables: Clearly define the variables you will be measuring or manipulating in your study. This will help ensure that your results are meaningful and relevant to your research question.
Choose data collection methods : Decide on the data collection methods you will use to gather information. This may include surveys, interviews, observations, experiments, or secondary data sources.
Create a data analysis plan: Develop a plan for analyzing your data, including the statistical or qualitative techniques you will use.
Consider ethical concerns : Finally, be sure to consider any ethical concerns related to your research, such as participant confidentiality or potential harm.

When to Write Research Design

Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.

Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.

Purpose of Research Design

The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.

Some of the key purposes of research design include:

Providing a clear and concise plan of action for the research study.
Ensuring that the research is conducted ethically and with rigor.
Maximizing the accuracy and reliability of the research findings.
Minimizing the possibility of errors, biases, or confounding variables.
Ensuring that the research is feasible, practical, and cost-effective.
Determining the appropriate research methodology to answer the research question(s).
Identifying the sample size, sampling method, and data collection techniques.
Determining the data analysis method and statistical tests to be used.
Facilitating the replication of the study by other researchers.
Enhancing the validity and generalizability of the research findings.

Applications of Research Design

There are numerous applications of research design in various fields, some of which are:

Social sciences: In fields such as psychology, sociology, and anthropology, research design is used to investigate human behavior and social phenomena. Researchers use various research designs, such as experimental, quasi-experimental, and correlational designs, to study different aspects of social behavior.
Education : Research design is essential in the field of education to investigate the effectiveness of different teaching methods and learning strategies. Researchers use various designs such as experimental, quasi-experimental, and case study designs to understand how students learn and how to improve teaching practices.
Health sciences : In the health sciences, research design is used to investigate the causes, prevention, and treatment of diseases. Researchers use various designs, such as randomized controlled trials, cohort studies, and case-control studies, to study different aspects of health and healthcare.
Business : Research design is used in the field of business to investigate consumer behavior, marketing strategies, and the impact of different business practices. Researchers use various designs, such as survey research, experimental research, and case studies, to study different aspects of the business world.
Engineering : In the field of engineering, research design is used to investigate the development and implementation of new technologies. Researchers use various designs, such as experimental research and case studies, to study the effectiveness of new technologies and to identify areas for improvement.

Advantages of Research Design

Here are some advantages of research design:

Systematic and organized approach : A well-designed research plan ensures that the research is conducted in a systematic and organized manner, which makes it easier to manage and analyze the data.
Clear objectives: The research design helps to clarify the objectives of the study, which makes it easier to identify the variables that need to be measured, and the methods that need to be used to collect and analyze data.
Minimizes bias: A well-designed research plan minimizes the chances of bias, by ensuring that the data is collected and analyzed objectively, and that the results are not influenced by the researcher’s personal biases or preferences.
Efficient use of resources: A well-designed research plan helps to ensure that the resources (time, money, and personnel) are used efficiently and effectively, by focusing on the most important variables and methods.
Replicability: A well-designed research plan makes it easier for other researchers to replicate the study, which enhances the credibility and reliability of the findings.
Validity: A well-designed research plan helps to ensure that the findings are valid, by ensuring that the methods used to collect and analyze data are appropriate for the research question.
Generalizability : A well-designed research plan helps to ensure that the findings can be generalized to other populations, settings, or situations, which increases the external validity of the study.

Research Design Vs Research Methodology

Research Design	Research Methodology
The plan and structure for conducting research that outlines the procedures to be followed to collect and analyze data.	The set of principles, techniques, and tools used to carry out the research plan and achieve research objectives.
Describes the overall approach and strategy used to conduct research, including the type of data to be collected, the sources of data, and the methods for collecting and analyzing data.	Refers to the techniques and methods used to gather, analyze and interpret data, including sampling techniques, data collection methods, and data analysis techniques.
Helps to ensure that the research is conducted in a systematic, rigorous, and valid way, so that the results are reliable and can be used to make sound conclusions.	Includes a set of procedures and tools that enable researchers to collect and analyze data in a consistent and valid manner, regardless of the research design used.
Common research designs include experimental, quasi-experimental, correlational, and descriptive studies.	Common research methodologies include qualitative, quantitative, and mixed-methods approaches.
Determines the overall structure of the research project and sets the stage for the selection of appropriate research methodologies.	Guides the researcher in selecting the most appropriate research methods based on the research question, research design, and other contextual factors.
Helps to ensure that the research project is feasible, relevant, and ethical.	Helps to ensure that the data collected is accurate, valid, and reliable, and that the research findings can be interpreted and generalized to the population of interest.

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15 Types of Research Methods

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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types of research methods, explained below

Research methods refer to the strategies, tools, and techniques used to gather and analyze data in a structured way in order to answer a research question or investigate a hypothesis (Hammond & Wellington, 2020).

Generally, we place research methods into two categories: quantitative and qualitative. Each has its own strengths and weaknesses, which we can summarize as:

Quantitative research can achieve generalizability through scrupulous statistical analysis applied to large sample sizes.
Qualitative research achieves deep, detailed, and nuance accounts of specific case studies, which are not generalizable.

Some researchers, with the aim of making the most of both quantitative and qualitative research, employ mixed methods, whereby they will apply both types of research methods in the one study, such as by conducting a statistical survey alongside in-depth interviews to add context to the quantitative findings.

Below, I’ll outline 15 common research methods, and include pros, cons, and examples of each .

Types of Research Methods

Research methods can be broadly categorized into two types: quantitative and qualitative.

Quantitative methods involve systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques, providing an in-depth understanding of a specific concept or phenomenon (Schweigert, 2021). The strengths of this approach include its ability to produce reliable results that can be generalized to a larger population, although it can lack depth and detail.
Qualitative methods encompass techniques that are designed to provide a deep understanding of a complex issue, often in a specific context, through collection of non-numerical data (Tracy, 2019). This approach often provides rich, detailed insights but can be time-consuming and its findings may not be generalizable.

These can be further broken down into a range of specific research methods and designs:

Primarily Quantitative Methods	Primarily Qualitative methods
Experimental Research	Case Study
Surveys and Questionnaires	Ethnography
Longitudinal Studies	Phenomenology
Cross-Sectional Studies	Historical research
Correlational Research	Content analysis
Causal-Comparative Research	Grounded theory
Meta-Analysis	Action research
Quasi-Experimental Design	Observational research

Combining the two methods above, mixed methods research mixes elements of both qualitative and quantitative research methods, providing a comprehensive understanding of the research problem . We can further break these down into:

Sequential Explanatory Design (QUAN→QUAL): This methodology involves conducting quantitative analysis first, then supplementing it with a qualitative study.
Sequential Exploratory Design (QUAL→QUAN): This methodology goes in the other direction, starting with qualitative analysis and ending with quantitative analysis.

Let’s explore some methods and designs from both quantitative and qualitative traditions, starting with qualitative research methods.

Qualitative Research Methods

Qualitative research methods allow for the exploration of phenomena in their natural settings, providing detailed, descriptive responses and insights into individuals’ experiences and perceptions (Howitt, 2019).

These methods are useful when a detailed understanding of a phenomenon is sought.

1. Ethnographic Research

Ethnographic research emerged out of anthropological research, where anthropologists would enter into a setting for a sustained period of time, getting to know a cultural group and taking detailed observations.

Ethnographers would sometimes even act as participants in the group or culture, which many scholars argue is a weakness because it is a step away from achieving objectivity (Stokes & Wall, 2017).

In fact, at its most extreme version, ethnographers even conduct research on themselves, in a fascinating methodology call autoethnography .

The purpose is to understand the culture, social structure, and the behaviors of the group under study. It is often useful when researchers seek to understand shared cultural meanings and practices in their natural settings.

However, it can be time-consuming and may reflect researcher biases due to the immersion approach.

Pros of Ethnographic Research	Cons of Ethnographic Research
1. Provides deep cultural insights	1. Time-consuming
2. Contextually relevant findings	2. Potential researcher bias
3. Explores dynamic social processes	3. May

Example of Ethnography

Liquidated: An Ethnography of Wall Street by Karen Ho involves an anthropologist who embeds herself with Wall Street firms to study the culture of Wall Street bankers and how this culture affects the broader economy and world.

2. Phenomenological Research

Phenomenological research is a qualitative method focused on the study of individual experiences from the participant’s perspective (Tracy, 2019).

It focuses specifically on people’s experiences in relation to a specific social phenomenon ( see here for examples of social phenomena ).

This method is valuable when the goal is to understand how individuals perceive, experience, and make meaning of particular phenomena. However, because it is subjective and dependent on participants’ self-reports, findings may not be generalizable, and are highly reliant on self-reported ‘thoughts and feelings’.

Pros of Phenomenological Research	Cons of Phenomenological Research
1. Provides rich, detailed data	1. Limited generalizability
2. Highlights personal experience and perceptions	2. Data collection can be time-consuming
3. Allows exploration of complex phenomena	3. Requires highly skilled researchers

Example of Phenomenological Research

A phenomenological approach to experiences with technology by Sebnem Cilesiz represents a good starting-point for formulating a phenomenological study. With its focus on the ‘essence of experience’, this piece presents methodological, reliability, validity, and data analysis techniques that phenomenologists use to explain how people experience technology in their everyday lives.

3. Historical Research

Historical research is a qualitative method involving the examination of past events to draw conclusions about the present or make predictions about the future (Stokes & Wall, 2017).

As you might expect, it’s common in the research branches of history departments in universities.

This approach is useful in studies that seek to understand the past to interpret present events or trends. However, it relies heavily on the availability and reliability of source materials, which may be limited.

Common data sources include cultural artifacts from both material and non-material culture , which are then examined, compared, contrasted, and contextualized to test hypotheses and generate theories.

Pros of Historical Research	Cons of Historical Research
1.	1. Dependent on available sources
2. Can help understand current events or trends	2. Potential bias in source materials
3. Allows the study of change over time	3. Difficult to replicate

Example of Historical Research

A historical research example might be a study examining the evolution of gender roles over the last century. This research might involve the analysis of historical newspapers, advertisements, letters, and company documents, as well as sociocultural contexts.

4. Content Analysis

Content analysis is a research method that involves systematic and objective coding and interpreting of text or media to identify patterns, themes, ideologies, or biases (Schweigert, 2021).

A content analysis is useful in analyzing communication patterns, helping to reveal how texts such as newspapers, movies, films, political speeches, and other types of ‘content’ contain narratives and biases.

However, interpretations can be very subjective, which often requires scholars to engage in practices such as cross-comparing their coding with peers or external researchers.

Content analysis can be further broken down in to other specific methodologies such as semiotic analysis, multimodal analysis , and discourse analysis .

Pros of Content Analysis	Cons of Content Analysis
1. Unobtrusive data collection	1. Lacks contextual information
2. Allows for large sample analysis	2. Potential coder bias
3. Replicable and reliable if done properly	3. May overlook nuances

Example of Content Analysis

How is Islam Portrayed in Western Media? by Poorebrahim and Zarei (2013) employs a type of content analysis called critical discourse analysis (common in poststructuralist and critical theory research ). This study by Poorebrahum and Zarei combs through a corpus of western media texts to explore the language forms that are used in relation to Islam and Muslims, finding that they are overly stereotyped, which may represent anti-Islam bias or failure to understand the Islamic world.

5. Grounded Theory Research

Grounded theory involves developing a theory during and after data collection rather than beforehand.

This is in contrast to most academic research studies, which start with a hypothesis or theory and then testing of it through a study, where we might have a null hypothesis (disproving the theory) and an alternative hypothesis (supporting the theory).

Grounded Theory is useful because it keeps an open mind to what the data might reveal out of the research. It can be time-consuming and requires rigorous data analysis (Tracy, 2019).

Pros of Grounded Theory Research	Cons of Grounded Theory Research
1. Helps with theory development	1. Time-consuming
2. Rigorous data analysis	2. Requires iterative data collection and analysis
3. Can fill gaps in existing theories	3. Requires skilled researchers

Grounded Theory Example

Developing a Leadership Identity by Komives et al (2005) employs a grounded theory approach to develop a thesis based on the data rather than testing a hypothesis. The researchers studied the leadership identity of 13 college students taking on leadership roles. Based on their interviews, the researchers theorized that the students’ leadership identities shifted from a hierarchical view of leadership to one that embraced leadership as a collaborative concept.

