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How to Write a Research Question: Types and Examples 

The first step in any research project is framing the research question. It can be considered the core of any systematic investigation as the research outcomes are tied to asking the right questions. Thus, this primary interrogation point sets the pace for your research as it helps collect relevant and insightful information that ultimately influences your work.   

Typically, the research question guides the stages of inquiry, analysis, and reporting. Depending on the use of quantifiable or quantitative data, research questions are broadly categorized into quantitative or qualitative research questions. Both types of research questions can be used independently or together, considering the overall focus and objectives of your research.  

What is a research question?

A research question is a clear, focused, concise, and arguable question on which your research and writing are centered. 1 It states various aspects of the study, including the population and variables to be studied and the problem the study addresses. These questions also set the boundaries of the study, ensuring cohesion. 

Designing the research question is a dynamic process where the researcher can change or refine the research question as they review related literature and develop a framework for the study. Depending on the scale of your research, the study can include single or multiple research questions. 

A good research question has the following features: 

• It is relevant to the chosen field of study. 
• The question posed is arguable and open for debate, requiring synthesizing and analysis of ideas. 
• It is focused and concisely framed. 
• A feasible solution is possible within the given practical constraint and timeframe. 

A poorly formulated research question poses several risks. 1   

• Researchers can adopt an erroneous design. 
• It can create confusion and hinder the thought process, including developing a clear protocol.  
• It can jeopardize publication efforts.  
• It causes difficulty in determining the relevance of the study findings.  
• It causes difficulty in whether the study fulfils the inclusion criteria for systematic review and meta-analysis. This creates challenges in determining whether additional studies or data collection is needed to answer the question.  
• Readers may fail to understand the objective of the study. This reduces the likelihood of the study being cited by others. 

Now that you know “What is a research question?”, let’s look at the different types of research questions. 

Types of research questions

Depending on the type of research to be done, research questions can be classified broadly into quantitative, qualitative, or mixed-methods studies. Knowing the type of research helps determine the best type of research question that reflects the direction and epistemological underpinnings of your research. 

The structure and wording of quantitative 2 and qualitative research 3 questions differ significantly. The quantitative study looks at causal relationships, whereas the qualitative study aims at exploring a phenomenon. 

• Quantitative research questions:  
• Seeks to investigate social, familial, or educational experiences or processes in a particular context and/or location.  
• Answers ‘how,’ ‘what,’ or ‘why’ questions. 
• Investigates connections, relations, or comparisons between independent and dependent variables. 

Quantitative research questions can be further categorized into descriptive, comparative, and relationship, as explained in the Table below. 

• Qualitative research questions  

Qualitative research questions are adaptable, non-directional, and more flexible. It concerns broad areas of research or more specific areas of study to discover, explain, or explore a phenomenon. These are further classified as follows: 

• Mixed-methods studies  

Mixed-methods studies use both quantitative and qualitative research questions to answer your research question. Mixed methods provide a complete picture than standalone quantitative or qualitative research, as it integrates the benefits of both methods. Mixed methods research is often used in multidisciplinary settings and complex situational or societal research, especially in the behavioral, health, and social science fields. 

What makes a good research question

A good research question should be clear and focused to guide your research. It should synthesize multiple sources to present your unique argument, and should ideally be something that you are interested in. But avoid questions that can be answered in a few factual statements. The following are the main attributes of a good research question. 

• Specific: The research question should not be a fishing expedition performed in the hopes that some new information will be found that will benefit the researcher. The central research question should work with your research problem to keep your work focused. If using multiple questions, they should all tie back to the central aim. 
• Measurable: The research question must be answerable using quantitative and/or qualitative data or from scholarly sources to develop your research question. If such data is impossible to access, it is better to rethink your question. 
• Attainable: Ensure you have enough time and resources to do all research required to answer your question. If it seems you will not be able to gain access to the data you need, consider narrowing down your question to be more specific. 
• You have the expertise 
• You have the equipment and resources 
• Realistic: Developing your research question should be based on initial reading about your topic. It should focus on addressing a problem or gap in the existing knowledge in your field or discipline. 
• Based on some sort of rational physics 
• Can be done in a reasonable time frame 
• Timely: The research question should contribute to an existing and current debate in your field or in society at large. It should produce knowledge that future researchers or practitioners can later build on. 
• Novel 
• Based on current technologies. 
• Important to answer current problems or concerns. 
• Lead to new directions. 
• Important: Your question should have some aspect of originality. Incremental research is as important as exploring disruptive technologies. For example, you can focus on a specific location or explore a new angle. 
• Meaningful whether the answer is “Yes” or “No.” Closed-ended, yes/no questions are too simple to work as good research questions. Such questions do not provide enough scope for robust investigation and discussion. A good research question requires original data, synthesis of multiple sources, and original interpretation and argumentation before providing an answer. 

Steps for developing a good research question

The importance of research questions cannot be understated. When drafting a research question, use the following frameworks to guide the components of your question to ease the process. 4  

• Determine the requirements: Before constructing a good research question, set your research requirements. What is the purpose? Is it descriptive, comparative, or explorative research? Determining the research aim will help you choose the most appropriate topic and word your question appropriately. 
• Select a broad research topic: Identify a broader subject area of interest that requires investigation. Techniques such as brainstorming or concept mapping can help identify relevant connections and themes within a broad research topic. For example, how to learn and help students learn. 
• Perform preliminary investigation: Preliminary research is needed to obtain up-to-date and relevant knowledge on your topic. It also helps identify issues currently being discussed from which information gaps can be identified. 
• Narrow your focus: Narrow the scope and focus of your research to a specific niche. This involves focusing on gaps in existing knowledge or recent literature or extending or complementing the findings of existing literature. Another approach involves constructing strong research questions that challenge your views or knowledge of the area of study (Example: Is learning consistent with the existing learning theory and research). 
• Identify the research problem: Once the research question has been framed, one should evaluate it. This is to realize the importance of the research questions and if there is a need for more revising (Example: How do your beliefs on learning theory and research impact your instructional practices). 

How to write a research question

Those struggling to understand how to write a research question, these simple steps can help you simplify the process of writing a research question. 

Sample Research Questions

The following are some bad and good research question examples 

• Example 1 
• Example 2 

References:  

• Thabane, L., Thomas, T., Ye, C., & Paul, J. (2009). Posing the research question: not so simple.  Canadian Journal of Anesthesia/Journal canadien d’anesthésie ,  56 (1), 71-79. 
• Rutberg, S., & Bouikidis, C. D. (2018). Focusing on the fundamentals: A simplistic differentiation between qualitative and quantitative research.  Nephrology Nursing Journal ,  45 (2), 209-213. 
• Kyngäs, H. (2020). Qualitative research and content analysis.  The application of content analysis in nursing science research , 3-11. 
• Mattick, K., Johnston, J., & de la Croix, A. (2018). How to… write a good research question.  The clinical teacher ,  15 (2), 104-108. 
• Fandino, W. (2019). Formulating a good research question: Pearls and pitfalls.  Indian Journal of Anaesthesia ,  63 (8), 611. 
• Richardson, W. S., Wilson, M. C., Nishikawa, J., & Hayward, R. S. (1995). The well-built clinical question: a key to evidence-based decisions.  ACP journal club ,  123 (3), A12-A13 

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Home » Research Questions – Types, Examples and Writing Guide

Research Questions – Types, Examples and Writing Guide

Table of Contents

Research Questions

Definition:

Research questions are the specific questions that guide a research study or inquiry. These questions help to define the scope of the research and provide a clear focus for the study. Research questions are usually developed at the beginning of a research project and are designed to address a particular research problem or objective.

Types of Research Questions

Types of Research Questions are as follows:

Descriptive Research Questions

These aim to describe a particular phenomenon, group, or situation. For example:

• What are the characteristics of the target population?
• What is the prevalence of a particular disease in a specific region?

Exploratory Research Questions

These aim to explore a new area of research or generate new ideas or hypotheses. For example:

• What are the potential causes of a particular phenomenon?
• What are the possible outcomes of a specific intervention?

Explanatory Research Questions

These aim to understand the relationship between two or more variables or to explain why a particular phenomenon occurs. For example:

• What is the effect of a specific drug on the symptoms of a particular disease?
• What are the factors that contribute to employee turnover in a particular industry?

Predictive Research Questions

These aim to predict a future outcome or trend based on existing data or trends. For example :

• What will be the future demand for a particular product or service?
• What will be the future prevalence of a particular disease?

Evaluative Research Questions

These aim to evaluate the effectiveness of a particular intervention or program. For example:

• What is the impact of a specific educational program on student learning outcomes?
• What is the effectiveness of a particular policy or program in achieving its intended goals?

How to Choose Research Questions

Choosing research questions is an essential part of the research process and involves careful consideration of the research problem, objectives, and design. Here are some steps to consider when choosing research questions:

• Identify the research problem: Start by identifying the problem or issue that you want to study. This could be a gap in the literature, a social or economic issue, or a practical problem that needs to be addressed.
• Conduct a literature review: Conducting a literature review can help you identify existing research in your area of interest and can help you formulate research questions that address gaps or limitations in the existing literature.
• Define the research objectives : Clearly define the objectives of your research. What do you want to achieve with your study? What specific questions do you want to answer?
• Consider the research design : Consider the research design that you plan to use. This will help you determine the appropriate types of research questions to ask. For example, if you plan to use a qualitative approach, you may want to focus on exploratory or descriptive research questions.
• Ensure that the research questions are clear and answerable: Your research questions should be clear and specific, and should be answerable with the data that you plan to collect. Avoid asking questions that are too broad or vague.
• Get feedback : Get feedback from your supervisor, colleagues, or peers to ensure that your research questions are relevant, feasible, and meaningful.

How to Write Research Questions

Guide for Writing Research Questions:

• Start with a clear statement of the research problem: Begin by stating the problem or issue that your research aims to address. This will help you to formulate focused research questions.
• Use clear language : Write your research questions in clear and concise language that is easy to understand. Avoid using jargon or technical terms that may be unfamiliar to your readers.
• Be specific: Your research questions should be specific and focused. Avoid broad questions that are difficult to answer. For example, instead of asking “What is the impact of climate change on the environment?” ask “What are the effects of rising sea levels on coastal ecosystems?”
• Use appropriate question types: Choose the appropriate question types based on the research design and objectives. For example, if you are conducting a qualitative study, you may want to use open-ended questions that allow participants to provide detailed responses.
• Consider the feasibility of your questions : Ensure that your research questions are feasible and can be answered with the resources available. Consider the data sources and methods of data collection when writing your questions.
• Seek feedback: Get feedback from your supervisor, colleagues, or peers to ensure that your research questions are relevant, appropriate, and meaningful.

Examples of Research Questions

Some Examples of Research Questions with Research Titles:

Research Title: The Impact of Social Media on Mental Health

• Research Question : What is the relationship between social media use and mental health, and how does this impact individuals’ well-being?

Research Title: Factors Influencing Academic Success in High School

• Research Question: What are the primary factors that influence academic success in high school, and how do they contribute to student achievement?

Research Title: The Effects of Exercise on Physical and Mental Health

• Research Question: What is the relationship between exercise and physical and mental health, and how can exercise be used as a tool to improve overall well-being?

Research Title: Understanding the Factors that Influence Consumer Purchasing Decisions

• Research Question : What are the key factors that influence consumer purchasing decisions, and how do these factors vary across different demographics and products?

Research Title: The Impact of Technology on Communication

• Research Question : How has technology impacted communication patterns, and what are the effects of these changes on interpersonal relationships and society as a whole?

Research Title: Investigating the Relationship between Parenting Styles and Child Development

• Research Question: What is the relationship between different parenting styles and child development outcomes, and how do these outcomes vary across different ages and developmental stages?

Research Title: The Effectiveness of Cognitive-Behavioral Therapy in Treating Anxiety Disorders

• Research Question: How effective is cognitive-behavioral therapy in treating anxiety disorders, and what factors contribute to its success or failure in different patients?

Research Title: The Impact of Climate Change on Biodiversity

• Research Question : How is climate change affecting global biodiversity, and what can be done to mitigate the negative effects on natural ecosystems?

Research Title: Exploring the Relationship between Cultural Diversity and Workplace Productivity

• Research Question : How does cultural diversity impact workplace productivity, and what strategies can be employed to maximize the benefits of a diverse workforce?

Research Title: The Role of Artificial Intelligence in Healthcare

• Research Question: How can artificial intelligence be leveraged to improve healthcare outcomes, and what are the potential risks and ethical concerns associated with its use?

Applications of Research Questions

Here are some of the key applications of research questions:

• Defining the scope of the study : Research questions help researchers to narrow down the scope of their study and identify the specific issues they want to investigate.
• Developing hypotheses: Research questions often lead to the development of hypotheses, which are testable predictions about the relationship between variables. Hypotheses provide a clear and focused direction for the study.
• Designing the study : Research questions guide the design of the study, including the selection of participants, the collection of data, and the analysis of results.
• Collecting data : Research questions inform the selection of appropriate methods for collecting data, such as surveys, interviews, or experiments.
• Analyzing data : Research questions guide the analysis of data, including the selection of appropriate statistical tests and the interpretation of results.
• Communicating results : Research questions help researchers to communicate the results of their study in a clear and concise manner. The research questions provide a framework for discussing the findings and drawing conclusions.

Characteristics of Research Questions

Characteristics of Research Questions are as follows:

• Clear and Specific : A good research question should be clear and specific. It should clearly state what the research is trying to investigate and what kind of data is required.
• Relevant : The research question should be relevant to the study and should address a current issue or problem in the field of research.
• Testable : The research question should be testable through empirical evidence. It should be possible to collect data to answer the research question.
• Concise : The research question should be concise and focused. It should not be too broad or too narrow.
• Feasible : The research question should be feasible to answer within the constraints of the research design, time frame, and available resources.
• Original : The research question should be original and should contribute to the existing knowledge in the field of research.
• Significant : The research question should have significance and importance to the field of research. It should have the potential to provide new insights and knowledge to the field.
• Ethical : The research question should be ethical and should not cause harm to any individuals or groups involved in the study.

Purpose of Research Questions

Research questions are the foundation of any research study as they guide the research process and provide a clear direction to the researcher. The purpose of research questions is to identify the scope and boundaries of the study, and to establish the goals and objectives of the research.

The main purpose of research questions is to help the researcher to focus on the specific area or problem that needs to be investigated. They enable the researcher to develop a research design, select the appropriate methods and tools for data collection and analysis, and to organize the results in a meaningful way.

Research questions also help to establish the relevance and significance of the study. They define the research problem, and determine the research methodology that will be used to address the problem. Research questions also help to determine the type of data that will be collected, and how it will be analyzed and interpreted.

Finally, research questions provide a framework for evaluating the results of the research. They help to establish the validity and reliability of the data, and provide a basis for drawing conclusions and making recommendations based on the findings of the study.

Advantages of Research Questions

There are several advantages of research questions in the research process, including:

• Focus : Research questions help to focus the research by providing a clear direction for the study. They define the specific area of investigation and provide a framework for the research design.
• Clarity : Research questions help to clarify the purpose and objectives of the study, which can make it easier for the researcher to communicate the research aims to others.
• Relevance : Research questions help to ensure that the study is relevant and meaningful. By asking relevant and important questions, the researcher can ensure that the study will contribute to the existing body of knowledge and address important issues.
• Consistency : Research questions help to ensure consistency in the research process by providing a framework for the development of the research design, data collection, and analysis.
• Measurability : Research questions help to ensure that the study is measurable by defining the specific variables and outcomes that will be measured.
• Replication : Research questions help to ensure that the study can be replicated by providing a clear and detailed description of the research aims, methods, and outcomes. This makes it easier for other researchers to replicate the study and verify the results.

