academic research questionnaire

Designing a Questionnaire for a Research Paper: A Comprehensive Guide to Design and Develop an Effective Questionnaire

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10 Survey Tools for Academic Research in 2024

• Important Features

Survey Panels

• Additional Tools

1. SurveyKing

2. alchemer, 3. surveymonkey, 4. qualtrics, 5. questionpro, 6. sawtooth, 7. conjointly, 8. typeform, 10. google forms.

• Employee Feedback
• Creating the Survey
• Identity Protection
• Research Tools

Need a research survey tool? Features include MaxDiff, conjoint, and more!

These ten survey tools are perfect for academic research because they offer unique question types, solid reporting options, and support staff to help make your project a success. This article includes a detailed review of each of these nine survey tools. In addition to these survey tools, we include information about other research tools and survey panels.

Below is a quick summary of these nine survey tools. We list the lowest price to upgrade, which usually has the featured s needed for research projects. We also include a summary of the unique features of each tool. Most survey software has a monthly subscription; we denote when a tool requires annual pricing is required.

Important Features of Research Survey Software

Academic research surveys often require advanced question types to capture the necessary data. Many of the tools we mention in this article include these questions. However, some projects also require specialized features or the ability to purchase a panel. To help guide your decision in choosing the best piece of software for your project, we’ll summarize some of the most critical aspects.

Research Questions

Standard multiple-choice questions can only get you so far. Here are some question types you should be aware of:

• MaxDiff – measure the relative importance of an attribute. It goes beyond a standard ranking or rating by forcing respondents to pick the least and most valued items from a list. Rankings and other types only can you what is liked, not what is disliked. A statistical model will give you the probability of a user selecting an item as the most important. Latent class analysis can help you identify groups of respondents who value different attributes.
• Conjoint – Similar to MaxDiff in terms of finding importance, respondents evaluate a complete product (multiple attributes combined). This simulates real word purchasing decisions. A statistical model is also used to compute the importance of each item.
• Van Westendorp – Asks respondents to evaluate four price points. This shapes price curves and gives you a range of acceptable prices.
• Gabor Granger – Asks users whether or not they would purchase an item at specific price points. Price points are shown in random order to simulate real-world buying conditions. The results include a demand curve, giving you the revenue-maximizing price.
• Likert Scale – Measure attitudes and opinions related to a topic. It’s essential to use a mobile-ready Likert scale tool to increase response rates; many tools use a matrix for Likert scales, which could be more user-friendly.
• Semantic differential scale – a multirow rating scale that contains grammatically opposite adjectives at each end. It is used similarly to a Likert scale but is much easier for respondents to evaluate.
• Image heat map – Respondents click on places they like on an image. The results include a heat map showing the density of clicks. This is useful for product packaging.
• Net Promoter Score – Respondents choose a rating from 0-10. Many companies use this industry-standard question to benchmark their brand perception. This question type is necessary if your academic project measures brand reputation.

Anonymous Survey Links

Many academic surveys can deal with sensitive subjects or target sensitive groups. For this reason, assuring anonymity for respondents is crucial. Choosing a platform with an anonymous link is essential to increase trust with respondents and increase your response rates.

Data Segmentation

Comparing two groups within your survey data is essential for many research projects. This is called cross tabulation . For example, consider a survey where you ask for gender along with product satisfaction. You may notice that males are not satisfied with the product while females are.

You can take this further and compute the statistical significance between the groups. In other words, make the differences that exist between two data sets due to random chance or not. Your comparison is statistically significant if it’s not due to random chance.

Some lower-end survey tools may not offer any segmentation features. If this is the case, you need to download your survey data into a spreadsheet and create pivots of set-up custom formulas.

Skip Logic and Piping

If your academic project has questions that only a specific subset of respondents need to answer, then some logic will help streamline your survey.

Skip logic will take you to a new page based on answers to previous questions. Display logic will show a question to a user based on previous questions; perfect for follow-up.

Answer piping will allow you to carry forward answers from one question into another. So, for example, ask someone which brand names they have heard of, then pipe those answers into a ranking question.

Data Cleaning

Making sure your responses are high quality is a big part of any survey research project. For example, if people speed through the survey or mark all the first answers for questions, those would be low-quality responses and should be removed from your data set. Some tools highlight these low-quality responses, which can be a helpful feature.

For platforms that do not offer a data cleaning feature, it’s generally possible to export the data to Excel, create formulas for time spent, answer straight-lining, then remove the needed data. You can also include a  trap question  to help filter out low-quality responses.

Great Support

Many academic projects require statistical analysis or additional options for the survey. Using a tool with a support staff that can explain a statistical model’s intricacies, help build custom models, or adds features on request will ensure your project is a success. With SurveyKing, custom-built features are billed at $50 per hour, making custom projects feasible for small budgets.