6. Action Research

Action research is an approach which aims to solve real-world problems and bring about change within a setting. The study is designed to solve a specific problem – or in other words, to take action (Patten, 2017).

This approach can involve mixed methods, but is generally qualitative because it usually involves the study of a specific case study wherein the researcher works, e.g. a teacher studying their own classroom practice to seek ways they can improve.

Action research is very common in fields like education and nursing where practitioners identify areas for improvement then implement a study in order to find paths forward.

Pros of Action Research	Cons of Action Research
1. Addresses real-world problems and seeks to find solutions.	1. It is time-consuming and often hard to implement into a practitioner’s already busy schedule
2. Integrates research and action in an action-research cycle.	2. Requires collaboration between researcher, practitioner, and research participants.
3. Can bring about positive change in isolated instances, such as in a school or nursery setting.	3. Complexity of managing dual roles (where the researcher is also often the practitioner)

Action Research Example

Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing by Ellison and Drew was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

7. Natural Observational Research

Observational research can also be quantitative (see: experimental research), but in naturalistic settings for the social sciences, researchers tend to employ qualitative data collection methods like interviews and field notes to observe people in their day-to-day environments.

This approach involves the observation and detailed recording of behaviors in their natural settings (Howitt, 2019). It can provide rich, in-depth information, but the researcher’s presence might influence behavior.

While observational research has some overlaps with ethnography (especially in regard to data collection techniques), it tends not to be as sustained as ethnography, e.g. a researcher might do 5 observations, every second Monday, as opposed to being embedded in an environment.

Pros of Qualitative Observational Research	Cons of Qualitative Observational Research
1. Captures behavior in natural settings, allowing for interesting insights into authentic behaviors.	1. Researcher’s presence may influence behavior
2. Can provide rich, detailed data through the researcher’s vignettes.	2. Can be time-consuming
3. Non-invasive because researchers want to observe natural activities rather than interfering with research participants.	3. Requires skilled and trained observers

Observational Research Example

A researcher might use qualitative observational research to study the behaviors and interactions of children at a playground. The researcher would document the behaviors observed, such as the types of games played, levels of cooperation , and instances of conflict.

8. Case Study Research

Case study research is a qualitative method that involves a deep and thorough investigation of a single individual, group, or event in order to explore facets of that phenomenon that cannot be captured using other methods (Stokes & Wall, 2017).

Case study research is especially valuable in providing contextualized insights into specific issues, facilitating the application of abstract theories to real-world situations (Patten, 2017).

However, findings from a case study may not be generalizable due to the specific context and the limited number of cases studied (Walliman, 2021).

Pros of Case Study Research	Cons of Case Study Research
1. Provides detailed insights	1. Limited generalizability
2. Facilitates the study of complex phenomena	2. Can be time-consuming
3. Can test or generate theories	3. Subject to observer bias

See More: Case Study Advantages and Disadvantages

Example of a Case Study

Scholars conduct a detailed exploration of the implementation of a new teaching method within a classroom setting. The study focuses on how the teacher and students adapt to the new method, the challenges encountered, and the outcomes on student performance and engagement. While the study provides specific and detailed insights of the teaching method in that classroom, it cannot be generalized to other classrooms, as statistical significance has not been established through this qualitative approach.

Quantitative Research Methods

Quantitative research methods involve the systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques (Pajo, 2022). The focus is on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

9. Experimental Research

Experimental research is a quantitative method where researchers manipulate one variable to determine its effect on another (Walliman, 2021).

This is common, for example, in high-school science labs, where students are asked to introduce a variable into a setting in order to examine its effect.

This type of research is useful in situations where researchers want to determine causal relationships between variables. However, experimental conditions may not reflect real-world conditions.

Pros of Experimental Research	Cons of Experimental Research
1. Allows for determination of causality	1. Might not reflect real-world conditions
2. Allows for the study of phenomena in highly controlled environments to minimize research contamination.	2. Can be costly and time-consuming to create a controlled environment.
3. Can be replicated so other researchers can test and verify the results.	3. Ethical concerns need to be addressed as the research is directly manipulating variables.

Example of Experimental Research

A researcher may conduct an experiment to determine the effects of a new educational approach on student learning outcomes. Students would be randomly assigned to either the control group (traditional teaching method) or the experimental group (new educational approach).

10. Surveys and Questionnaires

Surveys and questionnaires are quantitative methods that involve asking research participants structured and predefined questions to collect data about their attitudes, beliefs, behaviors, or characteristics (Patten, 2017).

Surveys are beneficial for collecting data from large samples, but they depend heavily on the honesty and accuracy of respondents.

They tend to be seen as more authoritative than their qualitative counterparts, semi-structured interviews, because the data is quantifiable (e.g. a questionnaire where information is presented on a scale from 1 to 10 can allow researchers to determine and compare statistical means, averages, and variations across sub-populations in the study).

Pros of Surveys and Questionnaires	Cons of Surveys and Questionnaires
1. Data can be gathered from larger samples than is possible in qualitative research.	1. There is heavy dependence on respondent honesty
2. The data is quantifiable, allowing for comparison across subpopulations	2. There is limited depth of response as opposed to qualitative approaches.
3. Can be cost-effective and time-efficient	3. Static with no flexibility to explore responses (unlike semi- or unstrcutured interviewing)

Example of a Survey Study

A company might use a survey to gather data about employee job satisfaction across its offices worldwide. Employees would be asked to rate various aspects of their job satisfaction on a Likert scale. While this method provides a broad overview, it may lack the depth of understanding possible with other methods (Stokes & Wall, 2017).

11. Longitudinal Studies

Longitudinal studies involve repeated observations of the same variables over extended periods (Howitt, 2019). These studies are valuable for tracking development and change but can be costly and time-consuming.

With multiple data points collected over extended periods, it’s possible to examine continuous changes within things like population dynamics or consumer behavior. This makes a detailed analysis of change possible.

a visual representation of a longitudinal study demonstrating that data is collected over time on one sample so researchers can examine how variables change over time

Perhaps the most relatable example of a longitudinal study is a national census, which is taken on the same day every few years, to gather comparative demographic data that can show how a nation is changing over time.

While longitudinal studies are commonly quantitative, there are also instances of qualitative ones as well, such as the famous 7 Up study from the UK, which studies 14 individuals every 7 years to explore their development over their lives.

Pros of Longitudinal Studies	Cons of Longitudinal Studies
1. Tracks changes over time allowing for comparison of past to present events.	1. Is almost by definition time-consuming because time needs to pass between each data collection session.
2. Can identify sequences of events, but causality is often harder to determine.	2. There is high risk of participant dropout over time as participants move on with their lives.

Example of a Longitudinal Study

A national census, taken every few years, uses surveys to develop longitudinal data, which is then compared and analyzed to present accurate trends over time. Trends a census can reveal include changes in religiosity, values and attitudes on social issues, and much more.

12. Cross-Sectional Studies

Cross-sectional studies are a quantitative research method that involves analyzing data from a population at a specific point in time (Patten, 2017). They provide a snapshot of a situation but cannot determine causality.

This design is used to measure and compare the prevalence of certain characteristics or outcomes in different groups within the sampled population.

A visual representation of a cross-sectional group of people, demonstrating that the data is collected at a single point in time and you can compare groups within the sample

The major advantage of cross-sectional design is its ability to measure a wide range of variables simultaneously without needing to follow up with participants over time.

However, cross-sectional studies do have limitations . This design can only show if there are associations or correlations between different variables, but cannot prove cause and effect relationships, temporal sequence, changes, and trends over time.

Pros of Cross-Sectional Studies	Cons of Cross-Sectional Studies
1. Quick and inexpensive, with no long-term commitment required.	1. Cannot determine causality because it is a simple snapshot, with no time delay between data collection points.
2. Good for descriptive analyses.	2. Does not allow researchers to follow up with research participants.

Example of a Cross-Sectional Study

Our longitudinal study example of a national census also happens to contain cross-sectional design. One census is cross-sectional, displaying only data from one point in time. But when a census is taken once every few years, it becomes longitudinal, and so long as the data collection technique remains unchanged, identification of changes will be achievable, adding another time dimension on top of a basic cross-sectional study.

13. Correlational Research

Correlational research is a quantitative method that seeks to determine if and to what degree a relationship exists between two or more quantifiable variables (Schweigert, 2021).

This approach provides a fast and easy way to make initial hypotheses based on either positive or negative correlation trends that can be observed within dataset.

While correlational research can reveal relationships between variables, it cannot establish causality.

Methods used for data analysis may include statistical correlations such as Pearson’s or Spearman’s.

Pros of Correlational Research	Cons of Correlational Research
1. Reveals relationships between variables	1. Cannot determine causality
2. Can use existing data	2. May be
3. Can guide further experimental research	3. Correlation may be coincidental

Example of Correlational Research

A team of researchers is interested in studying the relationship between the amount of time students spend studying and their academic performance. They gather data from a high school, measuring the number of hours each student studies per week and their grade point averages (GPAs) at the end of the semester. Upon analyzing the data, they find a positive correlation, suggesting that students who spend more time studying tend to have higher GPAs.

14. Quasi-Experimental Design Research

Quasi-experimental design research is a quantitative research method that is similar to experimental design but lacks the element of random assignment to treatment or control.

Instead, quasi-experimental designs typically rely on certain other methods to control for extraneous variables.

The term ‘quasi-experimental’ implies that the experiment resembles a true experiment, but it is not exactly the same because it doesn’t meet all the criteria for a ‘true’ experiment, specifically in terms of control and random assignment.

Quasi-experimental design is useful when researchers want to study a causal hypothesis or relationship, but practical or ethical considerations prevent them from manipulating variables and randomly assigning participants to conditions.

Pros	Cons
1. It’s more feasible to implement than true experiments.	1. Without random assignment, it’s harder to rule out confounding variables.
2. It can be conducted in real-world settings, making the findings more applicable to the real world.	2. The lack of random assignment may of the study.
3. Useful when it’s unethical or impossible to manipulate the independent variable or randomly assign participants.	3. It’s more difficult to establish a cause-effect relationship due to the potential for confounding variables.

Example of Quasi-Experimental Design

A researcher wants to study the impact of a new math tutoring program on student performance. However, ethical and practical constraints prevent random assignment to the “tutoring” and “no tutoring” groups. Instead, the researcher compares students who chose to receive tutoring (experimental group) to similar students who did not choose to receive tutoring (control group), controlling for other variables like grade level and previous math performance.

Related: Examples and Types of Random Assignment in Research

15. Meta-Analysis Research

Meta-analysis statistically combines the results of multiple studies on a specific topic to yield a more precise estimate of the effect size. It’s the gold standard of secondary research .

Meta-analysis is particularly useful when there are numerous studies on a topic, and there is a need to integrate the findings to draw more reliable conclusions.

Some meta-analyses can identify flaws or gaps in a corpus of research, when can be highly influential in academic research, despite lack of primary data collection.

However, they tend only to be feasible when there is a sizable corpus of high-quality and reliable studies into a phenomenon.

Pros	Cons
Increased Statistical Power: By combining data from multiple studies, meta-analysis increases the statistical power to detect effects.	Publication Bias: Studies with null or negative findings are less likely to be published, leading to an overestimation of effect sizes.
Greater Precision: It provides more precise estimates of effect sizes by reducing the influence of random error.	Quality of Studies: of a meta-analysis depends on the quality of the studies included.
Resolving Discrepancies: Meta-analysis can help resolve disagreements between different studies on a topic.	Heterogeneity: Differences in study design, sample, or procedures can introduce heterogeneity, complicating interpretation of results.

Example of a Meta-Analysis

The power of feedback revisited (Wisniewski, Zierer & Hattie, 2020) is a meta-analysis that examines 435 empirical studies research on the effects of feedback on student learning. They use a random-effects model to ascertain whether there is a clear effect size across the literature. The authors find that feedback tends to impact cognitive and motor skill outcomes but has less of an effect on motivational and behavioral outcomes.

Choosing a research method requires a lot of consideration regarding what you want to achieve, your research paradigm, and the methodology that is most valuable for what you are studying. There are multiple types of research methods, many of which I haven’t been able to present here. Generally, it’s recommended that you work with an experienced researcher or research supervisor to identify a suitable research method for your study at hand.