Limitations of Research Questions

Limitations of Research Questions are as follows:

• Subjectivity : Research questions are often subjective and can be influenced by personal biases and perspectives of the researcher. This can lead to a limited understanding of the research problem and may affect the validity and reliability of the study.
• Inadequate scope : Research questions that are too narrow in scope may limit the breadth of the study, while questions that are too broad may make it difficult to focus on specific research objectives.
• Unanswerable questions : Some research questions may not be answerable due to the lack of available data or limitations in research methods. In such cases, the research question may need to be rephrased or modified to make it more answerable.
• Lack of clarity : Research questions that are poorly worded or ambiguous can lead to confusion and misinterpretation. This can result in incomplete or inaccurate data, which may compromise the validity of the study.
• Difficulty in measuring variables : Some research questions may involve variables that are difficult to measure or quantify, making it challenging to draw meaningful conclusions from the data.
• Lack of generalizability: Research questions that are too specific or limited in scope may not be generalizable to other contexts or populations. This can limit the applicability of the study’s findings and restrict its broader implications.

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Research Aims, Objectives & Questions

The “Golden Thread” Explained Simply (+ Examples)

By: David Phair (PhD) and Alexandra Shaeffer (PhD) | June 2022

The research aims , objectives and research questions (collectively called the “golden thread”) are arguably the most important thing you need to get right when you’re crafting a research proposal , dissertation or thesis . We receive questions almost every day about this “holy trinity” of research and there’s certainly a lot of confusion out there, so we’ve crafted this post to help you navigate your way through the fog.

Overview: The Golden Thread

• What is the golden thread
• What are research aims ( examples )
• What are research objectives ( examples )
• What are research questions ( examples )
• The importance of alignment in the golden thread

What is the “golden thread”?  

The golden thread simply refers to the collective research aims , research objectives , and research questions for any given project (i.e., a dissertation, thesis, or research paper ). These three elements are bundled together because it’s extremely important that they align with each other, and that the entire research project aligns with them.

Importantly, the golden thread needs to weave its way through the entirety of any research project , from start to end. In other words, it needs to be very clearly defined right at the beginning of the project (the topic ideation and proposal stage) and it needs to inform almost every decision throughout the rest of the project. For example, your research design and methodology will be heavily influenced by the golden thread (we’ll explain this in more detail later), as well as your literature review.

The research aims, objectives and research questions (the golden thread) define the focus and scope ( the delimitations ) of your research project. In other words, they help ringfence your dissertation or thesis to a relatively narrow domain, so that you can “go deep” and really dig into a specific problem or opportunity. They also help keep you on track , as they act as a litmus test for relevance. In other words, if you’re ever unsure whether to include something in your document, simply ask yourself the question, “does this contribute toward my research aims, objectives or questions?”. If it doesn’t, chances are you can drop it.

Alright, enough of the fluffy, conceptual stuff. Let’s get down to business and look at what exactly the research aims, objectives and questions are and outline a few examples to bring these concepts to life.

Research Aims: What are they?

Simply put, the research aim(s) is a statement that reflects the broad overarching goal (s) of the research project. Research aims are fairly high-level (low resolution) as they outline the general direction of the research and what it’s trying to achieve .

Research Aims: Examples  

True to the name, research aims usually start with the wording “this research aims to…”, “this research seeks to…”, and so on. For example:

“This research aims to explore employee experiences of digital transformation in retail HR.”   “This study sets out to assess the interaction between student support and self-care on well-being in engineering graduate students”  

As you can see, these research aims provide a high-level description of what the study is about and what it seeks to achieve. They’re not hyper-specific or action-oriented, but they’re clear about what the study’s focus is and what is being investigated.

Need a helping hand?

Research Objectives: What are they?

The research objectives take the research aims and make them more practical and actionable . In other words, the research objectives showcase the steps that the researcher will take to achieve the research aims.

The research objectives need to be far more specific (higher resolution) and actionable than the research aims. In fact, it’s always a good idea to craft your research objectives using the “SMART” criteria. In other words, they should be specific, measurable, achievable, relevant and time-bound”.

Research Objectives: Examples  

Let’s look at two examples of research objectives. We’ll stick with the topic and research aims we mentioned previously.  

For the digital transformation topic:

To observe the retail HR employees throughout the digital transformation. To assess employee perceptions of digital transformation in retail HR. To identify the barriers and facilitators of digital transformation in retail HR.

And for the student wellness topic:

To determine whether student self-care predicts the well-being score of engineering graduate students. To determine whether student support predicts the well-being score of engineering students. To assess the interaction between student self-care and student support when predicting well-being in engineering graduate students.

  As you can see, these research objectives clearly align with the previously mentioned research aims and effectively translate the low-resolution aims into (comparatively) higher-resolution objectives and action points . They give the research project a clear focus and present something that resembles a research-based “to-do” list.

Research Questions: What are they?

Finally, we arrive at the all-important research questions. The research questions are, as the name suggests, the key questions that your study will seek to answer . Simply put, they are the core purpose of your dissertation, thesis, or research project. You’ll present them at the beginning of your document (either in the introduction chapter or literature review chapter) and you’ll answer them at the end of your document (typically in the discussion and conclusion chapters).  

The research questions will be the driving force throughout the research process. For example, in the literature review chapter, you’ll assess the relevance of any given resource based on whether it helps you move towards answering your research questions. Similarly, your methodology and research design will be heavily influenced by the nature of your research questions. For instance, research questions that are exploratory in nature will usually make use of a qualitative approach, whereas questions that relate to measurement or relationship testing will make use of a quantitative approach.  

Let’s look at some examples of research questions to make this more tangible.

Research Questions: Examples  

Again, we’ll stick with the research aims and research objectives we mentioned previously.  

For the digital transformation topic (which would be qualitative in nature):

How do employees perceive digital transformation in retail HR? What are the barriers and facilitators of digital transformation in retail HR?  

And for the student wellness topic (which would be quantitative in nature):

Does student self-care predict the well-being scores of engineering graduate students? Does student support predict the well-being scores of engineering students? Do student self-care and student support interact when predicting well-being in engineering graduate students?  

You’ll probably notice that there’s quite a formulaic approach to this. In other words, the research questions are basically the research objectives “converted” into question format. While that is true most of the time, it’s not always the case. For example, the first research objective for the digital transformation topic was more or less a step on the path toward the other objectives, and as such, it didn’t warrant its own research question.  

So, don’t rush your research questions and sloppily reword your objectives as questions. Carefully think about what exactly you’re trying to achieve (i.e. your research aim) and the objectives you’ve set out, then craft a set of well-aligned research questions . Also, keep in mind that this can be a somewhat iterative process , where you go back and tweak research objectives and aims to ensure tight alignment throughout the golden thread.

The importance of strong alignment 

Alignment is the keyword here and we have to stress its importance . Simply put, you need to make sure that there is a very tight alignment between all three pieces of the golden thread. If your research aims and research questions don’t align, for example, your project will be pulling in different directions and will lack focus . This is a common problem students face and can cause many headaches (and tears), so be warned.

Take the time to carefully craft your research aims, objectives and research questions before you run off down the research path. Ideally, get your research supervisor/advisor to review and comment on your golden thread before you invest significant time into your project, and certainly before you start collecting data .  

Recap: The golden thread

In this post, we unpacked the golden thread of research, consisting of the research aims , research objectives and research questions . You can jump back to any section using the links below.

As always, feel free to leave a comment below – we always love to hear from you. Also, if you’re interested in 1-on-1 support, take a look at our private coaching service here.

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This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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39 Comments

Thank you very much for your great effort put. As an Undergraduate taking Demographic Research & Methodology, I’ve been trying so hard to understand clearly what is a Research Question, Research Aim and the Objectives in a research and the relationship between them etc. But as for now I’m thankful that you’ve solved my problem.

Well appreciated. This has helped me greatly in doing my dissertation.

An so delighted with this wonderful information thank you a lot.

so impressive i have benefited a lot looking forward to learn more on research.

I am very happy to have carefully gone through this well researched article.

Infact,I used to be phobia about anything research, because of my poor understanding of the concepts.

Now,I get to know that my research question is the same as my research objective(s) rephrased in question format.

I please I would need a follow up on the subject,as I intends to join the team of researchers. Thanks once again.

Thanks so much. This was really helpful.

I know you pepole have tried to break things into more understandable and easy format. And God bless you. Keep it up

i found this document so useful towards my study in research methods. thanks so much.

This is my 2nd read topic in your course and I should commend the simplified explanations of each part. I’m beginning to understand and absorb the use of each part of a dissertation/thesis. I’ll keep on reading your free course and might be able to avail the training course! Kudos!

Thank you! Better put that my lecture and helped to easily understand the basics which I feel often get brushed over when beginning dissertation work.

This is quite helpful. I like how the Golden thread has been explained and the needed alignment.

This is quite helpful. I really appreciate!

The article made it simple for researcher students to differentiate between three concepts.

Very innovative and educational in approach to conducting research.

I am very impressed with all these terminology, as I am a fresh student for post graduate, I am highly guided and I promised to continue making consultation when the need arise. Thanks a lot.

A very helpful piece. thanks, I really appreciate it .

Very well explained, and it might be helpful to many people like me.

Wish i had found this (and other) resource(s) at the beginning of my PhD journey… not in my writing up year… 😩 Anyways… just a quick question as i’m having some issues ordering my “golden thread”…. does it matter in what order you mention them? i.e., is it always first aims, then objectives, and finally the questions? or can you first mention the research questions and then the aims and objectives?

Thank you for a very simple explanation that builds upon the concepts in a very logical manner. Just prior to this, I read the research hypothesis article, which was equally very good. This met my primary objective.

My secondary objective was to understand the difference between research questions and research hypothesis, and in which context to use which one. However, I am still not clear on this. Can you kindly please guide?

In research, a research question is a clear and specific inquiry that the researcher wants to answer, while a research hypothesis is a tentative statement or prediction about the relationship between variables or the expected outcome of the study. Research questions are broader and guide the overall study, while hypotheses are specific and testable statements used in quantitative research. Research questions identify the problem, while hypotheses provide a focus for testing in the study.

Exactly what I need in this research journey, I look forward to more of your coaching videos.

This helped a lot. Thanks so much for the effort put into explaining it.

What data source in writing dissertation/Thesis requires?

What is data source covers when writing dessertation/thesis

This is quite useful thanks

I’m excited and thankful. I got so much value which will help me progress in my thesis.

where are the locations of the reserch statement, research objective and research question in a reserach paper? Can you write an ouline that defines their places in the researh paper?

Very helpful and important tips on Aims, Objectives and Questions.

Thank you so much for making research aim, research objectives and research question so clear. This will be helpful to me as i continue with my thesis.

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As a researcher and lecturer, I find splitting research goals into research aims, objectives, and questions is unnecessarily bureaucratic and confusing for students. For most biomedical research projects, including ‘real research’, 1-3 research questions will suffice (numbers may differ by discipline).

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Well explained

The blog article on research aims, objectives, and questions by Grad Coach is a clear and insightful guide that aligns with my experiences in academic research. The article effectively breaks down the often complex concepts of research aims and objectives, providing a straightforward and accessible explanation. Drawing from my own research endeavors, I appreciate the practical tips offered, such as the need for specificity and clarity when formulating research questions. The article serves as a valuable resource for students and researchers, offering a concise roadmap for crafting well-defined research goals and objectives. Whether you’re a novice or an experienced researcher, this article provides practical insights that contribute to the foundational aspects of a successful research endeavor.

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How to Develop a Good Research Question? — Types & Examples

Cecilia is living through a tough situation in her research life. Figuring out where to begin, how to start her research study, and how to pose the right question for her research quest, is driving her insane. Well, questions, if not asked correctly, have a tendency to spiral us!

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Questions lead everyone to answers. Research is a quest to find answers. Not the vague questions that Cecilia means to answer, but definitely more focused questions that define your research. Therefore, asking appropriate question becomes an important matter of discussion.

A well begun research process requires a strong research question. It directs the research investigation and provides a clear goal to focus on. Understanding the characteristics of comprising a good research question will generate new ideas and help you discover new methods in research.

In this article, we are aiming to help researchers understand what is a research question and how to write one with examples.

Table of Contents

What Is a Research Question?

A good research question defines your study and helps you seek an answer to your research. Moreover, a clear research question guides the research paper or thesis to define exactly what you want to find out, giving your work its objective. Learning to write a research question is the beginning to any thesis, dissertation , or research paper. Furthermore, the question addresses issues or problems which is answered through analysis and interpretation of data.

Why Is a Research Question Important?

A strong research question guides the design of a study. Moreover, it helps determine the type of research and identify specific objectives. Research questions state the specific issue you are addressing and focus on outcomes of the research for individuals to learn. Therefore, it helps break up the study into easy steps to complete the objectives and answer the initial question.

Types of Research Questions

Research questions can be categorized into different types, depending on the type of research you want to undergo. Furthermore, knowing the type of research will help a researcher determine the best type of research question to use.

1. Qualitative Research Question

Qualitative questions concern broad areas or more specific areas of research. However, unlike quantitative questions, qualitative research questions are adaptable, non-directional and more flexible. Qualitative research question focus on discovering, explaining, elucidating, and exploring.

i. Exploratory Questions

This form of question looks to understand something without influencing the results. The objective of exploratory questions is to learn more about a topic without attributing bias or preconceived notions to it.

Research Question Example: Asking how a chemical is used or perceptions around a certain topic.

ii. Predictive Questions

Predictive research questions are defined as survey questions that automatically predict the best possible response options based on text of the question. Moreover, these questions seek to understand the intent or future outcome surrounding a topic.

Research Question Example: Asking why a consumer behaves in a certain way or chooses a certain option over other.

iii. Interpretive Questions

This type of research question allows the study of people in the natural setting. The questions help understand how a group makes sense of shared experiences with regards to various phenomena. These studies gather feedback on a group’s behavior without affecting the outcome.

Research Question Example: How do you feel about AI assisting publishing process in your research?

2. Quantitative Research Question

Quantitative questions prove or disprove a researcher’s hypothesis through descriptions, comparisons, and relationships. These questions are beneficial when choosing a research topic or when posing follow-up questions that garner more information.

i. Descriptive Questions

It is the most basic type of quantitative research question and it seeks to explain when, where, why, or how something occurred. Moreover, they use data and statistics to describe an event or phenomenon.

Research Question Example: How many generations of genes influence a future generation?

ii. Comparative Questions

Sometimes it’s beneficial to compare one occurrence with another. Therefore, comparative questions are helpful when studying groups with dependent variables.

Example: Do men and women have comparable metabolisms?

iii. Relationship-Based Questions

This type of research question answers influence of one variable on another. Therefore, experimental studies use this type of research questions are majorly.

Example: How is drought condition affect a region’s probability for wildfires.  

How to Write a Good Research Question?

1. Select a Topic

The first step towards writing a good research question is to choose a broad topic of research. You could choose a research topic that interests you, because the complete research will progress further from the research question. Therefore, make sure to choose a topic that you are passionate about, to make your research study more enjoyable.

2. Conduct Preliminary Research

After finalizing the topic, read and know about what research studies are conducted in the field so far. Furthermore, this will help you find articles that talk about the topics that are yet to be explored. You could explore the topics that the earlier research has not studied.

3. Consider Your Audience

The most important aspect of writing a good research question is to find out if there is audience interested to know the answer to the question you are proposing. Moreover, determining your audience will assist you in refining your research question, and focus on aspects that relate to defined groups.

4. Generate Potential Questions

The best way to generate potential questions is to ask open ended questions. Questioning broader topics will allow you to narrow down to specific questions. Identifying the gaps in literature could also give you topics to write the research question. Moreover, you could also challenge the existing assumptions or use personal experiences to redefine issues in research.