Asking classmates to take your survey, posting it on social media, or distributing QR code surveys around campus is a great way to collect responses for your project. But if you need more responses with those methods, purchasing additional answers might be required.

A panel provider will enable you to target a specific demographic, job role, or hobby type. When setting up a survey with a penal provider, you always want to include screening questions (on the first page) to ensure they meet your criteria, as panel filters may not be 100% accurate. Generally, panel responses start around $2.50 per completed response.  Cint  is one of the largest panel providers and works well with any survey platform.

Additional Research Tools

Before deep diving into the survey software list, here are some additional tools and resources that might assist in your project. These can help shape your survey by conducting preliminary research or using it as a substitute if conducting a study is not feasible.

• Hotjar  – They offer simple surveys and many tools to help capture feedback and data points from a website. A feedback widget customized for websites in addition to a heat map tool to show where users click the most or to identify rage clicks. A tool like this could be helpful if your academic projects revolve around launching or optimizing a website.
• Think with Google  – Used to help marketers understand their audience. The site contains links to Google Trends to search for the popularity of key terms over time. They also have a tool that helps you identify your audience based on popular YouTube channels. Finally, they have a “Grow My Store Tool” that recommends tips for improving an online store.
• Google Scholar  – A specific search engine used for scholarly literature. This can help locate research papers related to the survey you are creating.
• MIT Theses  – Contains over 58,000 theses and dissertations from all MIT departments. The database is organized by department and lets you search for keywords.

SurveyKing is the best tool for academic research surveys because of a wide variety of question types like MaxDiff, excellent reporting features, a solid support staff, and a low cost of $19 per month.

The survey builder is straightforward to use. Question types include MaxDiff, conjoint, Gabor Granger, Van Westendorp, a mobile optimized Likert scale, and semantic differential.

The MaxDiff question also includes anchored MaxDiff and collecting open-ended feedback for the feature most valued by a respondent. In addition, cluster analysis is available to help similar group data together; some respondents might value specific attributes, while other groups value others.

The reporting section is also a standout feature. It is easy to create filters and segment reports. In addition, the Excel export is well formatted easily for question types like ranking and Likert Scale, making it easy to upload into SPSS. The reporting section also gives the probability for MaxDiff, one of the few tools to offer that.

The anonymous link on SurveyKing is a valuable feature. A snippet at the top of each anonymous survey is where users can click to understand whether their identities are protected.

The software also offers a Net Promoter Score module which can come in handy for projects that deep dive into brand reputation.

Some downsides to SurveyKing include no answer piping, no image heat maps, no continuous sum question, and no premade data cleaning feature.

As a platform with lots of advanced question types and a reasonable cost, Alchemer is an excellent tool for academic research. Question types include MaxDiff, conjoint, semantic differential, image heat map, text highlighter, continuous sum, cascading dropdowns, rankings, and card grouping.

Reporting on Alchemer is a standout feature. Not only can you create filters and segment reports, but you can also create those filters and segments using advanced criteria. So if you ask a question about gender and hobby, you can make advanced criteria that match a specific gender and hobby.

In addition, their reporting section also can do chi-square tests to calculate the significant difference between the two groups. Finally, they also have a section where you can create and run your R scripts. This can be useful for various academic research projects as you can create custom statistical models in the software without needing to export your data.

Alchemer is less user-friendly than some other tools. The platform is a little clunky; things like MaxDiff require respondents to hit the submit button to get to the next set. Radio buttons need respondents to click inside of them instead of the area around them.

The pricing is reasonable for a student; $249 a month for access to the research questions. However, if you can organize your project quickly, you may only need one month of access.

As the most recognized brand for online surveys, SurveyMonkey is a reliable option for academic research. While the platform does not have any research questions, it offers all the standard question types and a clean user interface to build your surveys.

One advanced question type they do have is the image heat map. Their parent company  Momentive  does offer things like MaxDiff and conjoint studies, but you would need to contact sales to get a quote, meaning this could be out of budget for students.

The reporting on SurveyMonkey is good. You can easily create filters and segments. You can also save that criterion to create a view. The views enable you to toggle between rules quickly.

One of the main downsides to SurveyMonkey is the cost. For the image heat map and to create advanced branching rules, you need to upgrade to their Premier plan, which costs $1,428 annually. To get statistical significance, you would need their Primer plan, which is $468 annually.

As the survey tool known for experience management, Qualtrics has some nice features for research projects. For example, they offer both MaxDiff and conjoint in addition to tools like drill-down, continuous sun, image heat map, and a text highlighter.

Reporting on the tool offers the ability to create filters and segments. For segments, it’s called a report breakout, and it appears there is no ability to create a breakout with advanced criteria. However, filers do allow you for advanced criteria.