Hammond, M., & Wellington, J. (2020). Research methods: The key concepts . New York: Routledge.

Howitt, D. (2019). Introduction to qualitative research methods in psychology . London: Pearson UK.

Pajo, B. (2022). Introduction to research methods: A hands-on approach . New York: Sage Publications.

Patten, M. L. (2017). Understanding research methods: An overview of the essentials . New York: Sage

Schweigert, W. A. (2021). Research methods in psychology: A handbook . Los Angeles: Waveland Press.

Stokes, P., & Wall, T. (2017). Research methods . New York: Bloomsbury Publishing.

Tracy, S. J. (2019). Qualitative research methods: Collecting evidence, crafting analysis, communicating impact . London: John Wiley & Sons.

Walliman, N. (2021). Research methods: The basics. London: Routledge.

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How to Start a Research Project: A Step-by-Step Guide for Beginners

Young researcher with notebook and laptop, colorful charts.

Starting a research project can be a bit overwhelming, especially if it's your first time. But don't worry! This guide will walk you through each step, making the process easier and more manageable. By breaking down the project into smaller tasks, you'll find it much simpler to handle. Let's dive into how you can go from an idea to a well-organized research proposal.

Key Takeaways

Clearly define your research subject to set a strong foundation.
Engage stakeholders early to align expectations and gather input.
Craft a precise research statement to guide your study.
Establish specific research goals to stay focused.
Choose a suitable methodology to ensure reliable results.

Defining the Research Subject

Selecting a topic of interest.

The first step in starting your research project is to choose a topic that genuinely interests you. Selecting a topic that excites you will keep you motivated throughout the research process. Begin by brainstorming broad areas of interest and then narrow them down to a specific niche. Consider the practicalities, such as the availability of resources and the scope of your project. If you're struggling to find a topic, consult with your instructor or peers for guidance.

Narrowing Down the Focus

Once you have a general topic, it's essential to narrow it down to a more specific focus. This involves conducting an initial literature review to identify gaps, debates, and questions within your chosen field. By doing so, you can pinpoint a unique angle for your research. Remember, a well-defined focus will make your research more manageable and impactful.

Aligning with Assignment Instructions

It's crucial to ensure that your chosen topic aligns with the assignment instructions provided by your instructor. Review the guidelines carefully to understand the requirements and limitations. This alignment will not only help you meet academic expectations but also make your research more relevant and structured. If in doubt, seek clarification from your instructor to avoid any misunderstandings.

Engaging with Stakeholders

Identifying key stakeholders.

Before starting your research, it's crucial to identify the key stakeholders involved. These are the people who have a vested interest in your project. They can include supervisors, funding bodies, and even the target audience of your research. Understanding who your stakeholders are will help you align your research goals with their expectations.

Conducting Initial Meetings

Once you've identified your stakeholders, the next step is to conduct initial meetings . These meetings are essential for gathering input and setting expectations. During these meetings, discuss the scope of your research, the methodologies you plan to use, and any potential challenges. This is also a good time to ask for any resources or support you might need.

Gathering Input and Expectations

After the initial meetings, gather all the input and expectations from your stakeholders. This will help you refine your research plan and ensure that it meets everyone's needs. Create a summary document that outlines the key points discussed and any agreed-upon actions. This document will serve as a reference throughout your research project.

Crafting a Precise Research Statement

Formulating the main question.

Creating a strong research statement starts with formulating the main question . This question will guide your entire project. Make sure it is clear and specific. For example, if you're studying the impact of WhatsApp on communication, your main question could be, "How does WhatsApp influence daily communication habits?"

Ensuring Clarity and Conciseness

Your research statement should be both clear and concise. Avoid using complex words or jargon. Instead, focus on making your statement easy to understand. A clear and concise statement helps keep your research focused and on track.

Aligning with Research Goals

Finally, ensure that your research statement aligns with your overall research goals. This means that your statement should directly relate to what you aim to achieve with your study. For instance, if your goal is to understand user behavior on WhatsApp, your research statement should reflect this aim.

Establishing Research Goals

Setting clear research goals is a crucial step in any research project. These goals guide your study and help you stay focused on what you aim to achieve. Here’s how to establish effective research goals:

Identifying Key Areas of Exploration

Start by pinpointing the main areas you want to explore. These should be directly related to your research statement. Identifying these key areas will help you stay organized and ensure that your research is comprehensive.

Setting Specific Objectives

Once you have identified the key areas, the next step is to set specific objectives. These objectives should be clear, measurable, and achievable. Pinpointing the major focus of your research will help you stay on track and make your study more manageable.

Aligning Goals with Stakeholder Expectations

It's important to ensure that your research goals align with the expectations of your stakeholders. This alignment will help you gather the necessary support and resources for your project. Conducting initial meetings with stakeholders can provide valuable input and help you refine your goals.

Conducting a Comprehensive Literature Review

Gathering relevant sources.

Before diving into your research, it's crucial to gather all the relevant sources. Start by doing a preliminary search to see if there's enough information available. Use libraries, online databases, and academic journals to find books, articles, and papers related to your topic. This step ensures you have a solid foundation for your research .

Analyzing Existing Research

Once you have your sources, the next step is to analyze them. Skim through the materials to identify key points and different viewpoints. This will help you understand the current state of research in your field. Pay attention to how these sources relate to your research question.

Identifying Research Gaps

Finally, look for gaps in the existing research. These are areas that haven't been explored or questions that haven't been answered. Identifying these gaps can provide a direction for your own research and make your study more valuable. Conducting a comprehensive literature review is vital for putting your research in context and highlighting what your research will add to the field.

Choosing an Appropriate Methodology

Young researchers collaborating in a modern lab.

Deciding Between Qualitative and Quantitative Methods

When starting your research, you need to decide whether to use qualitative or quantitative methods . Qualitative methods involve first-hand observations like interviews, focus groups, and case studies. These methods are great for exploring complex issues in depth. On the other hand, quantitative methods deal with numbers and logic, focusing on statistics and numerical patterns. They are ideal for testing hypotheses and making generalizable conclusions. Sometimes, a mixed-method approach, combining both qualitative and quantitative methods, can be the best choice.

Selecting Data Collection Tools

Choosing the right tools for data collection is crucial. For qualitative research, you might use interviews, focus groups, or open-ended surveys. For quantitative research, tools like structured surveys, experiments, and statistical software are more appropriate. Make sure your tools align with your research questions and objectives.

Planning Data Analysis Techniques

Once you have collected your data, the next step is to analyze it. For qualitative data, look for patterns and themes. Coding and thematic analysis are common techniques. For quantitative data, use statistical methods to test your hypotheses. Software like SPSS or R can help you manage and analyze large datasets. Proper planning of your data analysis techniques ensures that your findings are reliable and valid.

Creating a Detailed Research Plan

Researcher planning project with books and charts

Creating a detailed research plan is essential for the success of your project. It helps you stay organized and ensures that you cover all necessary aspects of your research. Here are the key steps to follow:

Outlining the Methodology

Start by outlining the methodology you will use. This includes deciding on qualitative or quantitative methods, selecting tools for data collection, and determining how you will analyze the data. A clear methodology is essential for the credibility of your research.

Creating a Research Timeline

Next, create a timeline for your research activities. Break down your tasks into manageable steps and assign deadlines to each. This will help you stay on track and ensure that you complete your project on time. Use a table to organize your timeline:

Task	Deadline
Literature Review	Month 1
Data Collection	Month 2-3
Data Analysis	Month 4
Writing Draft	Month 5
Revisions	Month 6

Allocating Resources Effectively

Finally, allocate your resources effectively. This includes budgeting for any costs, such as software, travel, or materials, and ensuring you have access to necessary resources like libraries or labs. Proper resource allocation can make a significant difference in the quality and feasibility of your research.

Writing the Research Proposal

Structuring the proposal.

When structuring your research proposal, it's essential to include several key components. Start with a clear title that reflects the main focus of your study. Follow this with an abstract that provides a brief summary of your research objectives, methods, and expected outcomes. The introduction should set the context for your research, explaining the background and significance of your study. Make sure to include a literature review that highlights existing research and identifies gaps your study aims to fill. Finally, outline your research design, detailing the methods and procedures you will use to collect and analyze data.

Including a Literature Review

A comprehensive literature review is crucial for situating your research within the existing body of knowledge. Begin by gathering relevant sources from academic journals, books, and other credible publications. Summarize and synthesize these sources to show how they relate to your research question. Highlight any gaps or inconsistencies in the current literature that your study will address. This section not only demonstrates your understanding of the field but also justifies the need for your research.

Describing the Research Design

The research design section should provide a detailed plan of how you will conduct your study. Start by explaining whether you will use qualitative, quantitative, or mixed methods. Describe the data collection tools you will use, such as surveys, interviews, or experiments. Outline your sampling methods and criteria for selecting participants or data sources. Finally, detail your data analysis techniques, explaining how you will interpret the results to answer your research question. This section should be thorough enough to convince reviewers that your methodology is sound and feasible.

Implementing the Research Project

Collecting data.

Once your research plan is in place, the next step is to start collecting data. This involves gathering the information you need to answer your research questions . Make sure to use the data collection tools you selected during your planning phase. Accurate data collection is crucial for the success of your project.

Analyzing Results

After collecting your data, the next step is to analyze it. This means looking for patterns, trends, and insights that will help you answer your research questions. Use the data analysis techniques you planned earlier. Remember, the goal is to make sense of the data and draw meaningful conclusions.

Adjusting the Plan as Needed

As you collect and analyze data, you might find that some parts of your plan need to be adjusted. This is normal and part of the research process. Be flexible and ready to make changes to your methodology or data collection methods if necessary. Staying adaptable will help you overcome any challenges that arise.

Presenting Your Findings

Organizing the presentation.

When presenting your research findings, it's crucial to structure your presentation logically. Start with an introduction that outlines the purpose of your research and the main questions you aimed to answer. Follow this with a summary of your methodology, highlighting the key methods used for data collection and analysis. Ensure your findings are presented clearly and concisely , using tables and graphs where appropriate to illustrate your points.

Engaging the Audience

To keep your audience engaged, use a mix of visual aids and verbal explanations. Interactive elements like Q&A sessions or live demonstrations can also be effective. Make sure to explain the significance of your findings and how they contribute to the existing body of knowledge. This not only keeps the audience interested but also underscores the importance of your work.

Handling Questions and Feedback

Be prepared to handle questions and feedback from your audience. This is an opportunity to clarify any doubts and to demonstrate your deep understanding of the subject. Listen carefully to the questions, and take your time to provide thoughtful and well-reasoned answers. This will not only help in addressing any concerns but also in reinforcing the credibility of your research.

Sharing your research results is a crucial step in your academic journey. It can be tough, but you don't have to do it alone. Our Thesis Action Plan is here to guide you through every step. Ready to make your thesis writing stress-free? Visit our website now and claim your special offer!

In summary, starting a research project can seem overwhelming, but breaking it down into clear, manageable steps can make the process much more approachable. By carefully defining your research topic, engaging with stakeholders, crafting a precise research statement, and establishing clear goals and methodologies, you set a strong foundation for your project. Remember, a well-organized plan not only helps you manage your time and resources effectively but also enhances the credibility and impact of your research. As you embark on your research journey, keep these steps in mind to navigate the process smoothly and achieve your academic goals.

Frequently Asked Questions

What is a research project.

A research project is a detailed study on a specific topic. It involves gathering information, analyzing data, and presenting findings to answer a particular question or solve a problem.

How do I choose a good research topic?

Pick a topic that interests you and has plenty of resources available. Make sure it aligns with your assignment guidelines and is neither too broad nor too narrow.

Why is it important to define the research subject?

Defining the research subject helps you stay focused and organized. It ensures that you have a clear direction and don't get lost in too many ideas.

Who are stakeholders in a research project?

Stakeholders are people who have an interest in your research. They can include funders, academic supervisors, or anyone affected by your study.

What is a research statement?

A research statement is a clear and concise description of the main question or problem your research aims to address.

What are research goals?

Research goals are the specific objectives you aim to achieve with your study. They guide your research and help you stay focused on your main question.

How do I choose the right methodology for my research?