5. Review Your Questions

Once you have listed few of your questions, evaluate them to find out if they are effective research questions. Moreover while reviewing, go through the finer details of the question and its probable outcome, and find out if the question meets the research question criteria.

6. Construct Your Research Question

There are two frameworks to construct your research question. The first one being PICOT framework , which stands for:

• Population or problem
• Intervention or indicator being studied
• Comparison group
• Outcome of interest
• Time frame of the study.

The second framework is PEO , which stands for:

• Population being studied
• Exposure to preexisting conditions
• Outcome of interest.

Research Question Examples

• How might the discovery of a genetic basis for alcoholism impact triage processes in medical facilities?
• How do ecological systems respond to chronic anthropological disturbance?
• What are demographic consequences of ecological interactions?
• What roles do fungi play in wildfire recovery?
• How do feedbacks reinforce patterns of genetic divergence on the landscape?
• What educational strategies help encourage safe driving in young adults?
• What makes a grocery store easy for shoppers to navigate?
• What genetic factors predict if someone will develop hypothyroidism?
• Does contemporary evolution along the gradients of global change alter ecosystems function?

How did you write your first research question ? What were the steps you followed to create a strong research question? Do write to us or comment below.

Frequently Asked Questions

Research questions guide the focus and direction of a research study. Here are common types of research questions: 1. Qualitative research question: Qualitative questions concern broad areas or more specific areas of research. However, unlike quantitative questions, qualitative research questions are adaptable, non-directional and more flexible. Different types of qualitative research questions are: i. Exploratory questions ii. Predictive questions iii. Interpretive questions 2. Quantitative Research Question: Quantitative questions prove or disprove a researcher’s hypothesis through descriptions, comparisons, and relationships. These questions are beneficial when choosing a research topic or when posing follow-up questions that garner more information. Different types of quantitative research questions are: i. Descriptive questions ii. Comparative questions iii. Relationship-based questions

Qualitative research questions aim to explore the richness and depth of participants' experiences and perspectives. They should guide your research and allow for in-depth exploration of the phenomenon under investigation. After identifying the research topic and the purpose of your research: • Begin with Broad Inquiry: Start with a general research question that captures the main focus of your study. This question should be open-ended and allow for exploration. • Break Down the Main Question: Identify specific aspects or dimensions related to the main research question that you want to investigate. • Formulate Sub-questions: Create sub-questions that delve deeper into each specific aspect or dimension identified in the previous step. • Ensure Open-endedness: Make sure your research questions are open-ended and allow for varied responses and perspectives. Avoid questions that can be answered with a simple "yes" or "no." Encourage participants to share their experiences, opinions, and perceptions in their own words. • Refine and Review: Review your research questions to ensure they align with your research purpose, topic, and objectives. Seek feedback from your research advisor or peers to refine and improve your research questions.

Developing research questions requires careful consideration of the research topic, objectives, and the type of study you intend to conduct. Here are the steps to help you develop effective research questions: 1. Select a Topic 2. Conduct Preliminary Research 3. Consider Your Audience 4. Generate Potential Questions 5. Review Your Questions 6. Construct Your Research Question Based on PICOT or PEO Framework

There are two frameworks to construct your research question. The first one being PICOT framework, which stands for: • Population or problem • Intervention or indicator being studied • Comparison group • Outcome of interest • Time frame of the study The second framework is PEO, which stands for: • Population being studied • Exposure to preexisting conditions • Outcome of interest

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Library Home

• Library Website
• Research Basics

Developing a Research Question

• Introduction
• The Research Process
• Scholarly & Peer-Reviewed
• Primary vs. Secondary Sources
• Quantitative vs. Qualitative
• Evaluating Sources

What is a research question?

A research question is an essential tool to help guide your research paper, project, or thesis. It poses a specific question that you are seeking to answer in your paper. Research questions can be broad or narrow, and can change throughout the research process.

A good research question should be:

• Focused on a single issue
• Specific enough to answer thoroughly in your paper
• Feasible to answer within the length of your paper
• Researchable using the resources available to you
• Relevant to your field of study and/or to society at large

The length of your paper and the research you're able to locate will help to shape your research question. A longer paper, like a thesis or dissertation, may require multiple research questions.

The answer to your research question develops into your thesis statement .

Writing Your Research Question

Chose a Topic

You should choose a research topic that is interesting to you. This will make the research and writing process much more bearable.

A good way to begin brainstorming research questions is to list all the questions you would like to see answered, or topics you would like to learn more about. You may have been provided a list of potential topics by your professor, if none are interesting to you ask if you can develop your own.

It is better to start broad and narrow down your focus as you go.

Do Preliminary Research

Reference materials like encyclopedias can also be good for this purpose.

Narrow Your Topic

Now that you have a basic idea of what research exists on your topic, you can begin to narrow your focus.

Make sure that your question is specific enough that it can be answered thoroughly in the length of your paper.

Developing a Research Question Video Tutorial

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• Research Questions: Definitions, Types + [Examples]

Research questions lie at the core of systematic investigation and this is because recording accurate research outcomes is tied to asking the right questions. Asking the right questions when conducting research can help you collect relevant and insightful information that ultimately influences your work, positively. 

The right research questions are typically easy to understand, straight to the point, and engaging. In this article, we will share tips on how to create the right research questions and also show you how to create and administer an online questionnaire with Formplus . 

What is a Research Question? 

A research question is a specific inquiry which the research seeks to provide a response to. It resides at the core of systematic investigation and it helps you to clearly define a path for the research process. 

A research question is usually the first step in any research project. Basically, it is the primary interrogation point of your research and it sets the pace for your work.  

Typically, a research question focuses on the research, determines the methodology and hypothesis, and guides all stages of inquiry, analysis, and reporting. With the right research questions, you will be able to gather useful information for your investigation. 

Types of Research Questions 

Research questions are broadly categorized into 2; that is, qualitative research questions and quantitative research questions. Qualitative and quantitative research questions can be used independently and co-dependently in line with the overall focus and objectives of your research. 

If your research aims at collecting quantifiable data , you will need to make use of quantitative research questions. On the other hand, qualitative questions help you to gather qualitative data bothering on the perceptions and observations of your research subjects. 

Qualitative Research Questions  

A qualitative research question is a type of systematic inquiry that aims at collecting qualitative data from research subjects. The aim of qualitative research questions is to gather non-statistical information pertaining to the experiences, observations, and perceptions of the research subjects in line with the objectives of the investigation. 

Types of Qualitative Research Questions  

• Ethnographic Research Questions

As the name clearly suggests, ethnographic research questions are inquiries presented in ethnographic research. Ethnographic research is a qualitative research approach that involves observing variables in their natural environments or habitats in order to arrive at objective research outcomes. 

These research questions help the researcher to gather insights into the habits, dispositions, perceptions, and behaviors of research subjects as they interact in specific environments. 

Ethnographic research questions can be used in education, business, medicine, and other fields of study, and they are very useful in contexts aimed at collecting in-depth and specific information that are peculiar to research variables. For instance, asking educational ethnographic research questions can help you understand how pedagogy affects classroom relations and behaviors. 

This type of research question can be administered physically through one-on-one interviews, naturalism (live and work), and participant observation methods. Alternatively, the researcher can ask ethnographic research questions via online surveys and questionnaires created with Formplus.  

Examples of Ethnographic Research Questions

• Why do you use this product?
• Have you noticed any side effects since you started using this drug?
• Does this product meet your needs?

• Case Studies

A case study is a qualitative research approach that involves carrying out a detailed investigation into a research subject(s) or variable(s). In the course of a case study, the researcher gathers a range of data from multiple sources of information via different data collection methods, and over a period of time. 

The aim of a case study is to analyze specific issues within definite contexts and arrive at detailed research subject analyses by asking the right questions. This research method can be explanatory, descriptive , or exploratory depending on the focus of your systematic investigation or research. 

An explanatory case study is one that seeks to gather information on the causes of real-life occurrences. This type of case study uses “how” and “why” questions in order to gather valid information about the causative factors of an event. 

Descriptive case studies are typically used in business researches, and they aim at analyzing the impact of changing market dynamics on businesses. On the other hand, exploratory case studies aim at providing answers to “who” and “what” questions using data collection tools like interviews and questionnaires. 

Some questions you can include in your case studies are: 

• Why did you choose our services?
• How has this policy affected your business output?
• What benefits have you recorded since you started using our product?

An interview is a qualitative research method that involves asking respondents a series of questions in order to gather information about a research subject. Interview questions can be close-ended or open-ended , and they prompt participants to provide valid information that is useful to the research. 

An interview may also be structured, semi-structured , or unstructured , and this further influences the types of questions they include. Structured interviews are made up of more close-ended questions because they aim at gathering quantitative data while unstructured interviews consist, primarily, of open-ended questions that allow the researcher to collect qualitative information from respondents. 

You can conduct interview research by scheduling a physical meeting with respondents, through a telephone conversation, and via digital media and video conferencing platforms like Skype and Zoom. Alternatively, you can use Formplus surveys and questionnaires for your interview. 

Examples of interview questions include: 

• What challenges did you face while using our product?
• What specific needs did our product meet?
• What would you like us to improve our service delivery?

Quantitative Research Questions

Quantitative research questions are questions that are used to gather quantifiable data from research subjects. These types of research questions are usually more specific and direct because they aim at collecting information that can be measured; that is, statistical information. 

Types of Quantitative Research Questions

• Descriptive Research Questions

Descriptive research questions are inquiries that researchers use to gather quantifiable data about the attributes and characteristics of research subjects. These types of questions primarily seek responses that reveal existing patterns in the nature of the research subjects. 

It is important to note that descriptive research questions are not concerned with the causative factors of the discovered attributes and characteristics. Rather, they focus on the “what”; that is, describing the subject of the research without paying attention to the reasons for its occurrence. 

Descriptive research questions are typically closed-ended because they aim at gathering definite and specific responses from research participants. Also, they can be used in customer experience surveys and market research to collect information about target markets and consumer behaviors. 

Descriptive Research Question Examples

• How often do you make use of our fitness application?
• How much would you be willing to pay for this product?

• Comparative Research Questions

A comparative research question is a type of quantitative research question that is used to gather information about the differences between two or more research subjects across different variables. These types of questions help the researcher to identify distinct features that mark one research subject from the other while highlighting existing similarities. 

Asking comparative research questions in market research surveys can provide insights on how your product or service matches its competitors. In addition, it can help you to identify the strengths and weaknesses of your product for a better competitive advantage.  

The 5 steps involved in the framing of comparative research questions are: 

• Choose your starting phrase
• Identify and name the dependent variable
• Identify the groups you are interested in
• Identify the appropriate adjoining text
• Write out the comparative research question

Comparative Research Question Samples 

• What are the differences between a landline telephone and a smartphone?
• What are the differences between work-from-home and on-site operations?

• Relationship-based Research Questions  

Just like the name suggests, a relationship-based research question is one that inquires into the nature of the association between two research subjects within the same demographic. These types of research questions help you to gather information pertaining to the nature of the association between two research variables. 

Relationship-based research questions are also known as correlational research questions because they seek to clearly identify the link between 2 variables. 

Read: Correlational Research Designs: Types, Examples & Methods

Examples of relationship-based research questions include: 

• What is the relationship between purchasing power and the business site?
• What is the relationship between the work environment and workforce turnover?

Examples of a Good Research Question

Since research questions lie at the core of any systematic investigations, it is important to know how to frame a good research question. The right research questions will help you to gather the most objective responses that are useful to your systematic investigation. 

A good research question is one that requires impartial responses and can be answered via existing sources of information. Also, a good research question seeks answers that actively contribute to a body of knowledge; hence, it is a question that is yet to be answered in your specific research context.

• Open-Ended Questions

 An open-ended question is a type of research question that does not restrict respondents to a set of premeditated answer options. In other words, it is a question that allows the respondent to freely express his or her perceptions and feelings towards the research subject. 

Examples of Open-ended Questions

• How do you deal with stress in the workplace?
• What is a typical day at work like for you?
• Close-ended Questions

A close-ended question is a type of survey question that restricts respondents to a set of predetermined answers such as multiple-choice questions . Close-ended questions typically require yes or no answers and are commonly used in quantitative research to gather numerical data from research participants. 

Examples of Close-ended Questions

• Did you enjoy this event?
• How likely are you to recommend our services?
• Very Likely
• Somewhat Likely
• Likert Scale Questions

A Likert scale question is a type of close-ended question that is structured as a 3-point, 5-point, or 7-point psychometric scale . This type of question is used to measure the survey respondent’s disposition towards multiple variables and it can be unipolar or bipolar in nature. 

Example of Likert Scale Questions

• How satisfied are you with our service delivery?
• Very dissatisfied
• Not satisfied
• Very satisfied
• Rating Scale Questions

A rating scale question is a type of close-ended question that seeks to associate a specific qualitative measure (rating) with the different variables in research. It is commonly used in customer experience surveys, market research surveys, employee reviews, and product evaluations. 

Example of Rating Questions

• How would you rate our service delivery?

  Examples of a Bad Research Question

Knowing what bad research questions are would help you avoid them in the course of your systematic investigation. These types of questions are usually unfocused and often result in research biases that can negatively impact the outcomes of your systematic investigation. 

• Loaded Questions

A loaded question is a question that subtly presupposes one or more unverified assumptions about the research subject or participant. This type of question typically boxes the respondent in a corner because it suggests implicit and explicit biases that prevent objective responses. 

Example of Loaded Questions

• Have you stopped smoking?
• Where did you hide the money?
• Negative Questions

A negative question is a type of question that is structured with an implicit or explicit negator. Negative questions can be misleading because they upturn the typical yes/no response order by requiring a negative answer for affirmation and an affirmative answer for negation. 

Examples of Negative Questions

• Would you mind dropping by my office later today?
• Didn’t you visit last week?
• Leading Questions  

A l eading question is a type of survey question that nudges the respondent towards an already-determined answer. It is highly suggestive in nature and typically consists of biases and unverified assumptions that point toward its premeditated responses. 

Examples of Leading Questions

• If you enjoyed this service, would you be willing to try out our other packages?
• Our product met your needs, didn’t it?

Read More: Leading Questions: Definition, Types, and Examples

How to Use Formplus as Online Research Questionnaire Tool  

With Formplus, you can create and administer your online research questionnaire easily. In the form builder, you can add different form fields to your questionnaire and edit these fields to reflect specific research questions for your systematic investigation. 

Here is a step-by-step guide on how to create an online research questionnaire with Formplus: 

• Sign in to your Formplus accoun t, then click on the “create new form” button in your dashboard to access the Form builder.

• In the form builder, add preferred form fields to your online research questionnaire by dragging and dropping them into the form. Add a title to your form in the title block. You can edit form fields by clicking on the “pencil” icon on the right corner of each form field.

• Save the form to access the customization section of the builder. Here, you can tweak the appearance of your online research questionnaire by adding background images, changing the form font, and adding your organization’s logo.

• Finally, copy your form link and share it with respondents. You can also use any of the multiple sharing options available.

Conclusion  

The success of your research starts with framing the right questions to help you collect the most valid and objective responses. Be sure to avoid bad research questions like loaded and negative questions that can be misleading and adversely affect your research data and outcomes. 

Your research questions should clearly reflect the aims and objectives of your systematic investigation while laying emphasis on specific contexts. To help you seamlessly gather responses for your research questions, you can create an online research questionnaire on Formplus.  

Connect to Formplus, Get Started Now - It's Free!

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Research Questions: Types and Research Question Examples

The complete guide to research questions, including examples and sample research questions.

Research questions are critical components of any scientific investigation, guiding researchers toward focused preliminary research and assisting them in producing significant results. They provide a clear direction and purpose for the research paper and serve as the cornerstone.

In this article, we will discuss the significance of research questions and present 27 examples from diverse fields to demonstrate their variety and application.