There is a custom report builder option to create custom PDF reports. You can add as many elements as needed and customize the information displayed, whether a chart type or a data table.

Overall, Qualtrics could be more user-friendly and may require training. The survey builder and reporting screens could be more cohesive. For example, to add more answer options, you need to click the “plus” symbol on the left-hand side of the question instead of just hitting enter or clicking a button right below the current answer choice. In addition, the reporting section will display things like mean and standard deviation for simple multiple-choice questions before showing simple response counts.

One drawback to Qualtrics is the pricing. For example, you would need to pay $1,440 for an annual plan to use the research questions. But many universities have a licensing agreement with Qualtrics so students can use the platform. When you sign up for a new account, you can select academic use, enter your Edu email, and they will check if your university has a license agreement.

A survey platform with all the needed research questions, including Gabor Granger and Van Westendorp, QuestionPro is a quality research tool.

The reporting on QuestionPro is comprehensive. They offer segment reports with statistical significance using a t-test. In addition, they offer TURF analysis to show answer combinations with the highest reach.

For conjoint, offer a market simulation tool that can forecast new product market share based on your data. That tool can also calculate how much  premium  consumers will pay for a brand name.

QuestionPro is a little easier to use than Qualtrics. The UI is cleaner but still clumsy. You must navigate to a different section in the builder for things like quotas instead of just having it near skip logic rules. The distribution page has the link at the top but an email body below. The reporting has a lot of different pages to click through for each option. Small things like this mean there is a learning curve to use the platform efficiently.

The biggest downside of QuestionPro is the price. All of their research questions, even Net Promoter Score, would require a custom quote under the research plan. There another plan with upgraded feature types is $1,188 annually.

When it comes to advanced research projects, Sawtooth is a great resource. While their survey builder is a little limited in question types, they offer different forms of MaxDiff and conjoint. They also provide consulting services, which could help if your academic project is highly specialized.

For MaxDiff, they offer a bandit  version, which can be used for MaxDiff studies with over 50 attributes. Each set of detailed attributes that are most relevant to the user. This can save panel costs because you can build a suitable statistical model with 300 bandit responses compared with 500 or 1000 standard MaxDiff responses.

Their MaxDiff feature also comes with a TURF analysis option that can show you the possible market research of various attributes.

For conjoint, they offer adaptive choice-based conjoint and menu-based conjoint. Adaptive choice tailors the product cards toward each respondent based on early responses or screening questions. Menu-based conjoint is for more complex projects, allowing respondents to build their products based on various attributes and prices.

Sawtooth has a high price point and may be out of the research for many academic projects. The lowest plan is $4,500 annually. If you need advanced tools like bandit MaxDiff or adaptive conjoint, you must pay $11,990 annually. They do have a package just for MaxDiff starting at $2,420.

Conjointly is a platform geared towards research projects, namely market research. Not only do they have the standard research questions, but they also have a bunch of unique ones: claims testing, Kano Model testing, and monadic testing. There are also question types like feature placement matrix, which combines MaxDiff and Gabor Granger into a single question.

You can either use your respondents or select from a survey panel. The survey panel option comes with predefined audiences, which makes scouring respondents a breeze.

One unique feature is that they monitor in real-time speeders and other criteria for low-quality respondents. If a respondent is speeding through the survey, a warning message is displayed asking them to repeat questions before being disqualified. If a question has a lot of information to digest, the system automatically pauses, forcing the respondent to thoroughly read the question before answering.

The pricing is a little steep at $1,795 annually. Response panels for USA residents appear to start around $4 per completed response. The survey builder and reporting section could be cleaner, with different options in many places. It may take time to get up to speed.

While Typeform doesn’t have any research questions, it is a very well-designed and easy-to-use tool that can assist with your academic survey. For example, it could gather preliminary data for a MaxDiff study.

Typeform offers a lot of integrations with other applications. For example, if your project requires exporting data to a spreadsheet, then Google Sheets or Excel integration might be helpful. Likewise, if your research project is part of a class project, then the Slack or Microsoft Teams integration might help to notify other team members when you get responses.

One unique feature of Typeform is the calculator feature. Add, subtract, and multiply numbers to the @score or @price variable. These variables can be recalled to show scores or used in a payment form.

The reporting in Typeform is basic. There is no option to create a filter or a segment report. Any data analysis would need to be done in Google Sheets or Excel.

For $29 a month, you can get 100 responses, or $59 a month, you can collect 1,000 responses each month.

HubSpot’s form builder doesn’t include advanced research questions, but it is customizable and easy to use. You can pick between multiple form types, like standalone, embedded, and pop-up forms. There are also numerous templates including lead generation, support, or eBook download forms.

One of the form builder’s main advantages is that it offers native integrations with Salesforce and HubSpot CRM tools. In addition, you can add custom properties to the form from the CRM fields. You can then send the surveys in bulk to your audience using their email features.