Choosing the right methodology involves deciding how you will collect and analyze data. Consider whether you need qualitative or quantitative data and choose tools and techniques that best suit your study.

What should be included in a research proposal?

A research proposal should include the research subject, a literature review, research questions, methodology, and a timeline. It outlines what you plan to study and how you will do it.

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Research Methodologies

What are research designs?
What are research methodologies?

What are research methods?

Quantitative research methods, qualitative research methods, mixed method approach, selecting the best research method.

Additional Sources

Research methods are different from research methodologies because they are the ways in which you will collect the data for your research project. The best method for your project largely depends on your topic, the type of data you will need, and the people or items from which you will be collecting data. The following boxes below contain a list of quantitative, qualitative, and mixed research methods.

Closed-ended questionnaires/survey: These types of questionnaires or surveys are like "multiple choice" tests, where participants must select from a list of premade answers. According to the content of the question, they must select the one that they agree with the most. This approach is the simplest form of quantitative research because the data is easy to combine and quantify.
Structured interviews: These are a common research method in market research because the data can be quantified. They are strictly designed for little "wiggle room" in the interview process so that the data will not be skewed. You can conduct structured interviews in-person, online, or over the phone (Dawson, 2019).

Constructing Questionnaires

When constructing your questions for a survey or questionnaire, there are things you can do to ensure that your questions are accurate and easy to understand (Dawson, 2019):

Keep the questions brief and simple.
Eliminate any potential bias from your questions. Make sure that they do not word things in a way that favor one perspective over another.
If your topic is very sensitive, you may want to ask indirect questions rather than direct ones. This prevents participants from being intimidated and becoming unwilling to share their true responses.
If you are using a closed-ended question, try to offer every possible answer that a participant could give to that question.
Do not ask questions that assume something of the participant. The question "How often do you exercise?" assumes that the participant exercises (when they may not), so you would want to include a question that asks if they exercise at all before asking them how often.
Try and keep the questionnaire as short as possible. The longer a questionnaire takes, the more likely the participant will not complete it or get too tired to put truthful answers.
Promise confidentiality to your participants at the beginning of the questionnaire.

Quantitative Research Measures

When you are considering a quantitative approach to your research, you need to identify why types of measures you will use in your study. This will determine what type of numbers you will be using to collect your data. There are four levels of measurement:

Nominal: These are numbers where the order of the numbers do not matter. They aim to identify separate information. One example is collecting zip codes from research participants. The order of the numbers does not matter, but the series of numbers in each zip code indicate different information (Adamson and Prion, 2013).
Ordinal: Also known as rankings because the order of these numbers matter. This is when items are given a specific rank according to specific criteria. A common example of ordinal measurements include ranking-based questionnaires, where participants are asked to rank items from least favorite to most favorite. Another common example is a pain scale, where a patient is asked to rank their pain on a scale from 1 to 10 (Adamson and Prion, 2013).
Interval: This is when the data are ordered and the distance between the numbers matters to the researcher (Adamson and Prion, 2013). The distance between each number is the same. An example of interval data is test grades.
Ratio: This is when the data are ordered and have a consistent distance between numbers, but has a "zero point." This means that there could be a measurement of zero of whatever you are measuring in your study (Adamson and Prion, 2013). An example of ratio data is measuring the height of something because the "zero point" remains constant in all measurements. The height of something could also be zero.

Focus Groups

This is when a select group of people gather to talk about a particular topic. They can also be called discussion groups or group interviews (Dawson, 2019). They are usually lead by a moderator to help guide the discussion and ask certain questions. It is critical that a moderator allows everyone in the group to get a chance to speak so that no one dominates the discussion. The data that are gathered from focus groups tend to be thoughts, opinions, and perspectives about an issue.

Advantages of Focus Groups

Only requires one meeting to get different types of responses.
Less researcher bias due to participants being able to speak openly.
Helps participants overcome insecurities or fears about a topic.
The researcher can also consider the impact of participant interaction.

Disadvantages of Focus Groups

Participants may feel uncomfortable to speak in front of an audience, especially if the topic is sensitive or controversial.
Since participation is voluntary, not every participant may contribute equally to the discussion.
Participants may impact what others say or think.
A researcher may feel intimidated by running a focus group on their own.
A researcher may need extra funds/resources to provide a safe space to host the focus group.
Because the data is collective, it may be difficult to determine a participant's individual thoughts about the research topic.

Observation

There are two ways to conduct research observations:

Direct Observation: The researcher observes a participant in an environment. The researcher often takes notes or uses technology to gather data, such as a voice recorder or video camera. The researcher does not interact or interfere with the participants. This approach is often used in psychology and health studies (Dawson, 2019).
Participant Observation: The researcher interacts directly with the participants to get a better understanding of the research topic. This is a common research method when trying to understand another culture or community. It is important to decide if you will conduct a covert (participants do not know they are part of the research) or overt (participants know the researcher is observing them) observation because it can be unethical in some situations (Dawson, 2019).

Open-Ended Questionnaires

These types of questionnaires are the opposite of "multiple choice" questionnaires because the answer boxes are left open for the participant to complete. This means that participants can write short or extended answers to the questions. Upon gathering the responses, researchers will often "quantify" the data by organizing the responses into different categories. This can be time consuming because the researcher needs to read all responses carefully.

Semi-structured Interviews

This is the most common type of interview where researchers aim to get specific information so they can compare it to other interview data. This requires asking the same questions for each interview, but keeping their responses flexible. This means including follow-up questions if a subject answers a certain way. Interview schedules are commonly used to aid the interviewers, which list topics or questions that will be discussed at each interview (Dawson, 2019).

Theoretical Analysis

Often used for nonhuman research, theoretical analysis is a qualitative approach where the researcher applies a theoretical framework to analyze something about their topic. A theoretical framework gives the researcher a specific "lens" to view the topic and think about it critically. it also serves as context to guide the entire study. This is a popular research method for analyzing works of literature, films, and other forms of media. You can implement more than one theoretical framework with this method, as many theories complement one another.

Common theoretical frameworks for qualitative research are (Grant and Osanloo, 2014):

Behavioral theory
Change theory
Cognitive theory
Content analysis
Cross-sectional analysis
Developmental theory
Feminist theory
Gender theory
Marxist theory
Queer theory
Systems theory
Transformational theory

Unstructured Interviews

These are in-depth interviews where the researcher tries to understand an interviewee's perspective on a situation or issue. They are sometimes called life history interviews. It is important not to bombard the interviewee with too many questions so they can freely disclose their thoughts (Dawson, 2019).

Open-ended and closed-ended questionnaires: This approach means implementing elements of both questionnaire types into your data collection. Participants may answer some questions with premade answers and write their own answers to other questions. The advantage to this method is that you benefit from both types of data collection to get a broader understanding of you participants. However, you must think carefully about how you will analyze this data to arrive at a conclusion.

Other mixed method approaches that incorporate quantitative and qualitative research methods depend heavily on the research topic. It is strongly recommended that you collaborate with your academic advisor before finalizing a mixed method approach.

How do you determine which research method would be best for your proposal? This heavily depends on your research objective. According to Dawson (2019), there are several questions to ask yourself when determining the best research method for your project:

Are you good with numbers and mathematics?
Would you be interested in conducting interviews with human subjects?
Would you enjoy creating a questionnaire for participants to complete?
Do you prefer written communication or face-to-face interaction?
What skills or experiences do you have that might help you with your research? Do you have any experiences from past research projects that can help with this one?
How much time do you have to complete the research? Some methods take longer to collect data than others.
What is your budget? Do you have adequate funding to conduct the research in the method you want?
How much data do you need? Some research topics need only a small amount of data while others may need significantly larger amounts.
What is the purpose of your research? This can provide a good indicator as to what research method will be most appropriate.
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Next: Additional Sources >>
Last Updated: Aug 2, 2022 2:36 PM
URL: https://library.tiffin.edu/researchmethodologies

1000+ FREE Research Topics & Title Ideas

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If you’re struggling to get started, this step-by-step video tutorial will help you find the perfect research topic.

Research Topic FAQs

What (exactly) is a research topic.

A research topic is the subject of a research project or study – for example, a dissertation or thesis. A research topic typically takes the form of a problem to be solved, or a question to be answered.

A good research topic should be specific enough to allow for focused research and analysis. For example, if you are interested in studying the effects of climate change on agriculture, your research topic could focus on how rising temperatures have impacted crop yields in certain regions over time.

To learn more about the basics of developing a research topic, consider our free research topic ideation webinar.

What constitutes a good research topic?

A strong research topic comprises three important qualities : originality, value and feasibility.

Originality – a good topic explores an original area or takes a novel angle on an existing area of study.
Value – a strong research topic provides value and makes a contribution, either academically or practically.
Feasibility – a good research topic needs to be practical and manageable, given the resource constraints you face.

To learn more about what makes for a high-quality research topic, check out this post .

What's the difference between a research topic and research problem?

A research topic and a research problem are two distinct concepts that are often confused. A research topic is a broader label that indicates the focus of the study , while a research problem is an issue or gap in knowledge within the broader field that needs to be addressed.

To illustrate this distinction, consider a student who has chosen “teenage pregnancy in the United Kingdom” as their research topic. This research topic could encompass any number of issues related to teenage pregnancy such as causes, prevention strategies, health outcomes for mothers and babies, etc.

Within this broad category (the research topic) lies potential areas of inquiry that can be explored further – these become the research problems . For example:

What factors contribute to higher rates of teenage pregnancy in certain communities?
How do different types of parenting styles affect teen pregnancy rates?
What interventions have been successful in reducing teenage pregnancies?

Simply put, a key difference between a research topic and a research problem is scope ; the research topic provides an umbrella under which multiple questions can be asked, while the research problem focuses on one specific question or set of questions within that larger context.

How can I find potential research topics for my project?

There are many steps involved in the process of finding and choosing a high-quality research topic for a dissertation or thesis. We cover these steps in detail in this video (also accessible below).

How can I find quality sources for my research topic?

Finding quality sources is an essential step in the topic ideation process. To do this, you should start by researching scholarly journals, books, and other academic publications related to your topic. These sources can provide reliable information on a wide range of topics. Additionally, they may contain data or statistics that can help support your argument or conclusions.

Identifying Relevant Sources

When searching for relevant sources, it’s important to look beyond just published material; try using online databases such as Google Scholar or JSTOR to find articles from reputable journals that have been peer-reviewed by experts in the field.

You can also use search engines like Google or Bing to locate websites with useful information about your topic. However, be sure to evaluate any website before citing it as a source—look for evidence of authorship (such as an “About Us” page) and make sure the content is up-to-date and accurate before relying on it.

Evaluating Sources

Once you’ve identified potential sources for your research project, take some time to evaluate them thoroughly before deciding which ones will best serve your purpose. Consider factors such as author credibility (are they an expert in their field?), publication date (is the source current?), objectivity (does the author present both sides of an issue?) and relevance (how closely does this source relate to my specific topic?).

By researching the current literature on your topic, you can identify potential sources that will help to provide quality information. Once you’ve identified these sources, it’s time to look for a gap in the research and determine what new knowledge could be gained from further study.

How can I find a good research gap?

Finding a strong gap in the literature is an essential step when looking for potential research topics. We explain what research gaps are and how to find them in this post.

How should I evaluate potential research topics/ideas?

When evaluating potential research topics, it is important to consider the factors that make for a strong topic (we discussed these earlier). Specifically:

Originality
Feasibility

So, when you have a list of potential topics or ideas, assess each of them in terms of these three criteria. A good topic should take a unique angle, provide value (either to academia or practitioners), and be practical enough for you to pull off, given your limited resources.

Finally, you should also assess whether this project could lead to potential career opportunities such as internships or job offers down the line. Make sure that you are researching something that is relevant enough so that it can benefit your professional development in some way. Additionally, consider how each research topic aligns with your career goals and interests; researching something that you are passionate about can help keep motivation high throughout the process.

How can I assess the feasibility of a research topic?

When evaluating the feasibility and practicality of a research topic, it is important to consider several factors.

First, you should assess whether or not the research topic is within your area of competence. Of course, when you start out, you are not expected to be the world’s leading expert, but do should at least have some foundational knowledge.

Time commitment

When considering a research topic, you should think about how much time will be required for completion. Depending on your field of study, some topics may require more time than others due to their complexity or scope.