What are the research questions?

Research questions are defined as fundamental questions that facilitate a research project, a research study, a dissertation, a thesis, or a review. It allows researchers to collect relevant information to narrow the study's purpose and solve the research problem.

Asking appropriate research questions is the most crucial step in market research projects. You can use the insights from your own research questions to determine the path of the study. These insights also play an essential role in conducting a survey, analyzing obtained data, and reporting the analyzed information.

Choosing the right research questions helps you decide whether qualitative and quantitative research methods are best. The main objective of your research and the research theme define the type of qualitative or quantitative research questions you use.

The target audience and kind of research you're conducting also play significant roles. Below are a few research question ideas and good research question examples.

27 Research questions examples

To develop research questions for your academic research or marketing study, you must understand the types of questions available. Let's look at examples of research questions and sample research questions in general. Use these existing methods or research question examples to build beautiful surveys.

01. Open-ended research question

Open-ended questions are widely used in qualitative research and are common examples of qualitative research questions. Open-ended questions capture open responses from a research audience and open the door for text-based analysis of the data you receive.

This type of question forms the foundation of online qualitative research conducted using surveys and questionnaires.

Below is an example of an open-ended research question:

02. Multiple choice research question

Researchers use multiple-choice research questions to capture single or multiple responses from your research audience. They typically use these market research questions when conducting poll-based research, where the audience needs to select multiple responses to one problem. It can also be used with single-select answers to limit the number of answers a respondent can choose.

Below is an example of a multiple-choice research question with a single-select answer option:

03. Rank order scaling research question

This is a ranking-type question that offers multiple answer options. The participant selects answers in order of preference. Researchers usually use these research questions to understand respondents' opinions on preferred brands or products.

You can use data from rank order questions to determine which product a respondent prefers, even if they enjoy multiple products. For example, someone may like chocolates, cakes, and candy, but which do they like the most?

Rank-order scaling questions are the right research questions to determine which dessert is most loved by the respondent.

Below is a typical example of rank order:

04. Rating scale research question

Rating scale research questions capture responses based on a continuous scale rather than individual points. It is often used in medical research visual analog scales or pain scales, where patients need to rate their pain level. Another example would be a typical experience-based rating scale, like the example below.

05. Net promoter score question

Brands typically use a Net Promoter Score question to evaluate customer loyalty and brand recommendations. This question type is prevalent in consumer research, where this single question can provide numeric insights into the customer experience.

The data collected from Net Promoter Score questions allows you to see how many of your brand's followers are actively promoting your brand. You also get insight into how many are actively not recommending your products. For example, respondents answer this question on a scale of 0-10:

As per their rankings, respondents are classified under either of the three groups: Detractors (0-6), Passives (7-8), and Promoters (9-10).

06. Likert scale research question

The Likert scale question presents a psychometric scale with different answer options such as agree/disagree, very frequently/not very often, important/unimportant, and other similar polarizing nature questions. Generally divided into even and odd Likert scale questions, they are highly popular with researchers due to the accuracy of their results.

07. Semantic differential scale research question

A semantic differential scale question quantifies the feelings and opinions of a respondent. This question type uses a multiple-point rating scale to understand better the respondent's feelings on a particular service, brand, organization, or product. The scale features polarized opinions on either end, with a neutral option in the middle.

08. Stapel scale research question

It is a unipolar research question with a +5 to -5 rating scale for the respondents to rate a single factor. These questions often involve offering the respondent an adjective or trait in conjunction with a brand or product. The respondent uses the scale to determine whether the attribute accurately or inaccurately describes the brand, product, or organization.

09. Constant sum research question

A numeric answer question allows a researcher to collect ratio data about the answer options' factors. Respondents can assign a particular value to an entity, and the other entities can be comparatively rated.

10. Demographic research question

Demographic questions are based on a person's age, gender, family income, race, ethnicity, education, and other defining factors. Research about whether a specific product will be effective with a particular age or gender group can be carried out using demographic research questions.

11. Matrix table research question

It is a multiple-choice, close-ended question where multiple parameters are rated using the same column answer options. Matrix questions work similarly to any other scale questions but allow for more efficient use of space. Instead of asking five questions about the quality of different customer experiences, you can use just one question to capture the data.

12. Side-by-side matrix research question

Side-by-side matrix research questions allow the respondent to rate multiple variables at once. Like a single matrix, these research questions will enable you to compact your survey. However, you mustn't overload respondents with too many matrix questions, as they require more thought to answer. It can lead to high dropout rates.

13. Static content question

This question is an option for the researchers to include descriptive research questions such as presentation text, heading, or subheading. Static content isn't technically a question, as it is used for display purposes only. Instead, your static content can provide participants with important information about a section or your survey.

14. Miscellaneous question

Miscellaneous questions allow you to ask questions that don't fit into another category. Some types of demographic or categorizing questions are best used as miscellaneous questions.

15. Visual analog scale question

A visual analog scale is used to analyze pain levels among patients and generally evaluate characteristics across a constant range of values. It gives a picture or graphic that depicts various feelings on a scale. The respondent uses the images to help determine where they fall on the scale.

16. Image chooser-type question

Images are perfect tools to enhance user experience and, in turn, increase response rates for research. Image research questions help make your survey more visually appealing while decreasing the time a respondent needs to answer a question. Using select one, select many, or image rating matrix question options prompts several respondents to reply to the research survey.

17. Data reference question

Reference data research questions are used to accumulate or approve zip code data against standardized data.

18. Upload data question

Respondents can upload images, digital signatures, or videos with their research responses. Upload data questions are the right research questions for collecting signatures or accepting submissions.

19. Choice model question

Conjoint analysis and Maximum Difference questions fall under the category of choice model research questions. Conjoint analysis is used to understand respondent preferences about two or more entities. Maximum Difference is used to rate up to 30 factors such as features, interests, the scope of improvement, or the potential positioning of an upcoming product.

20. Dichotomous research question

These question types have Yes/No/Maybe, True/False, and Agree/Disagree answer options. Using them extensively in research is not advised due to the limited insights received.

21. Leading research question

A leading question is a market research question that pushes respondents to answer a particular question in a specific manner based on how they are framed. Leading questions often already contain information that the survey creator wants to confirm rather than try to get a correct and unbiased answer to that question.

22. Text slider research question

A text slider research question is a rating scale question type that uses an interactive slider to select the most appropriate option. Rating scales are often used to measure the direction and intensity of attitudes. The scale is well-defined and increases at an equal rate.

23. Push to the social research question

Push to social research questions allows respondents to share positive reviews or feedback on social media sites like Facebook and Twitter. This question creates a positive feeling about your brand on social media. Alternatively, this can be effectively used to collect and address negative feedback before it goes out on social media.

24. Max diff research question

Max Diff is a question type where respondents are given a set of attributes and asked to indicate the best and worst. In this research question type, there is only one of each option in the final response. For example, if a bank wants to understand payment merchants' preferences, the question can be asked in the following format.

25. Van Westendorp-price sensitivity research Question

The Van Westendorp-Price Sensitivity is a technique for market researchers to gauge consumer perceptions of products or services' value. It helps in understanding the need to tweak the price and offering. For example, if a software product manufacturer wants to know how to price a product, the following question could be asked:

26. Date/time research question

The date/Time research question type allows for collecting date/time information filled in by a respondent. For example, the following question can answer questions about the date of birth.

27. CAPTCHA research question

This research question type limits the number of phony responses in a survey or data collection by automated computer programs.

Importance of using the right research questions

When a research program is initiated, it requires a channel to accurately collect data for the study. Research questions form this channel and help a researcher to kick-start the research.

As the research continues, these questions are molded according to the original insights, which shape a practical study. Your first research questions may not be the final step in the research process, but they are the first to build your research hypothesis.

The importance of research questions can be highly subjective. For some researchers, formulating research questions might be necessary because they provide insights into essential decision-making factors.

Or example, a focused research question could give you vital data about funding needs or how to find the right resources to reach business goals.

How to write a research question to capture accurate information

What are the good research questions? Specific research questions are much more useful than template questions. Follow these six steps to learn how to write questions for research:

• Select a broad research topic that interests the target audience: You must choose an intriguing topic to target respondents. Interesting research topics encourage respondents to complete the survey on time. The problem should be vague enough that you can create plenty of the right research questions. You don't want your topic to be so specific that you can't produce enough questions to gather the needed data.
• Conduct rough research on your topic: Conduct primary research to analyze what information is available and what can be explored. This way, you can decide which case is most likely to achieve the best results based on what data is not currently available.
• Keep the target audience in mind: You must keep your target audience in mind and slowly narrow your research to a topic that caters to a particular set of people. It will help gather precise research information to make products and services customer-centric and boost your business.
• Frame appropriate questions: Draft a research questionnaire with open-ended and closed-ended questions to help you get the necessary information. You can use question framing to help you get the most information out of a respondent. For example, offer an open-ended and closed-ended questions about one particular product next to one another in your survey.
• Analyze these research questions: Once the questions are framed and ready to be sent out, you must analyze the questions' effectiveness. If there is room for improvement, these questions need to be revisited and reframed.
• Brainstorm the possible outcomes: After creating appropriate questions, you can map out your questions' potential responses. What types of answers are you expecting? Will they support your current plan? If not, what changes can you make to serve customers better based on their responses? This step helps prepare everyone involved in the survey and data analysis of a potential plan of action based on the study's top possible outcomes.

Three points to remember while writing research questions: Ordering your questions is vital to give a sense of flow to the survey. Always rank your items from simple concepts to more complex ones. Here are tips on how to write a research question.

• Right research questions start with a problem that needs to be solved.
• Research questions must be engaging enough for customers or employees to invest their time. At the same time, your questions need to provide data that can actually be used to better your brand or organization.
• Your questions should be straightforward to understand. It helps keep respondents engaged while also collecting the most accurate answers. If a respondent doesn't understand a problem, they may back out of the survey or choose an answer randomly.

What are examples of good research questions?

Clear, specific, pertinent, and capable of producing new knowledge with existing knowledge or insights are all characteristics of good research questions. Here are a few examples of good research questions from many disciplines:

• Question: What specifications would you like us to launch with our next mobile phone? The reason why it is a good research question: The question asks about a specific product. It will give respondents room to explain what they expect from an upcoming product.
• Question: What steps do you suggest to tackle the current situation of world poverty? The reason why it is a good research question: This question is simply put in practical terms so that the respondents can reply honestly to this open-ended question.
• Question: Among all our products, which one do you think is the most successful? The reason why it is a good research question: By asking respondents which product they think is most successful, you gain valuable insight into the perception of your various products.
• Question: How can online users deal with trolls on social networking websites? The reason why it is a broad research question: These are focused research questions that are well-constructed and understandable.
• Question: As a customer, what qualities in an organization appeal to you, and what can be done to make you stay loyal? The reason why it is a broad research question: The reason why it is a good research question: This question is complicated yet conveys the message.

It is important to ensure that research questions are specific, relevant, and attainable. Researchers can then begin with relevant questions that have the potential to make significant improvements to their respective professions.

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Organizing Your Social Sciences Research Paper

• The Research Problem/Question
• Purpose of Guide
• Design Flaws to Avoid
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• Glossary of Research Terms
• Reading Research Effectively
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A research problem is a definite or clear expression [statement] about an area of concern, a condition to be improved upon, a difficulty to be eliminated, or a troubling question that exists in scholarly literature, in theory, or within existing practice that points to a need for meaningful understanding and deliberate investigation. A research problem does not state how to do something, offer a vague or broad proposition, or present a value question. In the social and behavioral sciences, studies are most often framed around examining a problem that needs to be understood and resolved in order to improve society and the human condition.

Bryman, Alan. “The Research Question in Social Research: What is its Role?” International Journal of Social Research Methodology 10 (2007): 5-20; Guba, Egon G., and Yvonna S. Lincoln. “Competing Paradigms in Qualitative Research.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, editors. (Thousand Oaks, CA: Sage, 1994), pp. 105-117; Pardede, Parlindungan. “Identifying and Formulating the Research Problem." Research in ELT: Module 4 (October 2018): 1-13; Li, Yanmei, and Sumei Zhang. "Identifying the Research Problem." In Applied Research Methods in Urban and Regional Planning . (Cham, Switzerland: Springer International Publishing, 2022), pp. 13-21.

Importance of...

The purpose of a problem statement is to:

• Introduce the reader to the importance of the topic being studied . The reader is oriented to the significance of the study.
• Anchors the research questions, hypotheses, or assumptions to follow . It offers a concise statement about the purpose of your paper.
• Place the topic into a particular context that defines the parameters of what is to be investigated.
• Provide the framework for reporting the results and indicates what is probably necessary to conduct the study and explain how the findings will present this information.

In the social sciences, the research problem establishes the means by which you must answer the "So What?" question. This declarative question refers to a research problem surviving the relevancy test [the quality of a measurement procedure that provides repeatability and accuracy]. Note that answering the "So What?" question requires a commitment on your part to not only show that you have reviewed the literature, but that you have thoroughly considered the significance of the research problem and its implications applied to creating new knowledge and understanding or informing practice.

To survive the "So What" question, problem statements should possess the following attributes:

• Clarity and precision [a well-written statement does not make sweeping generalizations and irresponsible pronouncements; it also does include unspecific determinates like "very" or "giant"],
• Demonstrate a researchable topic or issue [i.e., feasibility of conducting the study is based upon access to information that can be effectively acquired, gathered, interpreted, synthesized, and understood],
• Identification of what would be studied, while avoiding the use of value-laden words and terms,
• Identification of an overarching question or small set of questions accompanied by key factors or variables,
• Identification of key concepts and terms,
• Articulation of the study's conceptual boundaries or parameters or limitations,
• Some generalizability in regards to applicability and bringing results into general use,
• Conveyance of the study's importance, benefits, and justification [i.e., regardless of the type of research, it is important to demonstrate that the research is not trivial],
• Does not have unnecessary jargon or overly complex sentence constructions; and,
• Conveyance of more than the mere gathering of descriptive data providing only a snapshot of the issue or phenomenon under investigation.

Bryman, Alan. “The Research Question in Social Research: What is its Role?” International Journal of Social Research Methodology 10 (2007): 5-20; Brown, Perry J., Allen Dyer, and Ross S. Whaley. "Recreation Research—So What?" Journal of Leisure Research 5 (1973): 16-24; Castellanos, Susie. Critical Writing and Thinking. The Writing Center. Dean of the College. Brown University; Ellis, Timothy J. and Yair Levy Nova. "Framework of Problem-Based Research: A Guide for Novice Researchers on the Development of a Research-Worthy Problem." Informing Science: the International Journal of an Emerging Transdiscipline 11 (2008); Thesis and Purpose Statements. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Thesis Statements. The Writing Center. University of North Carolina; Tips and Examples for Writing Thesis Statements. The Writing Lab and The OWL. Purdue University; Selwyn, Neil. "‘So What?’…A Question that Every Journal Article Needs to Answer." Learning, Media, and Technology 39 (2014): 1-5; Shoket, Mohd. "Research Problem: Identification and Formulation." International Journal of Research 1 (May 2014): 512-518.

Structure and Writing Style

I.  Types and Content

There are four general conceptualizations of a research problem in the social sciences:

• Casuist Research Problem -- this type of problem relates to the determination of right and wrong in questions of conduct or conscience by analyzing moral dilemmas through the application of general rules and the careful distinction of special cases.
• Difference Research Problem -- typically asks the question, “Is there a difference between two or more groups or treatments?” This type of problem statement is used when the researcher compares or contrasts two or more phenomena. This a common approach to defining a problem in the clinical social sciences or behavioral sciences.
• Descriptive Research Problem -- typically asks the question, "what is...?" with the underlying purpose to describe the significance of a situation, state, or existence of a specific phenomenon. This problem is often associated with revealing hidden or understudied issues.
• Relational Research Problem -- suggests a relationship of some sort between two or more variables to be investigated. The underlying purpose is to investigate specific qualities or characteristics that may be connected in some way.