If you’re a large academic organization. HubSpot would be ideal to organize and manage a large distribution list. If you need advanced questions, you can still use HubSpot for an initial screener survey or incorporate other surveys into HubSpot using skip logic.

As for the downsides, scalability can be challenging. Although you can use the form builder for free, you’ll have to subscribe to one of HubSpot’s Marketing Hub paid plans to access more advanced functionalities, like unlimited automation workflows and code customization. There are steep pricing differences between paid packages. 

One of the widely used survey tools, Google Forms , is a decent platform for an academic research survey. Unfortunately, the software doesn’t offer any research questions. Still, the few questions it has, like multiple choice, rantings, and open-ended feedback, are enough to collect essential feedback for simple projects or preliminary data for more complex studies.

Skip logic is straightforward to set up on Google Forms. For example, you can select what section to skip based on question answers or choose what to skip once a section is complete. Of course, you can’t create complex rules, but these simple rules can cover many bases.

Overall the user interface is elegant and straightforward. The form design is also elegant, meaning the respondent experience is excellent. Unlike other survey tools, which can have a clunky interface, there is no worry about that with Google Forms; respondents can quickly navigate your form and submit answers.

The spreadsheet export is very well formatted and can be easily imported into SPSS for advanced analysis. However, the export has the submission date and time but has yet to have the time started, so calculating speeders is impossible.

ABOUT THE AUTOR

Allen is the founder of SurveyKing. A former CPA and government auditor, he understands how important quality data is in decision making. He continues to help SurveyKing accomplish their main goal: providing organizations around the world with low-cost high-quality feedback tools.

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This PSR Tip Sheet provides some basic tips about how to write good survey questions and design a good survey questionnaire.

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Academic survey questions, examples, and a step-by-step guide

Use SurveyPlanet for your academic research and gather real data that supports your thesis.

If you want to deepen your knowledge about a particular subject by testing theories, then academic surveys are invaluable. Coming up with a hypothesis is hard enough and a well-designed survey—with carefully constructed questions—will help you test how viable your hypothesis actually is.

The best survey tool for academic research

SurveyPlanet is a great tool for creating academic surveys that will let you put theoretical knowledge into practice and learn by doing. With dozens of templates that include pre-written questions, you will learn right away what a great academic survey should look like.

You’ll also find powerful features like question branching, survey-length estimation, four chart types to display results, and many more when you sign up for a SurveyPlanet account to create an academic survey. Our user-friendly designs will make both creating and filling out surveys a simple yet exciting experience for both you and your respondents.

A step-by-step guide to creating a successful academic survey

• First, gather your thoughts by putting them on paper in order to create a strategy for a successful academic survey.
• Set one ultimate goal, then divide this into smaller, actionable steps that will lead to achieving it.
• Consider your hypothesis and figure out how an academic survey will help you confirm it.
• Before creating questions, decide or learn who will be your target group.
• After you know your target group, think about how big your sample should be to produce statistically significant data. You can do that with our free survey sample size calculator.
• Whether you need one hundred or one thousand responses, think about where your target sample hangs out and how you’ll distribute the survey. Share a survey link with different communities on social media and reach out to friends and acquaintances. Maybe they aren’t your target group, but a friend of a friend is. Don’t get discouraged, people love to help with academic research.
• Books are one thing, real-life data is another. Think about implementing what you already know in your academic survey and how that knowledge can serve a higher purpose.
• When writing questions make sure to use different types, such as multiple choice, Likert scale, open-ended, image choice, and ranking questions. This will make your survey more engaging and fewer people will drop out because they didn't make it through to the end.
• Be brief and concise, both with questions and the survey itself. Think about whether some questions are really necessary. Write questions with straightforward language.
• Make sure your survey isn’t too long. That will put respondents off. With a survey length estimate , you don’t have to manually estimate the length, since SurveyPlanet can do that for you.
• Creating an academic survey and gathering data is great, but you also need to analyze the results. Figure out which method you’ll use before distributing the survey and analyze the quantitative data first (because it’s more straightforward).

While we can't promise that, with the help of our survey tools, you will attain academic excellence in no time, we are sure that our tools will provide a valuable service in your research endeavors. In fact, our mission is to facilitate all the stages of conducting research , from ideation to analysis. That is why we made guidelines covering every step of the process, from creating a survey to survey data analysis for better insights.

Creating your academic survey online is one of the least expensive—but effective—ways to gather all the data you need. People are more eager to respond to an online survey in their free time, from the comfort of their homes. With SurveyPlanet as your partner, you will garner a high response rate and much useful data.