Additionally, if you plan on collaborating with other researchers or institutions in order to complete your project, additional considerations must be taken into account such as coordinating schedules and ensuring that all parties involved have adequate resources available.

Resources needed

It’s also critically important to consider what type of resources are necessary in order to conduct the research successfully. This includes physical materials such as lab equipment and chemicals but can also include intangible items like access to certain databases or software programs which may be necessary depending on the nature of your work. Additionally, if there are costs associated with obtaining these materials then this must also be factored into your evaluation process.

Potential risks

It’s important to consider the inherent potential risks for each potential research topic. These can include ethical risks (challenges getting ethical approval), data risks (not being able to access the data you’ll need), technical risks relating to the equipment you’ll use and funding risks (not securing the necessary financial back to undertake the research).

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Study Protocol
Open access
Published: 27 August 2024

Effect evaluation of outpatient long-term video EEGs for people with seizure disorders – study protocol of the ALVEEG project: a randomized controlled trial in Germany

Pauline Sarah Münchenberg ORCID: orcid.org/0000-0002-6184-2995 1 na1 ,
Ricarda Sophia Schulz ORCID: orcid.org/0009-0006-9725-7620 1 na1 ,
Kerstin Wainwright ORCID: orcid.org/0000-0002-0483-768X 1 ,
Imke Mayer ORCID: orcid.org/0000-0003-4936-5062 1 ,
Martin Holtkamp ORCID: orcid.org/0000-0003-2258-1670 2 ,
Christian Meisel ORCID: orcid.org/0000-0003-2984-5480 2 , 3 , 4 , 5 , 6 na2 ,
Tobias Kurth ORCID: orcid.org/0000-0001-7169-2620 1 na2 &

the ALVEEG Consortium

BMC Health Services Research volume 24 , Article number: 994 ( 2024 ) Cite this article

Metrics details

Epilepsy and other seizure disorders account for a high disease burden in Germany. As a timely diagnosis and accurate treatment are crucial, improving the management of these disorders is important. Outside of Germany, outpatient long-term video EEGs (ALVEEGs) have demonstrated the potential to support the diagnosis and management of epilepsy and other seizure disorders. This study aims to evaluate the implementation of ALVEEGs as a new diagnostic pathway in eastern parts of Germany to diagnose epilepsy and other seizure disorders and to assess if ALVEEGs are equally effective as the current inpatient-monitoring gold standard, which is currently only available at a limited number of specialized centers in Germany.

ALVEEG is a prospective, multicenter, randomized controlled equivalence trial, involving five epilepsy centers in the eastern states of Germany. Patients will be randomized into either intervention (IG) or control group (CG), using a permuted block randomization. The sample size targeted is 688 patients, continuously recruited over the trial. The IG will complete an ALVEEG in a home setting, including getting access to a smartphone app to document seizure activity. The CG will receive care as usual, i.e., inpatient long-term video-EEG monitoring. The primary outcome is the proportion of clinical questions being solved in the IG compared to the CG. Secondary outcomes include hospital stays, time until video EEG, time until diagnosis and result discussion, patients’ health status, quality of life and health competence, and number and form of epilepsy-related events and epileptiform activity. Alongside the trial, a process implementation and health economic evaluation will be conducted.

The extensive evaluation of this study, including an implementation and health economic evaluation, will provide valuable information for health policy decision-makers to optimize future delivery of neurological care to patients affected by epilepsy and other seizure disorders and on the uptake of ALVEEG into standard care in Germany.

Trial registration

German Clinical Trials Register (DRKS00032220), date registered: December 11, 2023.

Introduction

Background and rationale.

Epilepsy is one of the most common chronic neurological conditions worldwide, imposing a high burden of disease on people affected and on society [ 1 ]. In Germany, around 500,000 people are affected by epilepsy [ 2 ]. An accurate diagnosis of epilepsy and other seizure disorders, such as psychogenic non-epileptic seizures or syncopes, is crucial to avoid misdiagnoses and to create a correct treatment plan, leading to an improved quality of life (QoL) for people affected and preventing fatal seizures [ 3 ].

Therefore, equipping healthcare systems with the right tools to make a timely diagnosis is important to avoid a lack of healthcare services, especially in rural areas [ 4 ]. The current gold standard for diagnosing epilepsy and other seizure disorders is an inpatient long-term video-electroencephalogram (EEG) monitoring (VEM). However, inpatient monitoring is only available at limited specialized centers and is associated with significant time and work resources [ 5 ]. Further, there are still fewer neurologists and pediatric neurologists in the rural eastern parts of Germany, reflected by a higher number of epilepsy patients per neurologist, leading to a significant waiting time for inpatient long-term video EEGs [ 6 ]. To address these challenges, outpatient long-term video EEGs (ALVEEGs) have already been established in other countries [ 7 ]. The development of a new portable sensor technology, enhanced by innovative automated data analyses supported by artificial intelligence (AI), allows ALVEEGs in the patient’s home environment. This advancement facilitates faster and more accurate diagnoses in this setting. By aligning with the treatment gold standard of care, it helps preventing misdiagnoses and inappropriate treatment plans, thereby improving QoL of people affected by epilepsy and other seizure disorders [ 8 ].

As shown in a single-center feasibility study in Germany, ALVEEGs were well accepted by patients and clinicians. They may offer an equivalent way of diagnosing epilepsy and other seizure disorders in Germany [ 8 ].

The here presented study, funded by the German Innovations Fund of the Federal Joint Committee (G-BA), aims to evaluate if ALVEEGs in an outpatient setting as diagnostic pathways are equally effective as the current inpatient gold standard of VEM to diagnose epilepsy and other seizure disorders. If successful, barriers in diagnosis and treatment care may be resolved, and patients in Germany affected by these disorders may have better and more rapid access to adequate diagnostics and subsequent treatment initiation or optimization.

Study aim and objective

The aim of ALVEEG is to improve and optimize care of patients experiencing epilepsy and other seizure disorders in Germany by translating case and care management into the patient’s home environment by introducing a new standardized way of diagnosing epilepsy and optimizing disease management in the eastern states of Germany. The objectives of the evaluation are to (1) analyze the effects of ALVEEG on patient care compared to the current standard inpatient VEM, assessing patients who have had at least one seizure in the last 12 months or a diagnosis of epilepsy, (2) observe the implementation of project activities, and (3) conduct a health economic evaluation.

The presented study protocol follows the SPIRIT reporting standards [ 9 ] and is aligned with the reporting guidelines for randomized trials, i.e., CONSORT [ 10 ] and the TIDieR checklist [ 11 ] for intervention description and replication.

Trial design

ALVEEG is a prospective, multicenter, randomized controlled trial (RCT) with a project duration of 4 years. The study is designed as an equivalence trial, with a trial duration of 27 months and continuous patient recruitment.

Patients assigned to the control group (CG) receive care as usual, i.e., inpatient VEM, while those randomized to the intervention group (IG) undergo outpatient ALVEEG.

Study setting and eligibility criteria epilepsy centers

ALVEEG is conducted in cooperation with five epilepsy centers in the eastern states of Germany (Berlin, Brandenburg, Mecklenburg-West Pomerania, and Saxony). Eligible epilepsy centers had to (1) be led by neurologists/neuropediatrics/epileptologists, (2) meet the technical and spatial requirements for conducting long-term inpatient video EEGs, and (3) treat patients who are part of the statutory health system. Epilepsy centers were excluded if they (1) were located outside the catchment area, (2) did not meet the technical and spatial requirements, or (3) did not treat patients who are part of the statutory health system.

The following five epilepsy centers participate in the study: Charité – Universitätsmedizin Berlin, Epilepsy-Center Berlin-Brandenburg; Charité – Universitätsmedizin Berlin, Germany Epilepsy-Center for Children and Adolescents; University Hospital Greifswald; Epilepsy-Center Kleinwachau; and University Hospital Dresden.

Participating statutory health insurances are BARMER, DAK-Gesundheit and Techniker Krankenkasse (TK).

Eligibility criteria and patient recruitment

To be eligible to participate in ALVEEG, patients have to (1) have had at least one seizure in the last 12 months or a diagnosis of epilepsy, (2) have an indication 1–4 from OPS 1-210, (3) live in a household with access to at least 4G or faster, (4) be part of the German statutory health insurance system, and (5) present themselves at least at one of the participating epilepsy centers. Patients can only be included if they or their legal representative gave written informed consent. Given the open cohort design of the trial, patients will be continuously recruited by the participating epilepsy centers over the trial duration of 27 months.

Patients are excluded if they (1) have an epilepsy surgery indication (indication 5 from OPS 1-210), (2) present themselves with additional psychosocial needs such as consultation on occupational or driving issues, (3) are privately insured, self-paying patients, or (4) if they or their legal representative does not give informed consent.

In patients with an epilepsy surgery indication, ictal events require some acute neuropsychological testing performed by medical technicians. Therefore, these patients are excluded for medical reasons. Further, patients must have had at least one seizure in the last 12 months or an epilepsy diagnosis to use disease-specific questionnaires during the trial, e.g., the Quality Of Life In Epilepsy (QOLIE-10) questionnaire, to get better insights on seizures relevant for the included population.

Intervention

The IG will complete an ALVEEG at home, comprising a portable EEG- and electrocardiogram (ECG)-recorder and a mobile data station, including a camera and audio recorder. The ambulatory monitoring system is provided by a medical device company that develops, manufactures, and commercializes diagnostic technologies for brain monitoring applications. EEG data will be reviewed using a review and analysis software, which offers computer-assisted reviews of EEGs, supported by AI. Patients will also get access to the smartphone app Helpilepsy [ 12 ], a digital diary for the documentation of seizures and related factors throughout the study. Alternatively, patients can also choose to use a paper diary for documentation.

There will be four appointments in the IG at the participating centers. During the first appointment, the EEG and ECG electrodes will be fitted on the patient’s head and chest to measure brain and heart activity and are connected with a portable amplifier. The ALVEEG will take place in the patient’s home environment, recording EEG, ECG, video, and audio data for up to 6 days. Patients will be monitored throughout the study for possible adverse events (AE; e.g., skin irritations or mild rashes) that might occur, given the nature of the intervention. All AE will be recorded to inform future guidelines and use of ALVEEGs. Patients are also asked to document seizures via the app or the paper diary throughout the monitoring. After completing their ALVEEG, patients can either remove the electrodes themselves at home or they are removed in the clinic when patients return all devices at their second appointment. During the third appointment, results of the ALVEEG will be discussed, and the patient’s therapy and treatment plan will be amended accordingly. The patient will also get a medical findings report. The fourth and final appointment will take place three months after completing the VEM for the last follow-up and the final collection of study-related patient-reported outcome measures (PROMs).

Study outcomes

The outcomes of the study refer to the healthcare system (macro level), the institutional level (meso level) as well as the individual patient (micro level).

The primary outcome of ALVEEG is the proportion of clinical questions being solved in the IG compared to the CG. A clinical question is considered as solved if (1) a specified diagnosis is needed and provided via long-term video EEG, (2) treatment management needs to be defined and is provided via long-term video EEG, or (3) a specified diagnosis is needed, and treatment management needs to be defined according to findings of the long-term video EEG.

Secondary outcomes (see Table 1 ), include on the macro level: (1) number of hospital stays, (2) length of hospital stays, (3) inability to work (in days), and (4) number of video EEGs; on the meso level: (5) duration of waiting period for a video EEG (in days), (6) duration of waiting period for diagnosis and result discussion, (7) duration of diagnosis identification using AI, and (8) duration of long-term video EEG; and on the micro level: (9) number of diagnosis specifications, definition of treatment management and diagnosis specifications combined with treatment management, (10) number and form of epilepsy-related events and epileptiform activity, (11) QoL related to epilepsy, (12) QoL, (13) health status, (14) health competence, and (15) contentment, acceptance, and AE.

Participant timeline

Randomization of patients into either the IG or CG will take place in the participating epilepsy centers at baseline ( t0 ), after patients have given their informed consent. The treating neurologist will be informed about the patient’s group assignment, and all included patients are asked to complete REDCap (Research Electronic Data Capture) surveys on PROMs (IG and CG: EQ-5D-5L, EQ-5D-5L (VAS), as well as the QOLIE-10 and a subscale of the PESOS questionnaire). All questionnaires will be saved and managed in REDCap electronic data capture tools, hosted at the University of Nebraska Medical Center. REDCap is a secure, web-based application designed to support data capture for research studies [ 13 , 14 ].