A problem statement in the social sciences should contain :

• A lead-in that helps ensure the reader will maintain interest over the study,
• A declaration of originality [e.g., mentioning a knowledge void or a lack of clarity about a topic that will be revealed in the literature review of prior research],
• An indication of the central focus of the study [establishing the boundaries of analysis], and
• An explanation of the study's significance or the benefits to be derived from investigating the research problem.

NOTE :   A statement describing the research problem of your paper should not be viewed as a thesis statement that you may be familiar with from high school. Given the content listed above, a description of the research problem is usually a short paragraph in length.

II.  Sources of Problems for Investigation

The identification of a problem to study can be challenging, not because there's a lack of issues that could be investigated, but due to the challenge of formulating an academically relevant and researchable problem which is unique and does not simply duplicate the work of others. To facilitate how you might select a problem from which to build a research study, consider these sources of inspiration:

Deductions from Theory This relates to deductions made from social philosophy or generalizations embodied in life and in society that the researcher is familiar with. These deductions from human behavior are then placed within an empirical frame of reference through research. From a theory, the researcher can formulate a research problem or hypothesis stating the expected findings in certain empirical situations. The research asks the question: “What relationship between variables will be observed if theory aptly summarizes the state of affairs?” One can then design and carry out a systematic investigation to assess whether empirical data confirm or reject the hypothesis, and hence, the theory.

Interdisciplinary Perspectives Identifying a problem that forms the basis for a research study can come from academic movements and scholarship originating in disciplines outside of your primary area of study. This can be an intellectually stimulating exercise. A review of pertinent literature should include examining research from related disciplines that can reveal new avenues of exploration and analysis. An interdisciplinary approach to selecting a research problem offers an opportunity to construct a more comprehensive understanding of a very complex issue that any single discipline may be able to provide.

Interviewing Practitioners The identification of research problems about particular topics can arise from formal interviews or informal discussions with practitioners who provide insight into new directions for future research and how to make research findings more relevant to practice. Discussions with experts in the field, such as, teachers, social workers, health care providers, lawyers, business leaders, etc., offers the chance to identify practical, “real world” problems that may be understudied or ignored within academic circles. This approach also provides some practical knowledge which may help in the process of designing and conducting your study.

Personal Experience Don't undervalue your everyday experiences or encounters as worthwhile problems for investigation. Think critically about your own experiences and/or frustrations with an issue facing society or related to your community, your neighborhood, your family, or your personal life. This can be derived, for example, from deliberate observations of certain relationships for which there is no clear explanation or witnessing an event that appears harmful to a person or group or that is out of the ordinary.

Relevant Literature The selection of a research problem can be derived from a thorough review of pertinent research associated with your overall area of interest. This may reveal where gaps exist in understanding a topic or where an issue has been understudied. Research may be conducted to: 1) fill such gaps in knowledge; 2) evaluate if the methodologies employed in prior studies can be adapted to solve other problems; or, 3) determine if a similar study could be conducted in a different subject area or applied in a different context or to different study sample [i.e., different setting or different group of people]. Also, authors frequently conclude their studies by noting implications for further research; read the conclusion of pertinent studies because statements about further research can be a valuable source for identifying new problems to investigate. The fact that a researcher has identified a topic worthy of further exploration validates the fact it is worth pursuing.

III.  What Makes a Good Research Statement?

A good problem statement begins by introducing the broad area in which your research is centered, gradually leading the reader to the more specific issues you are investigating. The statement need not be lengthy, but a good research problem should incorporate the following features:

1.  Compelling Topic The problem chosen should be one that motivates you to address it but simple curiosity is not a good enough reason to pursue a research study because this does not indicate significance. The problem that you choose to explore must be important to you, but it must also be viewed as important by your readers and to a the larger academic and/or social community that could be impacted by the results of your study. 2.  Supports Multiple Perspectives The problem must be phrased in a way that avoids dichotomies and instead supports the generation and exploration of multiple perspectives. A general rule of thumb in the social sciences is that a good research problem is one that would generate a variety of viewpoints from a composite audience made up of reasonable people. 3.  Researchability This isn't a real word but it represents an important aspect of creating a good research statement. It seems a bit obvious, but you don't want to find yourself in the midst of investigating a complex research project and realize that you don't have enough prior research to draw from for your analysis. There's nothing inherently wrong with original research, but you must choose research problems that can be supported, in some way, by the resources available to you. If you are not sure if something is researchable, don't assume that it isn't if you don't find information right away--seek help from a librarian !

NOTE:   Do not confuse a research problem with a research topic. A topic is something to read and obtain information about, whereas a problem is something to be solved or framed as a question raised for inquiry, consideration, or solution, or explained as a source of perplexity, distress, or vexation. In short, a research topic is something to be understood; a research problem is something that needs to be investigated.

IV.  Asking Analytical Questions about the Research Problem

Research problems in the social and behavioral sciences are often analyzed around critical questions that must be investigated. These questions can be explicitly listed in the introduction [i.e., "This study addresses three research questions about women's psychological recovery from domestic abuse in multi-generational home settings..."], or, the questions are implied in the text as specific areas of study related to the research problem. Explicitly listing your research questions at the end of your introduction can help in designing a clear roadmap of what you plan to address in your study, whereas, implicitly integrating them into the text of the introduction allows you to create a more compelling narrative around the key issues under investigation. Either approach is appropriate.

The number of questions you attempt to address should be based on the complexity of the problem you are investigating and what areas of inquiry you find most critical to study. Practical considerations, such as, the length of the paper you are writing or the availability of resources to analyze the issue can also factor in how many questions to ask. In general, however, there should be no more than four research questions underpinning a single research problem.

Given this, well-developed analytical questions can focus on any of the following:

• Highlights a genuine dilemma, area of ambiguity, or point of confusion about a topic open to interpretation by your readers;
• Yields an answer that is unexpected and not obvious rather than inevitable and self-evident;
• Provokes meaningful thought or discussion;
• Raises the visibility of the key ideas or concepts that may be understudied or hidden;
• Suggests the need for complex analysis or argument rather than a basic description or summary; and,
• Offers a specific path of inquiry that avoids eliciting generalizations about the problem.

NOTE:   Questions of how and why concerning a research problem often require more analysis than questions about who, what, where, and when. You should still ask yourself these latter questions, however. Thinking introspectively about the who, what, where, and when of a research problem can help ensure that you have thoroughly considered all aspects of the problem under investigation and helps define the scope of the study in relation to the problem.

V.  Mistakes to Avoid

Beware of circular reasoning! Do not state the research problem as simply the absence of the thing you are suggesting. For example, if you propose the following, "The problem in this community is that there is no hospital," this only leads to a research problem where:

• The need is for a hospital
• The objective is to create a hospital
• The method is to plan for building a hospital, and
• The evaluation is to measure if there is a hospital or not.

This is an example of a research problem that fails the "So What?" test . In this example, the problem does not reveal the relevance of why you are investigating the fact there is no hospital in the community [e.g., perhaps there's a hospital in the community ten miles away]; it does not elucidate the significance of why one should study the fact there is no hospital in the community [e.g., that hospital in the community ten miles away has no emergency room]; the research problem does not offer an intellectual pathway towards adding new knowledge or clarifying prior knowledge [e.g., the county in which there is no hospital already conducted a study about the need for a hospital, but it was conducted ten years ago]; and, the problem does not offer meaningful outcomes that lead to recommendations that can be generalized for other situations or that could suggest areas for further research [e.g., the challenges of building a new hospital serves as a case study for other communities].

Alvesson, Mats and Jörgen Sandberg. “Generating Research Questions Through Problematization.” Academy of Management Review 36 (April 2011): 247-271 ; Choosing and Refining Topics. Writing@CSU. Colorado State University; D'Souza, Victor S. "Use of Induction and Deduction in Research in Social Sciences: An Illustration." Journal of the Indian Law Institute 24 (1982): 655-661; Ellis, Timothy J. and Yair Levy Nova. "Framework of Problem-Based Research: A Guide for Novice Researchers on the Development of a Research-Worthy Problem." Informing Science: the International Journal of an Emerging Transdiscipline 11 (2008); How to Write a Research Question. The Writing Center. George Mason University; Invention: Developing a Thesis Statement. The Reading/Writing Center. Hunter College; Problem Statements PowerPoint Presentation. The Writing Lab and The OWL. Purdue University; Procter, Margaret. Using Thesis Statements. University College Writing Centre. University of Toronto; Shoket, Mohd. "Research Problem: Identification and Formulation." International Journal of Research 1 (May 2014): 512-518; Trochim, William M.K. Problem Formulation. Research Methods Knowledge Base. 2006; Thesis and Purpose Statements. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Thesis Statements. The Writing Center. University of North Carolina; Tips and Examples for Writing Thesis Statements. The Writing Lab and The OWL. Purdue University; Pardede, Parlindungan. “Identifying and Formulating the Research Problem." Research in ELT: Module 4 (October 2018): 1-13; Walk, Kerry. Asking an Analytical Question. [Class handout or worksheet]. Princeton University; White, Patrick. Developing Research Questions: A Guide for Social Scientists . New York: Palgrave McMillan, 2009; Li, Yanmei, and Sumei Zhang. "Identifying the Research Problem." In Applied Research Methods in Urban and Regional Planning . (Cham, Switzerland: Springer International Publishing, 2022), pp. 13-21.

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• v.53(4); 2010 Aug

Research questions, hypotheses and objectives

Patricia farrugia.

* Michael G. DeGroote School of Medicine, the

Bradley A. Petrisor

† Division of Orthopaedic Surgery and the

Forough Farrokhyar

‡ Departments of Surgery and

§ Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ont

Mohit Bhandari

There is an increasing familiarity with the principles of evidence-based medicine in the surgical community. As surgeons become more aware of the hierarchy of evidence, grades of recommendations and the principles of critical appraisal, they develop an increasing familiarity with research design. Surgeons and clinicians are looking more and more to the literature and clinical trials to guide their practice; as such, it is becoming a responsibility of the clinical research community to attempt to answer questions that are not only well thought out but also clinically relevant. The development of the research question, including a supportive hypothesis and objectives, is a necessary key step in producing clinically relevant results to be used in evidence-based practice. A well-defined and specific research question is more likely to help guide us in making decisions about study design and population and subsequently what data will be collected and analyzed. 1

Objectives of this article

In this article, we discuss important considerations in the development of a research question and hypothesis and in defining objectives for research. By the end of this article, the reader will be able to appreciate the significance of constructing a good research question and developing hypotheses and research objectives for the successful design of a research study. The following article is divided into 3 sections: research question, research hypothesis and research objectives.

Research question

Interest in a particular topic usually begins the research process, but it is the familiarity with the subject that helps define an appropriate research question for a study. 1 Questions then arise out of a perceived knowledge deficit within a subject area or field of study. 2 Indeed, Haynes suggests that it is important to know “where the boundary between current knowledge and ignorance lies.” 1 The challenge in developing an appropriate research question is in determining which clinical uncertainties could or should be studied and also rationalizing the need for their investigation.

Increasing one’s knowledge about the subject of interest can be accomplished in many ways. Appropriate methods include systematically searching the literature, in-depth interviews and focus groups with patients (and proxies) and interviews with experts in the field. In addition, awareness of current trends and technological advances can assist with the development of research questions. 2 It is imperative to understand what has been studied about a topic to date in order to further the knowledge that has been previously gathered on a topic. Indeed, some granting institutions (e.g., Canadian Institute for Health Research) encourage applicants to conduct a systematic review of the available evidence if a recent review does not already exist and preferably a pilot or feasibility study before applying for a grant for a full trial.

In-depth knowledge about a subject may generate a number of questions. It then becomes necessary to ask whether these questions can be answered through one study or if more than one study needed. 1 Additional research questions can be developed, but several basic principles should be taken into consideration. 1 All questions, primary and secondary, should be developed at the beginning and planning stages of a study. Any additional questions should never compromise the primary question because it is the primary research question that forms the basis of the hypothesis and study objectives. It must be kept in mind that within the scope of one study, the presence of a number of research questions will affect and potentially increase the complexity of both the study design and subsequent statistical analyses, not to mention the actual feasibility of answering every question. 1 A sensible strategy is to establish a single primary research question around which to focus the study plan. 3 In a study, the primary research question should be clearly stated at the end of the introduction of the grant proposal, and it usually specifies the population to be studied, the intervention to be implemented and other circumstantial factors. 4

Hulley and colleagues 2 have suggested the use of the FINER criteria in the development of a good research question ( Box 1 ). The FINER criteria highlight useful points that may increase the chances of developing a successful research project. A good research question should specify the population of interest, be of interest to the scientific community and potentially to the public, have clinical relevance and further current knowledge in the field (and of course be compliant with the standards of ethical boards and national research standards).

FINER criteria for a good research question

Adapted with permission from Wolters Kluwer Health. 2

Whereas the FINER criteria outline the important aspects of the question in general, a useful format to use in the development of a specific research question is the PICO format — consider the population (P) of interest, the intervention (I) being studied, the comparison (C) group (or to what is the intervention being compared) and the outcome of interest (O). 3 , 5 , 6 Often timing (T) is added to PICO ( Box 2 ) — that is, “Over what time frame will the study take place?” 1 The PICOT approach helps generate a question that aids in constructing the framework of the study and subsequently in protocol development by alluding to the inclusion and exclusion criteria and identifying the groups of patients to be included. Knowing the specific population of interest, intervention (and comparator) and outcome of interest may also help the researcher identify an appropriate outcome measurement tool. 7 The more defined the population of interest, and thus the more stringent the inclusion and exclusion criteria, the greater the effect on the interpretation and subsequent applicability and generalizability of the research findings. 1 , 2 A restricted study population (and exclusion criteria) may limit bias and increase the internal validity of the study; however, this approach will limit external validity of the study and, thus, the generalizability of the findings to the practical clinical setting. Conversely, a broadly defined study population and inclusion criteria may be representative of practical clinical practice but may increase bias and reduce the internal validity of the study.

PICOT criteria 1

A poorly devised research question may affect the choice of study design, potentially lead to futile situations and, thus, hamper the chance of determining anything of clinical significance, which will then affect the potential for publication. Without devoting appropriate resources to developing the research question, the quality of the study and subsequent results may be compromised. During the initial stages of any research study, it is therefore imperative to formulate a research question that is both clinically relevant and answerable.

Research hypothesis

The primary research question should be driven by the hypothesis rather than the data. 1 , 2 That is, the research question and hypothesis should be developed before the start of the study. This sounds intuitive; however, if we take, for example, a database of information, it is potentially possible to perform multiple statistical comparisons of groups within the database to find a statistically significant association. This could then lead one to work backward from the data and develop the “question.” This is counterintuitive to the process because the question is asked specifically to then find the answer, thus collecting data along the way (i.e., in a prospective manner). Multiple statistical testing of associations from data previously collected could potentially lead to spuriously positive findings of association through chance alone. 2 Therefore, a good hypothesis must be based on a good research question at the start of a trial and, indeed, drive data collection for the study.

The research or clinical hypothesis is developed from the research question and then the main elements of the study — sampling strategy, intervention (if applicable), comparison and outcome variables — are summarized in a form that establishes the basis for testing, statistical and ultimately clinical significance. 3 For example, in a research study comparing computer-assisted acetabular component insertion versus freehand acetabular component placement in patients in need of total hip arthroplasty, the experimental group would be computer-assisted insertion and the control/conventional group would be free-hand placement. The investigative team would first state a research hypothesis. This could be expressed as a single outcome (e.g., computer-assisted acetabular component placement leads to improved functional outcome) or potentially as a complex/composite outcome; that is, more than one outcome (e.g., computer-assisted acetabular component placement leads to both improved radiographic cup placement and improved functional outcome).