Academic surveys questions and examples

The quality of questions directly influences the quality of data. At the end of the day, it’s the quality of results that matter. Because of that, we pay special attention to creating academic survey questions that are useful for both students and respondents. Academic surveys usually require some demographic questions , including:

• Please select your age range:
• 18 or younger
• Please select your gender:
• What’s your marital status?
• What’s the highest level of education you’ve completed?
• Less than high school
• High school
• Bachelor degree
• Masters degree
• Which category best describes your employment status?
• Employed full-time (40 hours a week or more)
• Employed part-time (less than 40 hours a week)
• Which category best fits the yearly household income of every member combined?
• $20,000-$59,999
• $60,000-$99,999
• $100,000-$149,999
• $150,000 or more

Academic surveys can explore and research many different topics. It just depends on what your area of interest is. Here are some academic survey examples to give you a better idea:

Healthcare surveys

With healthcare surveys, you can research patient demographics, figure out how accessible healthcare is, some common issues people encounter, and ways to improve performance.

Read more about healthcare surveys

Education surveys

Student satisfaction is a topic for which there is always more to ask and say. Using education surveys, you can explore students’ habits, assess the quality of their education, and research teachers’ working conditions.

Read more about education surveys

From employee satisfaction to work-life balance, HR surveys are an inexhaustible source for researching and studying workplace issues.

Read more about HR surveys

Brand surveys

Research consumer demographics and how they perceive different brands to draw conclusions based on the data you collect.

Read more about brand surveys

Depending on the theme that is being addressed, this type of questionnaire can be labeled as a:

• postgraduate taught experience survey
• academic performance survey
• academic research survey

Specific questions depend on the subject you’re studying and researching and we have dozens of academic survey templates to choose from.

SurveyPlanet can help you with your academic research. Use our survey tools, which can help you gather valuable data and insights in no time while providing the best experience to your examinees. Just sign up for a SurveyPlanet account and create an academic survey that will be ready for responses.

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Writing Survey Questions

Perhaps the most important part of the survey process is the creation of questions that accurately measure the opinions, experiences and behaviors of the public. Accurate random sampling will be wasted if the information gathered is built on a shaky foundation of ambiguous or biased questions. Creating good measures involves both writing good questions and organizing them to form the questionnaire.

Questionnaire design is a multistage process that requires attention to many details at once. Designing the questionnaire is complicated because surveys can ask about topics in varying degrees of detail, questions can be asked in different ways, and questions asked earlier in a survey may influence how people respond to later questions. Researchers are also often interested in measuring change over time and therefore must be attentive to how opinions or behaviors have been measured in prior surveys.

Surveyors may conduct pilot tests or focus groups in the early stages of questionnaire development in order to better understand how people think about an issue or comprehend a question. Pretesting a survey is an essential step in the questionnaire design process to evaluate how people respond to the overall questionnaire and specific questions, especially when questions are being introduced for the first time.

For many years, surveyors approached questionnaire design as an art, but substantial research over the past forty years has demonstrated that there is a lot of science involved in crafting a good survey questionnaire. Here, we discuss the pitfalls and best practices of designing questionnaires.

Question development

There are several steps involved in developing a survey questionnaire. The first is identifying what topics will be covered in the survey. For Pew Research Center surveys, this involves thinking about what is happening in our nation and the world and what will be relevant to the public, policymakers and the media. We also track opinion on a variety of issues over time so we often ensure that we update these trends on a regular basis to better understand whether people’s opinions are changing.

At Pew Research Center, questionnaire development is a collaborative and iterative process where staff meet to discuss drafts of the questionnaire several times over the course of its development. We frequently test new survey questions ahead of time through qualitative research methods such as  focus groups , cognitive interviews, pretesting (often using an  online, opt-in sample ), or a combination of these approaches. Researchers use insights from this testing to refine questions before they are asked in a production survey, such as on the ATP.

Measuring change over time

Many surveyors want to track changes over time in people’s attitudes, opinions and behaviors. To measure change, questions are asked at two or more points in time. A cross-sectional design surveys different people in the same population at multiple points in time. A panel, such as the ATP, surveys the same people over time. However, it is common for the set of people in survey panels to change over time as new panelists are added and some prior panelists drop out. Many of the questions in Pew Research Center surveys have been asked in prior polls. Asking the same questions at different points in time allows us to report on changes in the overall views of the general public (or a subset of the public, such as registered voters, men or Black Americans), or what we call “trending the data”.

When measuring change over time, it is important to use the same question wording and to be sensitive to where the question is asked in the questionnaire to maintain a similar context as when the question was asked previously (see  question wording  and  question order  for further information). All of our survey reports include a topline questionnaire that provides the exact question wording and sequencing, along with results from the current survey and previous surveys in which we asked the question.