After randomization, patients will receive either inpatient (CG) or outpatient (IG) long-term VEM, with patients in the IG being trained in how to use ALVEEG ( tSens ). They can also call at any time if problems occur during the monitoring at home ( tMon1-tMon2 ), and there will be a check-in on the first day of ALVEEG, led by a medical-technical assistant (MTA). Secondary outcome data will be assessed for both IG and CG throughout the study at different assessment time points (see Fig. 1 ). After the ALVEEG is completed ( tMon2 ), patients in the IG will return the equipment to the hospital ( tEA ). The ALVEEG data will be uploaded into the cloud provided by the medical device company and documented in REDCap ( tAP ). The patient’s practitioner will also get access to the monitoring results, which are evaluated by the neurologist for patients in the IG and CG ( tD2 ). After the evaluation of the monitoring is completed, the neurologist will discuss the results and care and treatment plan with the patient in both IG and CG ( tP1 ). Patients will additionally answer a survey on their acceptance, contentment, and AE during ALVEEG. The follow-up assessment will take place three months after the discussion of medical findings, with patients in both groups answering the PROM questions in REDCap again ( tP2 ).

Participant timeline throughout the course of the study

Data management, collection, and quality control

All surveys for neurologists, MTAs and patients will be conducted electronically via a tablet. The answers will be documented in REDCap, constituting the ALVEEG study database.

REDCap will be programmed using automatic plausibility checks and mandatory fields for data entry. Measures to inquire about missing data by the study personnel will be instituted.

Regular data consistency and plausibility checks will take place in cooperation with the evaluation team, which consequently will contribute to a better quality of documentation in the epilepsy centers. Technical training of the epilepsy centers and study personnel regarding the use of ALVEEG and its AI-supported diagnosis, as well as the documentation in REDCap, will take place prior to the start of the intervention. All questionnaires that were developed specifically for this study were piloted before the start of the intervention.

A data protection concept for the study has been accepted by the data protection officers in charge at the Charité – Universitätsmedizin Berlin. It comprises guidelines with respect to collecting data, data management, transfer, processing, and storage. Data originating from clinical care process and claims data of the participating health insurance companies (primary and secondary data) will be securely transferred from a data integration center (composited of the independent data trust agency (“Treuhandstelle”) at the Charité – Universitätsmedizin Berlin and a team for medical informatics at the Berlin Institute of Health) to the independent evaluating institution at the Charité – Universitätsmedizin Berlin where they will get analyzed and findings will be provided to the studies funding agency.

Statistical methods: sample size, recruitment and power calculations

The sample size calculation for the presented equivalence trial is based on the primary endpoint. After consultation with the clinical consortium partners, the proportion of resolved clinical cases in the CG is assumed to be 0.8 (80%). We expect to observe an equivalent rate of treatment successes in the IG, whereby (clinical) equivalence is defined within a margin of +/- 15% deviation from the rate in the CG. This corresponds to an equivalence interval of [0.68–0.92] ([68 − 92%]) for the proportion of clinical questions being solved. This margin is based on assumptions made by clinical experts within the consortium and is further supported by the results of international studies on the subject [ 15 ].

Based on a significance level of 0.05 and a power of (1-β) = 90%, applying two proportions z-test results in a sample size of 482 participants. Considering an expected dropout rate of about 30%, the sample size of the study amounts to 688 participants. In order to achieve this sample, an average of approximately five patients must be recruited per center and month.

For the secondary endpoints, a power of 0.83 was computed using a two-sided t-test for 550 patients, taking into account the latency period of the routine data from the participating health insurance funds.

According to estimations by the consortium partners and the involved health insurance companies, it is assumed that the aspired sample size can be achieved for all endpoints.

Sequence generation and randomization procedure

For ALVEEG, a permuted block randomization with block sizes of either 2 or 4 patients [ 16 ] was performed at the patient level prior to the start of the trial by an independent data analyst of the evaluation team. Each participating center was assigned its own randomization list.

Given the nature of the trial design, blinding the treating neurologist is impossible. After the patients or their legal representatives have given informed consent and the neurologist has discussed their further treatment strategy with them, patients will be aware of their group allocation.

Statistical methods

The primary analysis has the aim to evaluate the effect of ALVEEG based on the predefined primary endpoint, the proportion of cases being solved by the video EEG. Two one-sided z-tests will be performed, and a confidence interval will be determined based on the observed difference between IG and CG and interpreted using the predefined equivalence interval, analyzing the proportion of clinical questions being solved in the IG compared to the CG [ 17 ]. Point estimates of the intervention effect, together with the corresponding 95% confidence intervals, will be reported on the absolute and relative scale.

For the planned descriptive statistical analyses, mean values (standard deviation) for continuous normally distributed data, medians and interquartile ranges for non-normally distributed continuous data, and the proportions of frequencies for categorical data will be presented.

Depending on the relevant variables, various statistical test procedures and multivariable techniques will be applied in the context of secondary and sensitivity analyses to test the hypotheses within the context of inferential statistics. In principle, the inferential data analyses focus on differences between the IG and CG. For example, to test the difference in duration in days (e.g., waiting time until video EEG or length of in-hospital stay), we will perform a t-test for normal distributions or the Wilcoxson rank sum test for non-normally distributed data.

The entire statistical data analysis will be performed using the statistical software R [ 18 ] v4.2.1 (or higher).

Prior to data lock and the actual extraction of the data, a detailed statistical analysis plan, including additional information on ancillary analyses and the handling of missing data, will be developed.

Evaluation of the implementation of ALVEEG

To evaluate the implementation of ALVEEG, its delivery, further implementation and its generalizability, we will use the RE-AIM framework [ 19 ]. The RE-AIM framework facilitates assessing the benefits of innovative forms of care, while taking into account their successful implementation [ 20 ].

Therefore, the number of approached patients compared to those actually participating is measured to assess whether the intervention reaches the intended target population (REACH). The number of achieved treatment successes will also be recorded and evaluated accordingly (EFFECTIVENESS). In addition, we will examine the extent to which the included study sites participated in the intervention (ADOPTION) and the implementation of intervention activities according to protocol (IMPLEMENTATION). Furthermore, we will investigate the degree to which the intervention can be sustainably integrated into routine processes (MAINTENANCE).

Health economic evaluation

A health economic evaluation will be carried out alongside the trial, investigating whether the intervention is cost effective compared to standard care. The evaluation will be performed from a statutory health insurance perspective and will comprise a cost-utility as well as additional cost-effectiveness analyses. The outcome to be considered for the cost-utility analysis will be quality-adjusted life years (QALYs), calculated by data obtained from the EQ-5D-5L questionnaire under applying German population weights [ 21 ].

Additional emerging costs with relevance to the intervention will be considered compared to standard care (e.g., ALVEEG devices, staff education, etc.), as well as costs per patient stemming from health insurance data (e.g., number of hospitalizations, medications, travel expenses, etc.).

The shortage of inpatient VEM capacities for patients with epilepsy and other seizure disorders in Germany, in addition to the artificial environment of VEMs taking place in hospitals instead of the patient’s usual surroundings, requires better care and access for this population - especially in rural areas, where resources and neurological specialists are limited. As shown in previous studies from other countries, ALVEEGs allow a faster and more effective diagnosis and management of epilepsy and other seizure disorders [ 7 , 8 ].

We expect that results from this study will deliver insightful evidence on the effectiveness of ALVEEGs in diagnosis and management of epilepsy and other seizure disorders compared to the current inpatient gold standard - not only on the patient and clinical level but also with respect to the German statutory health care system. Further, we will be able to provide a more nuanced understanding of the intervention and its impact, as well as cost-utility and cost-effectiveness results, as we are evaluating different endpoints, while taking into account multiple outcomes and intervention-associated costs.

Nevertheless, there are some limitations to our study. As we collect data from a real-world clinical care setting, we expect missing data to occur, especially when it comes to self-reported information. Being aware of this, we will address this issue through the elaboration of statistical strategies to account for missing values for the different endpoints to be assessed. Further, as blinding of the treating neurologist and data analyst is not possible due to the nature of the trial design, potential bias cannot be ruled out. However, we do not expect any major impact, i.e., bias on the effects to be analyzed.

Finally, claims data from German statutory health insurances are subject to a waiting period for up to 9 months. Therefore, it will not be possible to analyze claims data from all included patients. Further, we will only be able to analyze claims data for patients who are part of the participating three statutory health insurances: BARMER, DAK-Gesundheit and TK. Although in total there are 96 statutory health insurances in Germany, the insurance companies participating in this trial are part of the biggest German statutory health insurances [ 22 ]. Hence, we believe that patients for whom claims data will be available are representative of the entire ALVEEG study population.

One major strength of the study is its pragmatic nature, allowing to generate real-world evidence on the use of ALVEEGs in clinical care processes as a new diagnostic pathway in epilepsy centers in Germany. Although we do not expect any possible harm for participating patients, we made sure that potentially occurring AE during the trial will be continuously monitored and patients will have access to professional support throughout the trial.

The evaluation of this study will provide valuable information for decision makers to optimize future delivery of neurological care to patients affected by epilepsy and other seizure disorders, and to guide a possible scale-up of ALVEEGs in Germany. Further, conducting an implementation and health economic evaluation alongside this trial will provide essential information for key stakeholders in the German healthcare system.

Trial status

Patient recruitment started in April 2024. In June 2026, the last patient will be recruited. Results are expected in 2027.

Availability of data and materials

No datasets were generated or analyzed during the current study.

Abbreviations

Adverse events

Artificial intelligence

Outpatient long-term video EEG

Control group

Electrocardiogram

Electroencephalogram

European quality of life questionnaire – 5 dimensions

German Innovations Fund of the Federal Joint Committee

Incremental cost-effectiveness ratio

Intervention group

Medical-technical assistant

Operation and procedure classification system

Performance, Socio-demographic aspects, Subjective evaluation Fragebogen

Patient reported outcome measures

Quality-adjusted life years

Quality of life

Quality of life in epilepsy

Randomized controlled trial

Research Electronic Data Capture

Techniker Krankenkasse

Visual analogue scale

Video-EEG monitoring

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Acknowledgements

We would like to thank the ALVEEG Consortium for their ongoing support and input in realizing the ALVEEG study (see Additional file 1).

Open Access funding enabled and organized by Projekt DEAL. Funding was provided via the grant program “new forms of health care” (grant no. 01NVF22101) by the G-BA ( https://www.g-ba.de/english ). There has been a competitive grant application for ALVEEG and a peer review process by the funding agency prior to financing. To account for public funding, the funding body’s role is to review and oversee the project. There was no involvement of the funder in preparing, reviewing, approving, or submitting this study protocol for publication.

Open Access funding enabled and organized by Projekt DEAL.

Author information

Pauline Sarah Münchenberg and Ricarda Sophia Schulz shared first authorship.

Christian Meisel and Tobias Kurth shared senior authorship.

Authors and Affiliations

Institute of Public Health, Charité – Universitätsmedizin Berlin, Berlin, Germany

Pauline Sarah Münchenberg, Ricarda Sophia Schulz, Kerstin Wainwright, Imke Mayer & Tobias Kurth

Department of Neurology with Experimental Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany

Martin Holtkamp & Christian Meisel

Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany

Christian Meisel

Berlin Institute of Health, Charité – Universitätsmedizin Berlin, Berlin, Berlin, Germany

NeuroCure Cluster of Excellence, Charité – Universitätsmedizin Berlin, Berlin, Germany

Bernstein Center for Computational Neuroscience, Berlin, Germany

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Pauline Sarah Münchenberg
, Ricarda Sophia Schulz
, Tobias Kurth
, Christian Meisel
, Martin Holtkamp
, Bernd Vorderwülbecke
, Mirja Steinbrenner
, Matthias Endres
, Claudia Gorski
, Fabian Prasser
, Angela Kaindl
, Bernhard Weschke
, Cornelia Potratz
, Pascal Fenske
, Felix von Podewils
, Astrid Bertsche
, Sarah Mai Viebahn
, Bernadette Gaida
, Norbert Utzig
, Juliane Schulz
, Thomas Mayer
, Peter Hopp
, Nils Holert
, Miriam Wienecke
, Georg Leonhardt
, Peggy Müller
, Petra Knobelsdorf
, Antke Wolter
, Anne Klinker
, Mara Brandebusemeyer
, Uwe Nussbaum
& Jannis Seemann

Contributions

The principal investigator of the ALVEEG consortium is CM. For the program evaluation, TK takes the role of the principal investigator. RS, KW, IM, MH, CM, and TK were mainly involved in conceptualizing the evaluation of the study. PM and RS jointly wrote the first draft of the protocol and created the tables and figures presented. All listed authors provided important critical comments on the draft and approved the final version of the manuscript. PM and RS share first authorship and CM and TK share senior authorship.