However, when formally testing statistical significance, the hypothesis should be stated as a “null” hypothesis. 2 The purpose of hypothesis testing is to make an inference about the population of interest on the basis of a random sample taken from that population. The null hypothesis for the preceding research hypothesis then would be that there is no difference in mean functional outcome between the computer-assisted insertion and free-hand placement techniques. After forming the null hypothesis, the researchers would form an alternate hypothesis stating the nature of the difference, if it should appear. The alternate hypothesis would be that there is a difference in mean functional outcome between these techniques. At the end of the study, the null hypothesis is then tested statistically. If the findings of the study are not statistically significant (i.e., there is no difference in functional outcome between the groups in a statistical sense), we cannot reject the null hypothesis, whereas if the findings were significant, we can reject the null hypothesis and accept the alternate hypothesis (i.e., there is a difference in mean functional outcome between the study groups), errors in testing notwithstanding. In other words, hypothesis testing confirms or refutes the statement that the observed findings did not occur by chance alone but rather occurred because there was a true difference in outcomes between these surgical procedures. The concept of statistical hypothesis testing is complex, and the details are beyond the scope of this article.

Another important concept inherent in hypothesis testing is whether the hypotheses will be 1-sided or 2-sided. A 2-sided hypothesis states that there is a difference between the experimental group and the control group, but it does not specify in advance the expected direction of the difference. For example, we asked whether there is there an improvement in outcomes with computer-assisted surgery or whether the outcomes worse with computer-assisted surgery. We presented a 2-sided test in the above example because we did not specify the direction of the difference. A 1-sided hypothesis states a specific direction (e.g., there is an improvement in outcomes with computer-assisted surgery). A 2-sided hypothesis should be used unless there is a good justification for using a 1-sided hypothesis. As Bland and Atlman 8 stated, “One-sided hypothesis testing should never be used as a device to make a conventionally nonsignificant difference significant.”

The research hypothesis should be stated at the beginning of the study to guide the objectives for research. Whereas the investigators may state the hypothesis as being 1-sided (there is an improvement with treatment), the study and investigators must adhere to the concept of clinical equipoise. According to this principle, a clinical (or surgical) trial is ethical only if the expert community is uncertain about the relative therapeutic merits of the experimental and control groups being evaluated. 9 It means there must exist an honest and professional disagreement among expert clinicians about the preferred treatment. 9

Designing a research hypothesis is supported by a good research question and will influence the type of research design for the study. Acting on the principles of appropriate hypothesis development, the study can then confidently proceed to the development of the research objective.

Research objective

The primary objective should be coupled with the hypothesis of the study. Study objectives define the specific aims of the study and should be clearly stated in the introduction of the research protocol. 7 From our previous example and using the investigative hypothesis that there is a difference in functional outcomes between computer-assisted acetabular component placement and free-hand placement, the primary objective can be stated as follows: this study will compare the functional outcomes of computer-assisted acetabular component insertion versus free-hand placement in patients undergoing total hip arthroplasty. Note that the study objective is an active statement about how the study is going to answer the specific research question. Objectives can (and often do) state exactly which outcome measures are going to be used within their statements. They are important because they not only help guide the development of the protocol and design of study but also play a role in sample size calculations and determining the power of the study. 7 These concepts will be discussed in other articles in this series.

From the surgeon’s point of view, it is important for the study objectives to be focused on outcomes that are important to patients and clinically relevant. For example, the most methodologically sound randomized controlled trial comparing 2 techniques of distal radial fixation would have little or no clinical impact if the primary objective was to determine the effect of treatment A as compared to treatment B on intraoperative fluoroscopy time. However, if the objective was to determine the effect of treatment A as compared to treatment B on patient functional outcome at 1 year, this would have a much more significant impact on clinical decision-making. Second, more meaningful surgeon–patient discussions could ensue, incorporating patient values and preferences with the results from this study. 6 , 7 It is the precise objective and what the investigator is trying to measure that is of clinical relevance in the practical setting.

The following is an example from the literature about the relation between the research question, hypothesis and study objectives:

Study: Warden SJ, Metcalf BR, Kiss ZS, et al. Low-intensity pulsed ultrasound for chronic patellar tendinopathy: a randomized, double-blind, placebo-controlled trial. Rheumatology 2008;47:467–71.

Research question: How does low-intensity pulsed ultrasound (LIPUS) compare with a placebo device in managing the symptoms of skeletally mature patients with patellar tendinopathy?

Research hypothesis: Pain levels are reduced in patients who receive daily active-LIPUS (treatment) for 12 weeks compared with individuals who receive inactive-LIPUS (placebo).

Objective: To investigate the clinical efficacy of LIPUS in the management of patellar tendinopathy symptoms.

The development of the research question is the most important aspect of a research project. A research project can fail if the objectives and hypothesis are poorly focused and underdeveloped. Useful tips for surgical researchers are provided in Box 3 . Designing and developing an appropriate and relevant research question, hypothesis and objectives can be a difficult task. The critical appraisal of the research question used in a study is vital to the application of the findings to clinical practice. Focusing resources, time and dedication to these 3 very important tasks will help to guide a successful research project, influence interpretation of the results and affect future publication efforts.

Tips for developing research questions, hypotheses and objectives for research studies

• Perform a systematic literature review (if one has not been done) to increase knowledge and familiarity with the topic and to assist with research development.
• Learn about current trends and technological advances on the topic.
• Seek careful input from experts, mentors, colleagues and collaborators to refine your research question as this will aid in developing the research question and guide the research study.
• Use the FINER criteria in the development of the research question.
• Ensure that the research question follows PICOT format.
• Develop a research hypothesis from the research question.
• Develop clear and well-defined primary and secondary (if needed) objectives.
• Ensure that the research question and objectives are answerable, feasible and clinically relevant.

FINER = feasible, interesting, novel, ethical, relevant; PICOT = population (patients), intervention (for intervention studies only), comparison group, outcome of interest, time.

Competing interests: No funding was received in preparation of this paper. Dr. Bhandari was funded, in part, by a Canada Research Chair, McMaster University.

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1-Research Questions

1. The Purpose of Research Questions

Both professional researchers and successful student researchers develop research questions. That’s because research questions are more than handy tools; they are essential to the research process.

By defining exactly what the researcher is trying to find out, these questions influence most of the rest of the steps taken to conduct the research. That’s true even if the research is not for academic purposes but for other areas of our lives.

For instance, if you’re seeking information about a health problem in order to learn whether you have anything to worry about, research questions will make it possible for you to more effectively decide whether to seek medical help–and how quickly.

Or, if you’re researching a potential employer, having developed and used research questions will mean you’re able to more confidently decide whether to apply for an internship or job there.

The confidence you’ll have when making such decisions will come from knowing that the information they’re based on was gathered by conscious thought rather than serendipity and whim.

Choosing & Using Sources: A Guide to Academic Research Copyright © 2015 by Teaching & Learning, Ohio State University Libraries is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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Scientists use generative AI to answer complex questions in physics

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When water freezes, it transitions from a liquid phase to a solid phase, resulting in a drastic change in properties like density and volume. Phase transitions in water are so common most of us probably don’t even think about them, but phase transitions in novel materials or complex physical systems are an important area of study.

To fully understand these systems, scientists must be able to recognize phases and detect the transitions between. But how to quantify phase changes in an unknown system is often unclear, especially when data are scarce.

Researchers from MIT and the University of Basel in Switzerland applied generative artificial intelligence models to this problem, developing a new machine-learning framework that can automatically map out phase diagrams for novel physical systems.

Their physics-informed machine-learning approach is more efficient than laborious, manual techniques which rely on theoretical expertise. Importantly, because their approach leverages generative models, it does not require huge, labeled training datasets used in other machine-learning techniques.

Such a framework could help scientists investigate the thermodynamic properties of novel materials or detect entanglement in quantum systems, for instance. Ultimately, this technique could make it possible for scientists to discover unknown phases of matter autonomously.

“If you have a new system with fully unknown properties, how would you choose which observable quantity to study? The hope, at least with data-driven tools, is that you could scan large new systems in an automated way, and it will point you to important changes in the system. This might be a tool in the pipeline of automated scientific discovery of new, exotic properties of phases,” says Frank Schäfer, a postdoc in the Julia Lab in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and co-author of a paper on this approach.

Joining Schäfer on the paper are first author Julian Arnold, a graduate student at the University of Basel; Alan Edelman, applied mathematics professor in the Department of Mathematics and leader of the Julia Lab; and senior author Christoph Bruder, professor in the Department of Physics at the University of Basel. The research is published today in Physical Review Letters.

Detecting phase transitions using AI

While water transitioning to ice might be among the most obvious examples of a phase change, more exotic phase changes, like when a material transitions from being a normal conductor to a superconductor, are of keen interest to scientists.

These transitions can be detected by identifying an “order parameter,” a quantity that is important and expected to change. For instance, water freezes and transitions to a solid phase (ice) when its temperature drops below 0 degrees Celsius. In this case, an appropriate order parameter could be defined in terms of the proportion of water molecules that are part of the crystalline lattice versus those that remain in a disordered state.

In the past, researchers have relied on physics expertise to build phase diagrams manually, drawing on theoretical understanding to know which order parameters are important. Not only is this tedious for complex systems, and perhaps impossible for unknown systems with new behaviors, but it also introduces human bias into the solution.

More recently, researchers have begun using machine learning to build discriminative classifiers that can solve this task by learning to classify a measurement statistic as coming from a particular phase of the physical system, the same way such models classify an image as a cat or dog.

The MIT researchers demonstrated how generative models can be used to solve this classification task much more efficiently, and in a physics-informed manner.

The Julia Programming Language , a popular language for scientific computing that is also used in MIT’s introductory linear algebra classes, offers many tools that make it invaluable for constructing such generative models, Schäfer adds.

Generative models, like those that underlie ChatGPT and Dall-E, typically work by estimating the probability distribution of some data, which they use to generate new data points that fit the distribution (such as new cat images that are similar to existing cat images).

However, when simulations of a physical system using tried-and-true scientific techniques are available, researchers get a model of its probability distribution for free. This distribution describes the measurement statistics of the physical system.

A more knowledgeable model

The MIT team’s insight is that this probability distribution also defines a generative model upon which a classifier can be constructed. They plug the generative model into standard statistical formulas to directly construct a classifier instead of learning it from samples, as was done with discriminative approaches.

“This is a really nice way of incorporating something you know about your physical system deep inside your machine-learning scheme. It goes far beyond just performing feature engineering on your data samples or simple inductive biases,” Schäfer says.

This generative classifier can determine what phase the system is in given some parameter, like temperature or pressure. And because the researchers directly approximate the probability distributions underlying measurements from the physical system, the classifier has system knowledge.

This enables their method to perform better than other machine-learning techniques. And because it can work automatically without the need for extensive training, their approach significantly enhances the computational efficiency of identifying phase transitions.

At the end of the day, similar to how one might ask ChatGPT to solve a math problem, the researchers can ask the generative classifier questions like “does this sample belong to phase I or phase II?” or “was this sample generated at high temperature or low temperature?”

Scientists could also use this approach to solve different binary classification tasks in physical systems, possibly to detect entanglement in quantum systems (Is the state entangled or not?) or determine whether theory A or B is best suited to solve a particular problem. They could also use this approach to better understand and improve large language models like ChatGPT by identifying how certain parameters should be tuned so the chatbot gives the best outputs.

In the future, the researchers also want to study theoretical guarantees regarding how many measurements they would need to effectively detect phase transitions and estimate the amount of computation that would require.

This work was funded, in part, by the Swiss National Science Foundation, the MIT-Switzerland Lockheed Martin Seed Fund, and MIT International Science and Technology Initiatives.

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Researchers at MIT and elsewhere have developed a new machine-learning model capable of “predicting a physical system’s phase or state,” report Kyle Wiggers and Devin Coldewey for TechCrunch . 

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As the FDA evaluates ecstasy treatment for PTSD, questions mount about the evidence

Research on MDMA has shown it can be effective for PTSD, but approval of the treatment isn't yet guaranteed. The Washington Post via Getty Images hide caption

Research on MDMA has shown it can be effective for PTSD, but approval of the treatment isn't yet guaranteed.

In a matter of months, the Food and Drug Administration is expected to decide whether the drug commonly known as ecstasy can be used as a treatment for post-traumatic stress disorder.

An approval by the agency would represent an enormous milestone for the movement to bring psychedelics into the mainstream of mental health care. An FDA rejection of MDMA, the abbreviation of the drug's chemical name, would deal a major setback to the effort.

Clinical trials have inspired optimism in the drug for its potential to help the millions of Americans who experience PTSD. Accounts from some of those who've participated in the trials describe the treatment as transformational.

But new and troubling questions about this research are now threatening to upset the final stretch in the drug's path to market.

The allegations surfaced in a draft report released in March by the Institute for Clinical and Economic Review , a nonprofit that evaluates clinical trials and drug prices, which found "substantial concerns about the validity of the results" of the MDMA clinical trials.

The ICER report was followed in April by a citizen petition to the FDA. In that document, a group of concerned people allege possible misconduct and ethical violations that could compromise the MDMA research. The petition asked the agency to hold a public meeting to address the concerns.

If true, the claims could jeopardize the drug's chances of receiving FDA approval, a decision that is expected to come by early August .

"There's the possibility that the data might not be representative of what's actually happened in clinical trials," says Neşe Devenot , one of the authors of the citizen petition and a senior lecturer in the writing program at Johns Hopkins University who is involved in psychedelic research. "I don't think this has been publicly reckoned with."

That may soon happen. The FDA announced Thursday that it plans to hold a public advisory committee meeting on MDMA-assisted therapy on June 4.

At the heart of the controversy are the organizations that have pioneered research into MDMA: the Multidisciplinary Association for Psychedelic Studies , and the public benefit corporation incubated by MAPS, which was recently rebranded as Lykos Therapeutics .

Lykos sponsored the clinical trials of MDMA. The results are included in the company's application to the FDA seeking approval to market the drug for therapy-assisted PTSD treatment.

Researchers and clinicians involved in the trials have pushed back strongly against the accusations that their clinical data isn't sound.

Jennifer Mitchell , lead author of the published papers from the Phase 3 trials, says she stands behind their findings.

"I didn't feel any pressure from the sponsor to come up with anything different than what the data was providing," says Mitchell, a professor of neurology and psychiatry at the University of California, San Francisco and associate chief of staff for research at the San Francisco VA Medical Center. "I wouldn't have continued to work with them if I had felt that."

Promising MDMA research for PTSD

The Phase 3 trials evaluated MDMA-assisted therapy, a protocol in which the drug is given under the supervision of two therapists.

In the second stage of the trials , 94 people with moderate and severe PTSD received either the drug or a placebo during three sessions, each spaced a month apart. There were also follow up "integration" sessions to help people process their experiences while on MDMA.

By the end of the trial, about 71% of participants in the MDMA arm no longer met the diagnostic criteria for PTSD, compared to about 48% who underwent the same therapy but took a placebo instead. Those findings built on promising results from earlier studies .

The study documented various adverse events in both groups — ranging from nausea and anxiety to heart palpitations — but none of them qualified as serious. The treatment was "generally well tolerated."

"Consistent with PTSD, suicidal ideation was observed in both groups," the authors reported in the journal Nature Medicine , "MDMA did not appear to increase this risk, and no suicidal behavior was observed."

Casey Tylek, a participant in the Phase 3 trials, says he had no experience with the drug prior to the study.

Tylek was in the placebo group, but was later given the opportunity to undergo the therapy with MDMA.