The Center’s transition from conducting U.S. surveys by live telephone interviewing to an online panel (around 2014 to 2020) complicated some opinion trends, but not others. Opinion trends that ask about sensitive topics (e.g., personal finances or attending religious services ) or that elicited volunteered answers (e.g., “neither” or “don’t know”) over the phone tended to show larger differences than other trends when shifting from phone polls to the online ATP. The Center adopted several strategies for coping with changes to data trends that may be related to this change in methodology. If there is evidence suggesting that a change in a trend stems from switching from phone to online measurement, Center reports flag that possibility for readers to try to head off confusion or erroneous conclusions.

Open- and closed-ended questions

One of the most significant decisions that can affect how people answer questions is whether the question is posed as an open-ended question, where respondents provide a response in their own words, or a closed-ended question, where they are asked to choose from a list of answer choices.

For example, in a poll conducted after the 2008 presidential election, people responded very differently to two versions of the question: “What one issue mattered most to you in deciding how you voted for president?” One was closed-ended and the other open-ended. In the closed-ended version, respondents were provided five options and could volunteer an option not on the list.

When explicitly offered the economy as a response, more than half of respondents (58%) chose this answer; only 35% of those who responded to the open-ended version volunteered the economy. Moreover, among those asked the closed-ended version, fewer than one-in-ten (8%) provided a response other than the five they were read. By contrast, fully 43% of those asked the open-ended version provided a response not listed in the closed-ended version of the question. All of the other issues were chosen at least slightly more often when explicitly offered in the closed-ended version than in the open-ended version. (Also see  “High Marks for the Campaign, a High Bar for Obama”  for more information.)

Researchers will sometimes conduct a pilot study using open-ended questions to discover which answers are most common. They will then develop closed-ended questions based off that pilot study that include the most common responses as answer choices. In this way, the questions may better reflect what the public is thinking, how they view a particular issue, or bring certain issues to light that the researchers may not have been aware of.

When asking closed-ended questions, the choice of options provided, how each option is described, the number of response options offered, and the order in which options are read can all influence how people respond. One example of the impact of how categories are defined can be found in a Pew Research Center poll conducted in January 2002. When half of the sample was asked whether it was “more important for President Bush to focus on domestic policy or foreign policy,” 52% chose domestic policy while only 34% said foreign policy. When the category “foreign policy” was narrowed to a specific aspect – “the war on terrorism” – far more people chose it; only 33% chose domestic policy while 52% chose the war on terrorism.

In most circumstances, the number of answer choices should be kept to a relatively small number – just four or perhaps five at most – especially in telephone surveys. Psychological research indicates that people have a hard time keeping more than this number of choices in mind at one time. When the question is asking about an objective fact and/or demographics, such as the religious affiliation of the respondent, more categories can be used. In fact, they are encouraged to ensure inclusivity. For example, Pew Research Center’s standard religion questions include more than 12 different categories, beginning with the most common affiliations (Protestant and Catholic). Most respondents have no trouble with this question because they can expect to see their religious group within that list in a self-administered survey.

In addition to the number and choice of response options offered, the order of answer categories can influence how people respond to closed-ended questions. Research suggests that in telephone surveys respondents more frequently choose items heard later in a list (a “recency effect”), and in self-administered surveys, they tend to choose items at the top of the list (a “primacy” effect).

Because of concerns about the effects of category order on responses to closed-ended questions, many sets of response options in Pew Research Center’s surveys are programmed to be randomized to ensure that the options are not asked in the same order for each respondent. Rotating or randomizing means that questions or items in a list are not asked in the same order to each respondent. Answers to questions are sometimes affected by questions that precede them. By presenting questions in a different order to each respondent, we ensure that each question gets asked in the same context as every other question the same number of times (e.g., first, last or any position in between). This does not eliminate the potential impact of previous questions on the current question, but it does ensure that this bias is spread randomly across all of the questions or items in the list. For instance, in the example discussed above about what issue mattered most in people’s vote, the order of the five issues in the closed-ended version of the question was randomized so that no one issue appeared early or late in the list for all respondents. Randomization of response items does not eliminate order effects, but it does ensure that this type of bias is spread randomly.

Questions with ordinal response categories – those with an underlying order (e.g., excellent, good, only fair, poor OR very favorable, mostly favorable, mostly unfavorable, very unfavorable) – are generally not randomized because the order of the categories conveys important information to help respondents answer the question. Generally, these types of scales should be presented in order so respondents can easily place their responses along the continuum, but the order can be reversed for some respondents. For example, in one of Pew Research Center’s questions about abortion, half of the sample is asked whether abortion should be “legal in all cases, legal in most cases, illegal in most cases, illegal in all cases,” while the other half of the sample is asked the same question with the response categories read in reverse order, starting with “illegal in all cases.” Again, reversing the order does not eliminate the recency effect but distributes it randomly across the population.