Corresponding author

Correspondence to Pauline Sarah Münchenberg .

Ethics declarations

Ethics approval and consent to participate.

The ALVEEG study was approved by the Ethics Committee of the Charité – Universitätsmedizin Berlin, Berlin, Germany (approval no. EA2/227/23). In case of any changes to the presented study protocol, a re-approval of the Ethics Committee is required. All patients participating in the study will have to provide written informed consent, including the publication of results in peer-reviewed journals. Furthermore, patients and caretakers will receive information on how to handle seizures that might occur during the ALVEEG before the beginning of the study (e.g., https://www.epilepsie-vereinigung.de/erste-hilfe/ ) .

Data transfer protocols have been monitored by the local data protection officers of the participating institutions and comply with the EU General Data Protection Regulation (GDPR), including the data for the evaluation, which will be anonymized. The analysis of ALVEEG is partially based on claims data. Approval by the supervisory authority of the participating health insurances is needed to release the claims data. ALVEEG will follow the Declaration of Helsinki in its current version, the guidelines of the International Conference on Harmonization of Good Clinical Practice, and applicable national regulations. In case of essential modifications to the current protocol, the funder, all relevant parties of the project, the trial registry, and journals will be informed. After the evaluation of the study data, the results will be reported to all project stakeholders and the funding agency involved by means of a formal report. Additionally, study findings are intended to be published in peer-reviewed scientific journals. Authors and collaborators will be engaged in the composition of manuscripts, press releases, and other formats of publication. It is also envisaged to disseminate the results at conferences and on the project’s website.

Consent for publication

Not applicable.

Competing interests

During the last three years, MH has received personal fees from Angelini, Bial, Desitin, Eisai, Jazz Pharma, and UCB. Outside of the submitted work, TK reports to have received research grants from the Bundesministerium für Gesundheit (BMG – Federal Ministry of Health, Germany). He further has received personal compensation from Eli Lilly, the BMJ, and Frontiers. All the remaining authors report no competing interests.

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Münchenberg, P.S., Schulz, R.S., Wainwright, K. et al. Effect evaluation of outpatient long-term video EEGs for people with seizure disorders – study protocol of the ALVEEG project: a randomized controlled trial in Germany. BMC Health Serv Res 24 , 994 (2024). https://doi.org/10.1186/s12913-024-11076-y

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DOI : https://doi.org/10.1186/s12913-024-11076-y

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10 Research Question Examples to Guide Your Research Project

10 Research Question Examples to Guide your Research Project

Published on October 30, 2022 by Shona McCombes . Revised on October 19, 2023.

The research question is one of the most important parts of your research paper , thesis or dissertation . It’s important to spend some time assessing and refining your question before you get started.

The exact form of your question will depend on a few things, such as the length of your project, the type of research you’re conducting, the topic , and the research problem . However, all research questions should be focused, specific, and relevant to a timely social or scholarly issue.

Once you’ve read our guide on how to write a research question , you can use these examples to craft your own.

Research question	Explanation
	The first question is not enough. The second question is more , using .
	Starting with “why” often means that your question is not enough: there are too many possible answers. By targeting just one aspect of the problem, the second question offers a clear path for research.
	The first question is too broad and subjective: there’s no clear criteria for what counts as “better.” The second question is much more . It uses clearly defined terms and narrows its focus to a specific population.
	It is generally not for academic research to answer broad normative questions. The second question is more specific, aiming to gain an understanding of possible solutions in order to make informed recommendations.
	The first question is too simple: it can be answered with a simple yes or no. The second question is , requiring in-depth investigation and the development of an original argument.
	The first question is too broad and not very . The second question identifies an underexplored aspect of the topic that requires investigation of various to answer.
	The first question is not enough: it tries to address two different (the quality of sexual health services and LGBT support services). Even though the two issues are related, it’s not clear how the research will bring them together. The second integrates the two problems into one focused, specific question.
	The first question is too simple, asking for a straightforward fact that can be easily found online. The second is a more question that requires and detailed discussion to answer.
? dealt with the theme of racism through casting, staging, and allusion to contemporary events?	The first question is not — it would be very difficult to contribute anything new. The second question takes a specific angle to make an original argument, and has more relevance to current social concerns and debates.
	The first question asks for a ready-made solution, and is not . The second question is a clearer comparative question, but note that it may not be practically . For a smaller research project or thesis, it could be narrowed down further to focus on the effectiveness of drunk driving laws in just one or two countries.

Note that the design of your research question can depend on what method you are pursuing. Here are a few options for qualitative, quantitative, and statistical research questions.

Type of research	Example question
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Factors affecting contract compliance and execution of public works in the executing unit: special project huallaga central and bajo mayo in peru, 2022.

1. Introduction

2. materials and methods, 3.1. identification of factors, 3.1.1. determination of factors, 3.1.2. relative import (rii).

		Main Factors Identified from the Literature Review
Dimension	Factor Identified	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	Frequency	RII
Time	Poor time management									x	x					x						x		x							x				6	3.947368421
	Inadequate Project Management								x		x	x						x			x						x						x		7	4.605263158
	Excessive bureaucratic procedures	x		x					x								x										x	x				x			7	4.605263158
	Lack of implementation of practical tools	x	x																									x							3	1.973684211
	Political interference		x				x													x			x			x									5	3.289473684
	Characteristics of the project													x		x			x										x		x			x	6	3.947368421
	Land conditions			x		x					x														x										4	2.631578947
	Poor contract management								x				x				x								x		x	x							6	3.947368421
	Changes of government						x			x					x			x					x		x						x		x		8	5.263157895
	Leadership Skills of Project Managers		x	x					x			x			x		x			x			x								x				9	5.921052632
	Poor monitoring of project execution	x		x	x						x			x					x			x												x	8	5.263157895
	Delays in the technical approval process of the project	x								x						x		x						x						x					6	3.947368421
	Conflicts between consultant of design and execution of the Work														x								x				x								3	1.973684211
	Delay in approval of substantial design changes																								x				x				x	x	4	2.631578947
	Delay in inspection of evidence						x		x								x									x					x				5	3.289473684
	Slowness in making important decisions			x								x		x						x		x			x			x				x			8	5.263157895
	Interference by the landowner	x				x				x								x									x			x	x			x	8	5.263157895
	Poor communication and coordination		x					x							x						x					x			x			x			7	4.605263158
	Suspension of deadlines and unjustified delays				x								x			x		x		x				x	x			x			x				9	5.921052632
	Control and restriction of site traffic					x											x								x									x	4	2.631578947
	Shortages of workers on site	x	x		x								x													x			x			x			7	4.605263158
	Excessive planning time by the contractor		x	x					x	x					x	x			x						x										8	5.263157895
	Changes in Laws and Regulations					x							x									x								x			x		5	3.289473684
	Unfavorable climatological factors		x					x						x				x			x		x	x		x		x							9	5.921052632

		Main Factors Identified from the Literature Review
Dimension	Factor Identified	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	Frequency	RII
Cost	Lack of experience in project budget execution					x			x	x					x				x			x	x					x	x			x	x		11	6.832298137
	Low levels of productivity				x	x						x		x					x						x		x		x					x	9	5.590062112
	Social conflicts					x	x	x						x	x	x			x	x								x		x	x				11	6.832298137
	Exceptionally low offers		x					x				x	x	x							x				x	x	x				x				10	6.211180124
	Late payments	x														x															x	x			4	2.48447205
	Lack of sustainability of the project				x											x														x				x	4	2.48447205
	Lack of political will to finance the Project			x		x		x									x		x		x								x		x				8	4.968944099
	Inaccurate estimates				x								x		x											x		x							5	3.105590062
	Poor technical and economic evaluation of financial resources	x					x													x										x					4	2.48447205
	Project size				x				x			x	x									x			x	x						x			8	4.968944099
	Inappropriate allocation of resources		x			x					x		x	x	x				x					x		x	x	x							11	6.832298137
	Efficient public-private partnership				x			x			x				x						x			x				x			x			x	9	5.590062112
	Commitment of technical approval authorities						x			x										x			x							x			x		6	3.726708075
	Delays in the adaptation and installation of the workplace					x						x							x						x				x						5	3.105590062
	Poor maintenance management of equipment and machinery										x		x		x									x		x		x							6	3.726708075
	Lack of safety precautions											x													x				x		x				4	2.48447205
	Poor performance in the area of tenders and contracts		x		x									x													x								4	2.48447205
	Material price fluctuation							x		x		x				x					x		x		x						x		x		9	5.590062112
	Unforeseen conditions on site related to public services	x				x							x					x	x							x									6	3.726708075
	Low level of operational prowess	x	x						x		x	x			x			x				x			x			x				x			11	6.832298137
	Delinquency of suppliers and subcontractors and cash flows		x	x	x						x													x											5	3.105590062
	High administrative costs related to the Work				x				x	x	x											x	x	x								x	x	x	10	6.211180124

		Main Factors Identified from the Literature Review.
Dimension	Factor Identified	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	Frequency	RII
Quality	Poor construction management					x				x									x					x									x		5	3.968253968
	Frequent errors in the construction process					x									x			x											x			x			5	3.968253968
	Sudden changes in the construction process					x	x											x		x	x											x		x	7	5.555555556
	Inefficient project management and control	x									x														x										3	2.380952381
	Poor quality of monitoring effect								x		x			x				x					x		x			x				x			8	6.349206349
	Commitments and obligations on the part of the Project Manager	x	x					x		x	x			x	x	x												x		x					10	7.936507937
	Experience and Trajectory of those responsible for the Works				x		x									x					x									x					5	3.968253968
	Commitment and participation of those responsible for the Work						x	x	x		x										x	x	x		x										8	6.349206349
	Little definition of quality				x	x	x				x		x							x	x				x		x							x	10	7.936507937
	Detail of drawings in unclear and coherent plans								x			x		x		x							x			x		x		x					8	6.349206349
	Obsolete machinery and equipment								x	x													x	x											4	3.174603175
	Delay in the delivery of materials on site														x				x										x				x		4	3.174603175
	Shortage of skilled labor					x		x					x				x					x					x				x				7	5.555555556
	Shortage of managers and staff with project experience									x				x										x				x							4	3.174603175
	Delay of final inspection of works on site	x			x	x				x						x		x						x						x		x			9	7.142857143
	Ignorance of safety regulations			x		x	x	x							x				x		x	x							x				x		10	7.936507937
	Low motivation/morale of Project workers			x				x			x											x			x										5	3.968253968
	Poor maintenance scheduling of machinery and equipment		x										x							x							x							x	5	3.968253968
	Abandonment of Work				x																								x		x				3	2.380952381
	Disputes between technical staff	x				x			x														x												4	3.174603175

3.1.3. Determination of the Most Significant Factors

3.2. pilot test, reliability analysis (cronbach’s alpha) for risk factors, 3.3. expert judgement, 3.4. case study: determination of incidence factors—case study on the executing unit of special projects huallaga central and bajo mayo, 3.4.1. identification of impact projects.

Changes of government.
Poor monitoring of project implementation.
Suspension of deadlines and unjustified delays.
Excessive planning time on the part of the contractor.
Improper allocation of resources.
High administrative costs related to the work.
Detail of plans in unclear and coherent plans.

3.4.2. Impact of Time, Cost, and Quality Dimensions on PEHCBM

4. discussion, 5. conclusions, author contributions, data availability statement, conflicts of interest.