"It was incredibly powerful," says Tylek, a veteran who lives in Massachusetts, "I truly don't know if I would be alive today if I hadn't gone through that trial."

ICER report raises concerns

In its report , ICER acknowledges that the MDMA data suggest it would be an "important addition to treatment options for PTSD," but it questions whether the published findings tell the full story.

Among the concerns, the ICER report details a well-known challenge in psychedelic research around how to make sure study participants don't know if they got the experimental treatment or a placebo. Most of those in the MDMA group were able to identify they had received the drug. It also suggests the method used to assess PTSD — considered the gold-standard — showed improvements in symptoms after the treatment, even though some people were worse overall.

Beyond that, however, the report brings up the possibility that "very strong prior beliefs" among therapists, investigators and patients influenced the results.

"Concerns have been raised by some that therapists encouraged favorable reports by patients and discouraged negative reports by patients including discouraging reports of substantial harms, potentially biasing the recording of benefits and harms," the report states.

ICER does not identify the sources who were interviewed, although it did include two trial participants, a "trial therapist" and those who worked on a podcast called Cover Story , says Dr. David Rind , the chief medical officer for ICER.

"This was a very unusual review," says Rind.

The podcast, produced by New York Magazine and the nonprofit media organization Psymposia , brought to light claims by a participant named Meaghan Buisson, who appeared in a video of two therapists , a married couple, engaged in what Buisson described as inappropriate physical contact while she was under the influence of MDMA at a Phase 2 trial site in Canada.

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This psychedelics researcher approached his death with calm and curiosity.

MAPS determined the therapists "substantially deviated" from the treatment manual. The organization also barred the two therapists from becoming providers of MDMA-assisted therapy in affiliation with MAPS, and health authorities were notified in Canada and the U.S.

The podcast also interviewed two people (their full names were not revealed) who said they received MDMA in the large-scale, or Phase 3, trials and experienced feelings of suicidality and other distress after the studies.

The ICER report is yet to be finalized, but Rind says their analysis showed "there's still a lot of uncertainty" about the treatment.

"You have a group of people who are very upset about how these trials went," he says. "We couldn't tell, even though we talked with people where this happened, whether that represents a tiny fraction of bad events or a number of bad events large enough to have rendered the trial just not believable."

Pushback against the allegations

According to Rind, MAPS and Lykos had "very little" engagement with ICER on the draft report.

But since then, a group of more than 70 clinicians, investigators and others involved in the Phase 3 MDMA trials have published a detailed response , saying that certain aspects of the trials were "misrepresented" and that a number of assertions amount to "hearsay."

Willa Hall , a clinical psychologist in the Phase 3 trials, says she and her colleagues were shocked by how ICER described their work.

"I didn't recognize the study that they were talking about," Hall told NPR. "I think a lot of us felt quite insulted actually by that characterization. I saw nothing like that. I only saw professionalism ."

In their response, Hall and her colleagues write that "[ICER] does not note the many measures taken to train, support, and evaluate therapists on those trials—measures that met, and in some cases exceeded, the accepted standards in the field of psychotherapy research."

They also take issue with ICER relying on "a small number of undisclosed study participants and unnamed 'experts' rather than validated research outcomes." The critiques that participants knew they received the treatment or that the measure of PTSD symptoms might not capture someone's overall condition would also apply to other clinical trials, unrelated to MDMA, they say.

UCSF's Jennifer Mitchell says the clinical trial was designed to safeguard against bias.

Therapists on site were not collecting key data from participants about their PTSD symptoms following the sessions. Instead, that was being done online by "independent assessors" who didn't know who had received the treatment or a placebo.

Hall says therapists "meticulously" captured any adverse events. "We encouraged our participants to be very honest," she says. "We're all invested in knowing how it works and what are the risks for people."

Still, Mitchell acknowledges she doesn't have full insight into what was going on at each trial site on a given day.

"This is my own frustration," she says. "I can't attest to what was happening at one of the sites in Israel on a day to day basis, or on one of the sites in Canada."

But she contends that ICER tried to conduct an investigation without access to the full data.

Luminous: A Series About Psychedelics from 'To The Best Of Our Knowledge'

The FDA granted MDMA "breakthrough therapy" status, she says, which means the agency was involved in the study design and "many aspects" of the trial.

"So there's no keeping things from the FDA," Mitchell says.

The ICER report points out that therapists and participants in the study were "pulled heavily from the existing community of those interested and involved in the use of psychedelics for possible psychological benefits."

For her part though, Mitchell says she's not what some would call a "true believer."

"My personal feeling is that psychedelics are complicated compounds and they do not work for everyone," she says.

Petition adds to controversy ahead of the FDA meeting

On the heels of the ICER report, Neşe Devenot and four others, including Meaghan Buisson, submitted the citizen petition to the FDA calling for a public advisory meeting about the Lykos' application for MDMA.

In it, they ask for extended time for stakeholders who are concerned about the "risks and shortcomings" of the research.

"Evidence from multiple sources indicates that the sponsor has engaged in a pattern of systematic and deliberate omission of adverse events from the public record while minimizing documented harms," the petition states.

It continues: "We cannot rule out the possibility that MAPS/Lykos manipulated clinical trial data to hide adverse events from regulatory agencies."

The petition cites media reports and public statements from figures at Lykos and MAPS — and disclosures from a former employee of the MAPS public benefit corporation "who prefers to maintain anonymity at this juncture."

In addition, the petition alleges that clinical trial investigators would phone MAPS in the event of an incident during the trial to see whether that should be reported as an adverse event and that a suicide attempt during a dosing session was discouraged from being reported.

In an email to NPR, a spokesperson for MAPS rejects the claim.

It's not clear if the FDA's decision to hold a meeting was influenced by Devenot's petition, which has over 80 signatures .

Alaina Jaster , who has a doctorate in pharmacology and toxicology, is another author of the petition.

"We need to listen to people [in the trials] who are having these experiences, instead of telling them that they are liars and that they're going to ruin the psychedelic renaissance," says Jaster who hosts a podcast on psychedelics.

"None of us are against this as a useful tool, or none of us are against treating mental health. We don't have any monetary interests in this not going through," she says.

Neşe Devenot and Brian Pace, another author of the petition, are affiliated with Psymposia , the media organization that produced the podcast, but Devenot says they were not involved in the podcast and are unpaid board members.

In response to the petition's call for a public meeting, a spokesperson for Lykos sent NPR a statement in April saying the company supports holding an advisory meeting. "The voice of the PTSD patient is incredibly important," the email reads.

Shots - Health News

Psychedelic drugs may launch a new era in psychiatric treatment, brain scientists say.

MAPS "remains fully supportive of comprehensive, high-quality research; careful analysis of safety and efficacy; and stringent regulatory oversight of any psychedelic-assisted therapy research or delivery," according to the statement it also sent to NPR in April. "We stand behind Lykos' execution of the clinical program and support the clinical results."

One of those who signed the petition after seeing it posted online is Dr. Boris Heifets , an anesthesiologist at Stanford University whose lab studies psychedelics, including MDMA.

"I don't know if the allegations are true, it just makes me deeply sad if there was actually malfeasance for such an important trial," says Heifets. "The MDMA Phase 3 trials were very important for mental health, important for a lot of people who may benefit from this therapy."

Learning about MAPS several decades ago was, in part, what inspired Heifets to get involved in this type of research.

He says he donates $100 a year to MAPS and that they have supplied his lab with MDMA. He also consults for one company that's developing a derivative of MDMA.

Heifets says the petition contains some "very strong allegations," particularly the claim that certain adverse events were not disclosed.

"I want to hear MAPS respond," he says. " I would really like to understand the risk profile of this drug before it's approved, not after."

• psychedelic drugs
• psychedelics
• clinical trials
• mdma therapy

Facility for Rare Isotope Beams

At michigan state university, international research team uses wavefunction matching to solve quantum many-body problems, new approach makes calculations with realistic interactions possible.

FRIB researchers are part of an international research team solving challenging computational problems in quantum physics using a new method called wavefunction matching. The new approach has applications to fields such as nuclear physics, where it is enabling theoretical calculations of atomic nuclei that were previously not possible. The details are published in Nature (“Wavefunction matching for solving quantum many-body problems”) .

Ab initio methods and their computational challenges

An ab initio method describes a complex system by starting from a description of its elementary components and their interactions. For the case of nuclear physics, the elementary components are protons and neutrons. Some key questions that ab initio calculations can help address are the binding energies and properties of atomic nuclei not yet observed and linking nuclear structure to the underlying interactions among protons and neutrons.

Yet, some ab initio methods struggle to produce reliable calculations for systems with complex interactions. One such method is quantum Monte Carlo simulations. In quantum Monte Carlo simulations, quantities are computed using random or stochastic processes. While quantum Monte Carlo simulations can be efficient and powerful, they have a significant weakness: the sign problem. The sign problem develops when positive and negative weight contributions cancel each other out. This cancellation results in inaccurate final predictions. It is often the case that quantum Monte Carlo simulations can be performed for an approximate or simplified interaction, but the corresponding simulations for realistic interactions produce severe sign problems and are therefore not possible.

Using ‘plastic surgery’ to make calculations possible

The new wavefunction-matching approach is designed to solve such computational problems. The research team—from Gaziantep Islam Science and Technology University in Turkey; University of Bonn, Ruhr University Bochum, and Forschungszentrum Jülich in Germany; Institute for Basic Science in South Korea; South China Normal University, Sun Yat-Sen University, and Graduate School of China Academy of Engineering Physics in China; Tbilisi State University in Georgia; CEA Paris-Saclay and Université Paris-Saclay in France; and Mississippi State University and the Facility for Rare Isotope Beams (FRIB) at Michigan State University (MSU)—includes  Dean Lee , professor of physics at FRIB and in MSU’s Department of Physics and Astronomy and head of the Theoretical Nuclear Science department at FRIB, and  Yuan-Zhuo Ma , postdoctoral research associate at FRIB.

“We are often faced with the situation that we can perform calculations using a simple approximate interaction, but realistic high-fidelity interactions cause severe computational problems,” said Lee. “Wavefunction matching solves this problem by doing plastic surgery. It removes the short-distance part of the high-fidelity interaction, and replaces it with the short-distance part of an easily computable interaction.”

This transformation is done in a way that preserves all of the important properties of the original realistic interaction. Since the new wavefunctions look similar to that of the easily computable interaction, researchers can now perform calculations using the easily computable interaction and apply a standard procedure for handling small corrections called perturbation theory.  A team effort

The research team applied this new method to lattice quantum Monte Carlo simulations for light nuclei, medium-mass nuclei, neutron matter, and nuclear matter. Using precise ab initio calculations, the results closely matched real-world data on nuclear properties such as size, structure, and binding energies. Calculations that were once impossible due to the sign problem can now be performed using wavefunction matching.

“It is a fantastic project and an excellent opportunity to work with the brightest nuclear scientist s in FRIB and around the globe,” said Ma. “As a theorist , I'm also very excited about programming and conducting research on the world's most powerful exascale supercomputers, such as Frontier , which allows us to implement wavefunction matching to explore the mysteries of nuclear physics.”

While the research team focused solely on quantum Monte Carlo simulations, wavefunction matching should be useful for many different ab initio approaches, including both classical and  quantum computing calculations. The researchers at FRIB worked with collaborators at institutions in China, France, Germany, South Korea, Turkey, and United States.

“The work is the culmination of effort over many years to handle the computational problems associated with realistic high-fidelity nuclear interactions,” said Lee. “It is very satisfying to see that the computational problems are cleanly resolved with this new approach. We are grateful to all of the collaboration members who contributed to this project, in particular, the lead author, Serdar Elhatisari.”

This material is based upon work supported by the U.S. Department of Energy, the U.S. National Science Foundation, the German Research Foundation, the National Natural Science Foundation of China, the Chinese Academy of Sciences President’s International Fellowship Initiative, Volkswagen Stiftung, the European Research Council, the Scientific and Technological Research Council of Turkey, the National Natural Science Foundation of China, the National Security Academic Fund, the Rare Isotope Science Project of the Institute for Basic Science, the National Research Foundation of Korea, the Institute for Basic Science, and the Espace de Structure et de réactions Nucléaires Théorique.

Michigan State University operates the Facility for Rare Isotope Beams (FRIB) as a user facility for the U.S. Department of Energy Office of Science (DOE-SC), supporting the mission of the DOE-SC Office of Nuclear Physics. Hosting what is designed to be the most powerful heavy-ion accelerator, FRIB enables scientists to make discoveries about the properties of rare isotopes in order to better understand the physics of nuclei, nuclear astrophysics, fundamental interactions, and applications for society, including in medicine, homeland security, and industry.

The U.S. Department of Energy Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of today’s most pressing challenges. For more information, visit energy.gov/science.

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Are We Talking Too Much About Mental Health?

Recent studies cast doubt on whether large-scale mental health interventions are making young people better. Some even suggest they can have a negative effect.

By Ellen Barry

In recent years, mental health has become a central subject in childhood and adolescence. Teenagers narrate their psychiatric diagnosis and treatment on TikTok and Instagram. School systems, alarmed by rising levels of distress and self-harm, are introducing preventive coursework in emotional self-regulation and mindfulness.

Now, some researchers warn that we are in danger of overdoing it. Mental health awareness campaigns, they argue, help some young people identify disorders that badly need treatment — but they have a negative effect on others, leading them to over-interpret their symptoms and see themselves as more troubled than they are.

The researchers point to unexpected results in trials of school-based mental health interventions in the United Kingdom and Australia: Students who underwent training in the basics of mindfulness , cognitive behavioral therapy and dialectical behavior therapy did not emerge healthier than peers who did not participate, and some were worse off, at least for a while.

And new research from the United States shows that among young people, “self-labeling” as having depression or anxiety is associated with poor coping skills, like avoidance or rumination.

In a paper published last year , two research psychologists at the University of Oxford, Lucy Foulkes and Jack Andrews, coined the term “prevalence inflation” — driven by the reporting of mild or transient symptoms as mental health disorders — and suggested that awareness campaigns were contributing to it.

“It’s creating this message that teenagers are vulnerable, they’re likely to have problems, and the solution is to outsource them to a professional,” said Dr. Foulkes, a Prudence Trust Research Fellow in Oxford’s department of experimental psychology, who has written two books on mental health and adolescence.

Until high-quality research has clarified these unexpected negative effects, they argue, school systems should proceed cautiously with large-scale mental health interventions.

“It’s not that we need to go back to square one, but it’s that we need to press pause and reroute potentially,” Dr. Foulkes said. “It’s possible that something very well-intended has overshot a bit and needs to be brought back in.”

This remains a minority view among specialists in adolescent mental health, who mostly agree that the far more urgent problem is lack of access to treatment.

About 60 percent of young Americans with severe depression receive no treatment, according to Mental Health America, a nonprofit research group. In crisis, desperate families fall back on emergency rooms, where teens often remain for days before a psychiatric bed opens up. There is good reason to embrace a preventive approach, teaching schoolchildren basic skills that might forestall crises later, experts say.

Dr. Foulkes said she understood that her argument runs counter to that consensus, and when she began to present it, she braced for a backlash. To her surprise, she said, many educators reached out to express quiet agreement.

“There’s definitely a fear about being the one to say it,” she said.

A deflating result

In the summer of 2022, the results of a landmark study on mindfulness training in British classrooms landed — like a lead balloon.

The trial, My Resilience in Adolescence, or MYRIAD, was ambitious, meticulous and expansive, following about 28,000 teenagers over eight years. It had been launched in a glow of optimism that the practice would pay off, improving the students’ mental health outcomes in later years.

Half of the teenagers were trained by their teachers to direct their attention to the present moment — breathing, physical sensations or everyday activities — in 10 lessons of 30 to 50 minutes apiece.