Question wording

The choice of words and phrases in a question is critical in expressing the meaning and intent of the question to the respondent and ensuring that all respondents interpret the question the same way. Even small wording differences can substantially affect the answers people provide.

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An example of a wording difference that had a significant impact on responses comes from a January 2003 Pew Research Center survey. When people were asked whether they would “favor or oppose taking military action in Iraq to end Saddam Hussein’s rule,” 68% said they favored military action while 25% said they opposed military action. However, when asked whether they would “favor or oppose taking military action in Iraq to end Saddam Hussein’s rule  even if it meant that U.S. forces might suffer thousands of casualties, ” responses were dramatically different; only 43% said they favored military action, while 48% said they opposed it. The introduction of U.S. casualties altered the context of the question and influenced whether people favored or opposed military action in Iraq.

There has been a substantial amount of research to gauge the impact of different ways of asking questions and how to minimize differences in the way respondents interpret what is being asked. The issues related to question wording are more numerous than can be treated adequately in this short space, but below are a few of the important things to consider:

First, it is important to ask questions that are clear and specific and that each respondent will be able to answer. If a question is open-ended, it should be evident to respondents that they can answer in their own words and what type of response they should provide (an issue or problem, a month, number of days, etc.). Closed-ended questions should include all reasonable responses (i.e., the list of options is exhaustive) and the response categories should not overlap (i.e., response options should be mutually exclusive). Further, it is important to discern when it is best to use forced-choice close-ended questions (often denoted with a radio button in online surveys) versus “select-all-that-apply” lists (or check-all boxes). A 2019 Center study found that forced-choice questions tend to yield more accurate responses, especially for sensitive questions.  Based on that research, the Center generally avoids using select-all-that-apply questions.

It is also important to ask only one question at a time. Questions that ask respondents to evaluate more than one concept (known as double-barreled questions) – such as “How much confidence do you have in President Obama to handle domestic and foreign policy?” – are difficult for respondents to answer and often lead to responses that are difficult to interpret. In this example, it would be more effective to ask two separate questions, one about domestic policy and another about foreign policy.

In general, questions that use simple and concrete language are more easily understood by respondents. It is especially important to consider the education level of the survey population when thinking about how easy it will be for respondents to interpret and answer a question. Double negatives (e.g., do you favor or oppose  not  allowing gays and lesbians to legally marry) or unfamiliar abbreviations or jargon (e.g., ANWR instead of Arctic National Wildlife Refuge) can result in respondent confusion and should be avoided.

Similarly, it is important to consider whether certain words may be viewed as biased or potentially offensive to some respondents, as well as the emotional reaction that some words may provoke. For example, in a 2005 Pew Research Center survey, 51% of respondents said they favored “making it legal for doctors to give terminally ill patients the means to end their lives,” but only 44% said they favored “making it legal for doctors to assist terminally ill patients in committing suicide.” Although both versions of the question are asking about the same thing, the reaction of respondents was different. In another example, respondents have reacted differently to questions using the word “welfare” as opposed to the more generic “assistance to the poor.” Several experiments have shown that there is much greater public support for expanding “assistance to the poor” than for expanding “welfare.”

We often write two versions of a question and ask half of the survey sample one version of the question and the other half the second version. Thus, we say we have two  forms  of the questionnaire. Respondents are assigned randomly to receive either form, so we can assume that the two groups of respondents are essentially identical. On questions where two versions are used, significant differences in the answers between the two forms tell us that the difference is a result of the way we worded the two versions.

One of the most common formats used in survey questions is the “agree-disagree” format. In this type of question, respondents are asked whether they agree or disagree with a particular statement. Research has shown that, compared with the better educated and better informed, less educated and less informed respondents have a greater tendency to agree with such statements. This is sometimes called an “acquiescence bias” (since some kinds of respondents are more likely to acquiesce to the assertion than are others). This behavior is even more pronounced when there’s an interviewer present, rather than when the survey is self-administered. A better practice is to offer respondents a choice between alternative statements. A Pew Research Center experiment with one of its routinely asked values questions illustrates the difference that question format can make. Not only does the forced choice format yield a very different result overall from the agree-disagree format, but the pattern of answers between respondents with more or less formal education also tends to be very different.

One other challenge in developing questionnaires is what is called “social desirability bias.” People have a natural tendency to want to be accepted and liked, and this may lead people to provide inaccurate answers to questions that deal with sensitive subjects. Research has shown that respondents understate alcohol and drug use, tax evasion and racial bias. They also may overstate church attendance, charitable contributions and the likelihood that they will vote in an election. Researchers attempt to account for this potential bias in crafting questions about these topics. For instance, when Pew Research Center surveys ask about past voting behavior, it is important to note that circumstances may have prevented the respondent from voting: “In the 2012 presidential election between Barack Obama and Mitt Romney, did things come up that kept you from voting, or did you happen to vote?” The choice of response options can also make it easier for people to be honest. For example, a question about church attendance might include three of six response options that indicate infrequent attendance. Research has also shown that social desirability bias can be greater when an interviewer is present (e.g., telephone and face-to-face surveys) than when respondents complete the survey themselves (e.g., paper and web surveys).