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Click here to enlarge figure

Category	Factors	Frequency	Relative Value Index/RII
Cost	Lack of experience in project budget execution	11	6.832
	Social conflicts	11	6.832
	Exceptionally low offers	10	6.211
	Inappropriate allocation of resources	11	6.832
	Low level of operational prowess	11	6.832
	High administrative costs related to the work	10	6.211

Category	Factors	Frequency	Relative Value Index/RII
Time	Changes of government	8	5.263
	Leadership skills of project managers	9	5.921
	Poor monitoring of project execution	8	5.263
	Slowness in making important decisions	8	5.263
	Interference by the landowner	8	5.263
	Suspension of deadlines and unjustified delays	9	5.921
	Excessive planning time by the contractor	8	5.263
	Unfavorable climatological factors	9	5.921

Category	Factors	Frequency	Relative Value Index/RII
Quality	Poor quality of monitoring effect	8	6.349206349
	Commitments and obligations on the part of the Project Manager	10	7.936507937
	Commitment and participation of those responsible for the work	8	6.349206349
	Little definition of quality	10	7.936507937
	Detail of drawings in unclear and coherent plans	8	6.349206349
	Delay of final inspection of works on site	9	7.142857143
	Ignorance of safety regulations	10	7.936507937

		N	%
Cases	Valid	25	100.0
	Excluded	0	0.0
	Total	25	100.0
List deletion is based on all procedural variables.

Cronbach’s Alpha	N of Elements
0.878	31

Reliability Statistics
Cronbach’s alpha	Part 1	Value	0.838
	Part 1	N of items	16a
	Part 2	Value	0.762
	Part 2	N of items	15b
	Total N of items		31
Correlation between forms			0.699
Spearman–Brown coefficient	Equal length		0.822
Spearman–Brown coefficient	Unequal length		0.823
Guttman’s coefficient of two halves			0.821

Dimensions	Org.	Experience (Years)	Number of Interviewees
Expert in technical project studies	Public	10–15	5
Expert in the execution of works	Private	08–12	5
Expert in construction supervision	Public/Private	10–15	5
Contract administration expert	Public	8–10	5
Specialist in works liquidation	Public/Private	8–10	5

			Incidence Factors	Performance Contracts
Spearman’s rho	Incidence factors	Correlation coefficient	1.000	0.521 **
		Sig. (bilateral)	.	0.008
		N	25	25
	Performance contracts	Correlation coefficient	0.521 **	1.000
		Sig. (bilateral)	0.008	.
		N	25	25

Item	C.U.I.	Public Investment Project (PIP)
1	2234509	Improvement of Health Services at the Hospital Tocache, province de Tocache—San Martín region.
2	2114066	Improvement of the Services of the Hospital II-2-Tarapoto, province and region San Martin.
3	2234505	Improvement of Health Services and Health Hospital Bellavista, province de Bellavista—region San Martin.
4	2234506	Improvement of Health Services in the Saposoa Health Establishment, province of Huallaga-San Martin region.
5	2234510	Improvement of Health Services in the San José de Sisa Health Establishment, El Dorado province, San Martin region.
6	2234507	Improvement of Health Services in the Picota Health Establishment, Picota province, San Martin region.
7	2134084	Construction of the Ponaza Irrigation System.
8	2113014	Improvement of the Drinking Water Supply and Sewerage System of the Saposoa quality.
9	2177562	Road Network 01: Road Improvement; SM-107: Tingo de Pona-za-Shamboyacu; SM-108: Nvo. Lima-Barranca; SM-118; Sm-119: Bel-lavista-Alto Cuñumbuza; SM-120: Pte. Sta Martha-Huicungo and SM-103: Piscoyaco-El Dorado, Prov. From Huallaga, M. Cáceres, Picota and Bellavista—San Martin.
10	2177548	Road Network 02: Improvement of the Departmental Highway, Route SM-111, Emp. PE-5N (Tocache)—Nva. Esperanza—Jorge Chávez—Palma de Espino—Emp. PE-12A (Dv. Palma de Espino), districts of Tocache and Uchiza, province of Tocache-San Martin Martha-Huicungo and SM-103: Piscoyaco-El Dorado, Prov. de Huallaga, M. Cáceres, Picota and Bellavista—San Martin.
11	2177558	Road Network 02: Improvement of the Departmental Highway Route SM-110 Section Emp PE-5N (Dv. Yacusisa)—Las Palmas—Calabaza—Tambo de Paja—Metal, districts of Tocache and Shunte, province of Tocache—San Martín.
12	2177561	Road Network 02: Mej. OF TRACKS DEP. SM 101, EMP. PE-5N-Roque; SM 116, Emp. PE-5N (Pte. Cumbaza)-Dv. San Ant. de C.-San Roque de C.; SM 115, Emp. SM 104 (Lamas)-Pamashto and SM 100, San Martin de Alao-Emp. SM -102 (San José De Sisa), Prov. de Lamas, El Dorado and San Martin.
13	2177559	Road Network 02: Improvement of the Departmental Highway: Route SM-105 Emp. PE-5N (Pongo de Caynarachi)—Barranquita—Pelejo—Papaplaya and Route SM 106, Section: Pongo Isla—Yarina—Emp. SM-105 (Nuevo San Juan), provinces of San Martin and Lamas—San Martin

Factors	PIP 1	PIP 2	PIP 3	PIP 4	PIP 5	PIP 6	PIP 7	PIP 8	PIP 9	PIP 10	PIP 11	PIP 12	PIP 13
Changes of government	x	x	x	x	x		x	x					x
Leadership skills of project managers						x				x	x	x
Poor monitoring of project execution	x		x	x	x				x
Slowness in making important decisions		x					x			x	x		x
Interference by the landowner							x	x
Suspension of deadlines and unjustified delays	x	x	x	x	x
Excessive planning time by the contractor	x	x	x	x					x	x	x
Unfavorable climatological factors							x	x	x				x
Lack of experience in project budget execution										x	x	x
Social conflicts							x	x
Exceptionally low offers											x	x
Inappropriate allocation of resources	x	x	x	x	x								x
Low level of operational prowess							x	x	x
High administrative costs related to the work	x	x	x	x	x						x	x
Poor quality of monitoring effect						x				x
Commitments and obligations on the part of the project manager							x			x	x		x
Commitment and participation of those responsible for the work							x			x	x		x
Little definition of quality								x	x
Detail of drawings in unclear and coherent plans	x	x	x	x	x
Delay of final inspection of works on site									x	x	x	x	x
Ignorance of safety regulations										x	x	x
Frequency	7	7	7	7	6	2	8	6	6	9	10	6	7

Item	C.U.I.	Initial Budget PEN	Updated Budget PEN	Variation (%)
1	2234509	98,242,198.27	130,631,709.75	33.0%
2	2114066	149,461,811.00	183,516,976.51	22.8%
3	2234505	80,146,949.44	121,959,456.08	52.2%
4	2234506	44,205,657.27	63,629,302.11	43.9%
5	2234510	42,051,866.46	55,706,416.58	32.5%
6	2234507	38,677,718.15	58,612,886.09	51.5%
7	2134084	46,323,155.00	66,917,933.20	44.5%
8	2113014	23,773,420.03	35,329,542.69	48.6%
9	2177562	155,392,551.96	168,995,500.25	8.8%
10	2177548	32,180,223.33	35,645,331.20	10.8%
11	2177558	33,953,181.76	42,276,932.33	24.5%
12	2177561	55,133,625.31	63,049,526.39	14.4%
13	2177559	92,776,301.67	112,591,649.38	21.4%

Item	C.U.I.	Audit Findings
1	2234509	12
2	2114066	8
3	2234505	15
4	2234506	7
5	2234510	2
6	2234507	7
7	2134084	5
8	2113014	4
9	2177562	1
10	2177548	3
11	2177558	3
12	2177561	3
13	2177559	3

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Romero, A.; Esenarro, D. Factors Affecting Contract Compliance and Execution of Public Works in the Executing Unit: Special Project Huallaga Central and Bajo Mayo in Peru, 2022. Buildings 2024 , 14 , 2664. https://doi.org/10.3390/buildings14092664

Romero A, Esenarro D. Factors Affecting Contract Compliance and Execution of Public Works in the Executing Unit: Special Project Huallaga Central and Bajo Mayo in Peru, 2022. Buildings . 2024; 14(9):2664. https://doi.org/10.3390/buildings14092664

Romero, Anjhinson, and Doris Esenarro. 2024. "Factors Affecting Contract Compliance and Execution of Public Works in the Executing Unit: Special Project Huallaga Central and Bajo Mayo in Peru, 2022" Buildings 14, no. 9: 2664. https://doi.org/10.3390/buildings14092664

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A research method is a type of research or a research tool, like an interview or survey, that you use to collect and evaluate data in pursuit of answers. Show Transcript Video: Types of Research: Definitions and Examples Data-informed decisions are critical to a successful business.
What are research methods?
Research methods are different from research methodologies because they are the ways in which you will collect the data for your research project. The best method for your project largely depends on your topic, the type of data you will need, and the people or items from which you will be collecting data.
1000+ Research Topics & Research Title Examples For Students
A research topic is the subject of a research project or study - for example, a dissertation or thesis. A research topic typically takes the form of a problem to be solved, or a question to be answered. A good research topic should be specific enough to allow for focused research and analysis. For example, if you are interested in studying ...
Research Associate, in Salt Lake City
Research Associate, in Salt Lake City Research Associate Job Summary The Genetic Science Learning Center (GSLC ) at the University of Utah is a world-renowned team dedicated to making science and health accessible to everyone. Our Learn.Genetics and Teach.Genetics websites are accessed globally, accounting for one-third of utah.edu's annual traffic.</p><p>We seek an energetic, collaborative ...
Research on the Teaching Method of Automatic Control Principle Based on
This study discusses the teaching method of control principle based on problem-oriented learning (PBL), and verifies its feasibility and effectiveness through teaching practice and effect evaluation. Research has found that the PBL teaching method can stimulate students 'interest, improve their learning effect, and cultivate students' problem-solving ability, teamwork and innovation ability ...
What Is a Research Design
A research design is a strategy for answering your research question using empirical data. Creating a research design means making decisions about: Your overall research objectives and approach. Whether you'll rely on primary research or secondary research. Your sampling methods or criteria for selecting subjects. Your data collection methods.
Effect evaluation of outpatient long-term video EEGs for people with
Methods. ALVEEG is a prospective, multicenter, randomized controlled equivalence trial, involving five epilepsy centers in the eastern states of Germany. Patients will be randomized into either intervention (IG) or control group (CG), using a permuted block randomization. The sample size targeted is 688 patients, continuously recruited over the ...
NTRS
For example, there are projections of large increases to the 864,000 registered UAS and 45,000 aviation operations taking place in the NAS each day. With a data output range from 1 to 20 terabytes per flight or each aerial vehicle, which is projected to have proportional rate increase to that of registered UASs.
A data-driven method with sample entropy and CEEMDAN for ...
A data-driven method for short-term degradation prediction is proposed based on Sample Entropy (SE), Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and a varying ...
10 Research Question Examples to Guide your Research Project
The first question asks for a ready-made solution, and is not focused or researchable. The second question is a clearer comparative question, but note that it may not be practically feasible. For a smaller research project or thesis, it could be narrowed down further to focus on the effectiveness of drunk driving laws in just one or two countries.
Buildings
Cost overruns, delays, and poor quality are frequent in public investment projects under the contract modality, executed by the Executing Unit: Special Project Huallaga Central and Bajo Mayo (PEHCBM). The purpose of this research is to identify the factors that affect the fulfillment of contracts for the execution of public works in the PEHCBM. This research includes the determination of the ...

What Is Research Methodology? Types, Process, Examples In Research Design

Types Of Research Methodology

Qualitative Research Methodology

Quantitative Research Methodology

Mixed Research Methodology

Factors To Consider When Deciding On Research Methodology

Research Question Compatibility

Data Requirements

Resources and Constraints

Skill Set and Expertise

Ethical and Practical Considerations

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Research Methods | Definition, Types, Examples

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Qualitative vs quantitative data

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Qualitative analysis methods

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The Essential Guide to Doing Your Research Project

How to write a research plan: Step-by-step guide

Define your project’s purpose

Identify individual objectives

Select research methods

Recruit participants and allocate tasks

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Create a realistic timeline

Determine how to present your results

Customizing a research plan template

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What is Research Methodology? Definition, Types, and Examples

What is research methodology ?

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