The results were disappointing . The authors reported “no support for our hypothesis” that mindfulness training would improve students’ mental health. In fact, students at highest risk for mental health problems did somewhat worse after receiving the training, the authors concluded.

But by the end of the eight-year project, “mindfulness is already embedded in a lot of schools, and there are already organizations making money from selling this program to schools,” said Dr. Foulkes, who had assisted on the study as a postdoctoral research associate. “And it’s very difficult to get the scientific message out there.”

Why, one might ask, would a mental health program do harm?

Researchers in the study speculated that the training programs “bring awareness to upsetting thoughts,” encouraging students to sit with darker feelings, but without providing solutions, especially for societal problems like racism or poverty. They also found that the students didn’t enjoy the sessions and didn’t practice at home.

Another explanation is that mindfulness training could encourage “co-rumination,” the kind of long, unresolved group discussion that churns up problems without finding solutions.

As the MYRIAD results were being analyzed, Dr. Andrews led an evaluation of Climate Schools, an Australian intervention based on the principles of cognitive behavioral therapy, in which students observed cartoon characters navigating mental health concerns and then answered questions about practices to improve mental health.

Here, too, he found negative effects. Students who had taken the course reported higher levels of depression and anxiety symptoms six months and 12 months later.

Co-rumination appears to be higher in girls, who tend to come into the program more distressed, as well as more attuned to their friends, he said. “It might be,” he said, “that they kind of get together and make things a little bit worse for each other.”

Dr. Andrews, a Wellcome Trust research fellow, has since joined an effort to improve Climate Schools by addressing negative effects. And he has concluded that schools should slow down until “we know the evidence base a bit more.” Sometimes, he said, “doing nothing is better than doing something.”

The awareness paradox

One problem with mental health awareness, some research suggests, is that it may not help to put a label to your symptoms.

Isaac Ahuvia, a doctoral candidate at Stony Brook University, recently tested this in a study of 1,423 college students . Twenty-two percent “self-labeled” as having depression, telling researchers “I am depressed” or “I have depression,” but 39 percent met the diagnostic criteria for depression.

He found that the students who self-labeled felt that they had less control over depression and were more likely to catastrophize and less likely to respond to distress by putting their difficulties in perspective, compared with peers who had similar depression symptoms.

Jessica L. Schleider, a co-author of the self-labeling study, said this was no surprise. People who self-label “appear to be viewing depression as a biological inevitability,” she said. “People who don’t view emotions as malleable, view them as set and stuck and uncontrollable, tend to cope less well because they don’t see a point to trying.”

But Dr. Schleider, an associate professor of medical social sciences at Northwestern University and the director of the university’s Lab for Scalable Mental Health, pushed back on the prevalence inflation hypothesis. She disagreed with the claim that students are overdiagnosing themselves, noting that Mr. Ahuvia’s findings suggest otherwise.

Awareness campaigns are bound to have multiple effects, helping some students and not others. And ultimately, she argued, the priority for public health should be reaching young people in the most distress.

“The urgency of the mental health crisis is so clear,” she said. “In the partnerships that I have, the emphasis is on the kids truly struggling right now who have nothing — we need to help them — more so than a possible risk for a subset of kids who aren’t really struggling.”

Maybe, she said, we need to look beyond the “universal, school-assembly-style approach,” to targeted, light-touch interventions, which research has shown can be effective at decreasing anxiety and conduct disorders, especially in younger children.

“There is a risk of throwing the baby out with the bathwater,” Dr. Schleider said. “The response can’t be ‘Forget all of it.’ It should be ‘What about this intervention was unhelpful?’”

Other researchers echoed her concern, pointing to studies that show that on average, students benefit from social and emotional learning courses.

One of the largest, a 2023 meta-analysis of 252 classroom programs in 53 countries, found that students who participated performed better academically, displayed better social skills and had lower levels of emotional distress or behavioral problems. In that context, negative effects in a handful of trials appear modest, the researchers said.

“We clearly have not figured out how to do them yet, but I can’t imagine any population-based intervention that the field got right the first time,” said Dr. Andrew J. Gerber, the president and medical director of Silver Hill Hospital and a practicing child and adolescent psychiatrist.

“Really, if you think about almost everything we do in schools, we don’t have great evidence for it working,” he added. “That doesn’t mean we don’t do it. It just means that we’re constantly thinking about ways to improve it.”

‘We want everyone to have it’

These debates are taking place a long way away from classrooms, where mental health curriculums are increasingly commonplace.

Allyson Kangisser, a counselor at Woodsdale Elementary School in Wheeling, W.Va., said the focus in her school is on basic coping skills. In the early grades, students are asked, “What things can you do to take care of yourself when you’re having big feelings?”

Starting in third grade, they take on more complex material, such as watching cartoon characters to distinguish transient stress from chronic conditions like depression. “We’re not trying to have them diagnose themselves,” Ms. Kangisser said. “We are saying, what do you feel — this one? Or this one?”

At the school’s sixth annual mental health fair last month, Woodsdale students walked through a giant inflatable brain, its lobes neatly labeled. They did yoga stretches and talked about regulating their emotions. Ms. Kangisser said the event is valuable precisely because it is universal, so troubled children are not singled out.

“The mental health fair, everybody does it,” she said. “It’s not ‘You need it, and you don’t.’ We want everyone to have it, because you just never know.”

By the time the students reach college, they will have absorbed enormous amounts of information about mental health — from school, but also from social media and from one another.

Dr. Jessica Gold, chief wellness officer for the University of Tennessee system, said the college students she sees are recognizably different — more comfortable speaking about their emotions and more willing to be vulnerable. They also overuse diagnostic terms and have the self-assurance to question a psychiatrist’s judgment.

“It’s sort of a double-edged sword,” she said. “We want people to talk about this more, but we don’t want that to lead to overdiagnosis or incorrect diagnosis or overtreatment. We want it to lead to normalizing of having feelings.”

Lucy Kim, a Yale senior who has lobbied for better mental health support on campus, described the prevalence inflation hypothesis as “disheartening, dismissive and potentially dangerous,” providing another way to discount the experiences of young people.

“As a college student, I see a generation of young people around me impacted by a depth and breadth of loneliness, exhaustion and disillusionment suggestive of a malaise that goes deeper than the general vicissitudes of life,” said Ms. Kim, 23.

Overdiagnosis does happen, she said, and so does glorification of mental health disorders. But stigma and barriers to treatment remain the bigger problem. “I can confidently say I have never heard anyone respond to disclosures of depression with ‘That’s so cool, I wish I had that, too,’” she said.

Ellen Barry is a reporter covering mental health for The Times. More about Ellen Barry

Managing Anxiety and Stress

Stay balanced in the face of stress and anxiety with our collection of tools and advice..

How are you, really? This self-guided check-in will help you take stock of your emotional well-being — and learn how to make changes .

These simple and proven strategies will help you manage stress , support your mental health and find meaning in the new year.

First, bring calm and clarity into your life with these 10 tips . Next, identify what you are dealing with: Is it worry, anxiety or stress ?

Persistent depressive disorder is underdiagnosed, and many who suffer from it have never heard of it. Here is what to know .

New research suggests people tend to be lonelier in young adulthood and late life. But experts say it doesn’t have to be that way .

How much anxiety is too much? Here is how to establish whether you should see a professional about it .

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• Published: 14 May 2024

2023 summer warmth unparalleled over the past 2,000 years

• Jan Esper   ORCID: orcid.org/0000-0003-3919-014X 1 , 2 ,
• Max Torbenson   ORCID: orcid.org/0000-0003-2720-2238 1 &
• Ulf Büntgen 2 , 3 , 4  

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• Climate change
• Palaeoclimate

Including an exceptionally warm Northern Hemisphere (NH) summer 1 ,2 , 2023 has been reported as the hottest year on record 3-5 . Contextualizing recent anthropogenic warming against past natural variability is nontrivial, however, because the sparse 19 th century meteorological records tend to be too warm 6 . Here, we combine observed and reconstructed June-August (JJA) surface air temperatures to show that 2023 was the warmest NH extra-tropical summer over the past 2000 years exceeding the 95% confidence range of natural climate variability by more than half a degree Celsius. Comparison of the 2023 JJA warming against the coldest reconstructed summer in 536 CE reveals a maximum range of pre-Anthropocene-to-2023 temperatures of 3.93°C. Although 2023 is consistent with a greenhouse gases-induced warming trend 7 that is amplified by an unfolding El Niño event 8 , this extreme emphasizes the urgency to implement international agreements for carbon emission reduction.

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Global Change Research Institute of the Czech Academy of Sciences, Brno, Czech Republic

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Esper, J., Torbenson, M. & Büntgen, U. 2023 summer warmth unparalleled over the past 2,000 years. Nature (2024). https://doi.org/10.1038/s41586-024-07512-y

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May 15, 2024

Purdue Global to expand AI learning capabilities with launch of Learning Assistant

Purdue Global launched its new Purdue Global Learning Assistant pilot across four courses in January. The AI tool is directing students to resources for classes and projects. (Purdue Global photo/Kelsey Lefever)

New resource embedded into online classroom platform

WEST LAFAYETTE, Ind. — Purdue Global professor Melissa Bahle welcomed a new teaching assistant to her composition classes this spring, helping field questions and providing answers while she is leading online classes.

The assistant’s name: Purdue Global Learning Assistant (PGLA), a new conversational AI tool designed to help students navigate and understand course resources and policies.

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• Purdue Global joins the Guild and Team USA Learning Network to provide higher education opportunities for Team USA athletes
• More than 1,500 Purdue Global graduates cap off college careers at commencement ceremonies
• Purdue Global: Don’t fear generative AI tools in the classroom
• Purdue Global’s student success coaching program to celebrate one year of addressing student needs, providing additional support

PGLA had a soft launch Jan. 31, with nearly 700 students across four sections of undergraduate and graduate courses piloting the new software. 

Bahle is a professor in Purdue Global’s Department of English and Rhetoric who teaches two sections of CM 107 (College Composition I), each with 28 students enrolled.

“I think PGLA is a wonderful addition to the class,” she said. “I have noticed fewer course navigation questions. So far, PGLA seems to work well for questions related to finding materials in the course, providing information and links about APA formatting, and helping students connect with the Academic Success Center.”

Timothy Werth , Purdue Global’s chief information officer and vice president of Administrative Services, said that providing self-directed and immediate resources for students in the classroom is exactly what the PGLA is designed to do.

“We wanted to make sure the pilot courses would be good foundational building blocks for PGLA and representative of challenges facing our students and faculty,” Werth said.

The concept for PGLA came from the 2021 Purdue Global Moves strategic initiatives that address opportunities to improve student success, such as visioning for Purdue Global’s Classroom of the Future. Purdue Global is Purdue’s online university for working adults.

Several faculty and leadership members believe that supplementing online classrooms with real-time assistance to students could have, in the long run, a positive impact on learning outcomes for students.

Teams of developers, IT professionals, learning designers and faculty members began collaborating in 2021 on initial conceptualization. The group began the institutional design phase in fall 2022.

This tool's development is focused on directly improving the Purdue Global teaching and learning experience. The development blueprint is grounded in student and faculty feedback issues.

“The excitement and engagement of our faculty has been a driving factor in our success during the product development life cycle. This is an academic project, not an IT project, that has clear outcome-based success criteria that everyone from faculty to finance can understand and evaluate. Every day, our faculty are bringing new problems to solve, which has resulted in a robust backlog of features that gets everyone excited about the future evolution of the Learning Assistant,” said Judy Lewandowski , vice provost for Adult Teaching and Learning.

Perfect timing of how a technology revolution assisted in tool development

As work groups were planning for PGLA, they encountered a technology revolution with the public release and adoption of generative AI programs .

And the work groups not only embraced the emergence of generative AI programs, they began including it in the design.

“We were methodical in our process to determine our next steps, which proved valuable as technologies available to Purdue Global were, and continue to be, changing rapidly,” Werth said. “The emergence of generative AI technologies using natural language models began to inform our potential path. In the fall of 2023, we decided the technologies were at a maturity level sufficient to embark on our vision to create the PGLA.”

With generative AI becoming more and more prevalent in the classroom, Purdue Global had to make sure what was being generated was correct for the students.

“The ability of any institution or organization to optimize AI is dependent upon the readiness of their data and processes to support an ‘AI first’ approach,” Werth said. “We expected challenges in this area, and we found them. Now it is about making incremental improvements as we move ahead.”

The three other courses — MT 140 (Introduction to Management), CJ 100 (Preparing for a Career in Public Safety) and ED 720 (doctoral course — Diversity, Equity, and Inclusion in Educational Contexts) — were selected for the pilot due to the number of students, plans of study and learning content.

Robert Winters , a professor in Purdue Global’s College of Social and Behavioral Sciences, teaches the CJ 100 course and participated in product testing.

Winters said PGLA’s interface is easy to use, and both he and his students are already seeing benefits.

“Pre-PGLA, students would either have to email me, as their professor, ask the question and then wait for me to respond, or wait to ask in our live weekly seminar, or often, just not ask and remain frustrated,” Winters said. “PGLA allows students to get answers 24/7 to their questions, on their time and need. When students use the tool, it helps to reduce the time that I need to spend either responding to emails or in seminars, time that can be better spent engaging students and teaching substantive content.”

Next steps: Continuous feedback

Faculty and student feedback is key to continued development, enhancement and scalability of the AI application. Focus groups will be created, and surveys will go out to the students. Developers are looking at feedback and interactions to see what other aspects could be tweaked or expanded.

Werth praises the course leads and faculty members who helped map user journeys in the initial version of PGLA.

“All faculty have been highly engaged and bring a deep knowledge of our classroom and gaps that exist that can be filled by the PGLA. They believe in this project, and they believe in the positive impact this will have on students over time,” Werth said.

Prior to launch, Bahle took time to ask PGLA questions about her courses. She attended two training sessions and now attends meetings twice a month with the larger working team, sharing how it is working with her students and brainstorming ways to make it more effective.

“I provided feedback on those answers that were not as thorough as they could be and noted when responses were helpful,” she said. “I worked on rewording questions to see how the responses from the program changed and worked on adjusting my seminars to dedicate time to discussing the PGLA with students and encouraging them to utilize it.”

Bahle looks forward to seeing how PGLA grows during the upcoming year.

“The more we work with it, the more effective it will be. I like that it is teaching students how to use AI as a tool when writing,” she said.

Winters also includes sections about PGLA in his seminars, encouraging students to use it.

“It is much easier for me to be able to talk to the entire class about PGLA than to have to field one student’s question and risk losing the attention of others because they do not have the same question,” Winters said.

Students are also responding positively to the additional tool, being able to get quick answers to basic course questions.

“From the student’s perspective, PGLA is like having me right there with them 24/7 to answer questions. That, in turn, lowers their stress level and allows them to more fully focus on learning their course content,” Winters said.

Werth believes the application will become more dynamic and valuable to the students as technology improves and problem-solving features are expanded. He hopes it becomes another trusted tool in our belt to improve student outcomes and persistence.

“The challenges of natural language models and accuracy are real, and we encounter something new each day,” he said. “It’s important that we keep an open mind and collaborate with our stakeholders all along the way to ensure this product delivers on our promise to drive Student Success.” 

About Purdue Global

Purdue Global is Purdue’s online university for working adults who have life experience and often some college credits. It offers flexible paths for students to earn an associate, bachelor’s, master’s or doctoral degree, based on their work experience, military service and previous college credits, no matter where they are in their life journey. Purdue Global is a nonprofit, public university accredited by the Higher Learning Commission and backed by Purdue University. For more information, visit https://www.purdueglobal.edu .

Writer/Media contact: Matthew Oates, [email protected] , 765-496-6160, @mo_oates

Sources: Timothy Werth, Melissa Bahle, Robert Winters, Sam Weber, Judy Lewandowski

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