Lastly, because slight modifications in question wording can affect responses, identical question wording should be used when the intention is to compare results to those from earlier surveys. Similarly, because question wording and responses can vary based on the mode used to survey respondents, researchers should carefully evaluate the likely effects on trend measurements if a different survey mode will be used to assess change in opinion over time.

Question order

Once the survey questions are developed, particular attention should be paid to how they are ordered in the questionnaire. Surveyors must be attentive to how questions early in a questionnaire may have unintended effects on how respondents answer subsequent questions. Researchers have demonstrated that the order in which questions are asked can influence how people respond; earlier questions can unintentionally provide context for the questions that follow (these effects are called “order effects”).

One kind of order effect can be seen in responses to open-ended questions. Pew Research Center surveys generally ask open-ended questions about national problems, opinions about leaders and similar topics near the beginning of the questionnaire. If closed-ended questions that relate to the topic are placed before the open-ended question, respondents are much more likely to mention concepts or considerations raised in those earlier questions when responding to the open-ended question.

For closed-ended opinion questions, there are two main types of order effects: contrast effects ( where the order results in greater differences in responses), and assimilation effects (where responses are more similar as a result of their order).

An example of a contrast effect can be seen in a Pew Research Center poll conducted in October 2003, a dozen years before same-sex marriage was legalized in the U.S. That poll found that people were more likely to favor allowing gays and lesbians to enter into legal agreements that give them the same rights as married couples when this question was asked after one about whether they favored or opposed allowing gays and lesbians to marry (45% favored legal agreements when asked after the marriage question, but 37% favored legal agreements without the immediate preceding context of a question about same-sex marriage). Responses to the question about same-sex marriage, meanwhile, were not significantly affected by its placement before or after the legal agreements question.

Another experiment embedded in a December 2008 Pew Research Center poll also resulted in a contrast effect. When people were asked “All in all, are you satisfied or dissatisfied with the way things are going in this country today?” immediately after having been asked “Do you approve or disapprove of the way George W. Bush is handling his job as president?”; 88% said they were dissatisfied, compared with only 78% without the context of the prior question.

Responses to presidential approval remained relatively unchanged whether national satisfaction was asked before or after it. A similar finding occurred in December 2004 when both satisfaction and presidential approval were much higher (57% were dissatisfied when Bush approval was asked first vs. 51% when general satisfaction was asked first).

Several studies also have shown that asking a more specific question before a more general question (e.g., asking about happiness with one’s marriage before asking about one’s overall happiness) can result in a contrast effect. Although some exceptions have been found, people tend to avoid redundancy by excluding the more specific question from the general rating.

Assimilation effects occur when responses to two questions are more consistent or closer together because of their placement in the questionnaire. We found an example of an assimilation effect in a Pew Research Center poll conducted in November 2008 when we asked whether Republican leaders should work with Obama or stand up to him on important issues and whether Democratic leaders should work with Republican leaders or stand up to them on important issues. People were more likely to say that Republican leaders should work with Obama when the question was preceded by the one asking what Democratic leaders should do in working with Republican leaders (81% vs. 66%). However, when people were first asked about Republican leaders working with Obama, fewer said that Democratic leaders should work with Republican leaders (71% vs. 82%).

The order questions are asked is of particular importance when tracking trends over time. As a result, care should be taken to ensure that the context is similar each time a question is asked. Modifying the context of the question could call into question any observed changes over time (see  measuring change over time  for more information).

A questionnaire, like a conversation, should be grouped by topic and unfold in a logical order. It is often helpful to begin the survey with simple questions that respondents will find interesting and engaging. Throughout the survey, an effort should be made to keep the survey interesting and not overburden respondents with several difficult questions right after one another. Demographic questions such as income, education or age should not be asked near the beginning of a survey unless they are needed to determine eligibility for the survey or for routing respondents through particular sections of the questionnaire. Even then, it is best to precede such items with more interesting and engaging questions. One virtue of survey panels like the ATP is that demographic questions usually only need to be asked once a year, not in each survey.

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• Doing Survey Research | A Step-by-Step Guide & Examples

Doing Survey Research | A Step-by-Step Guide & Examples

Published on 6 May 2022 by Shona McCombes . Revised on 10 October 2022.

Survey research means collecting information about a group of people by asking them questions and analysing the results. To conduct an effective survey, follow these six steps:

• Determine who will participate in the survey
• Decide the type of survey (mail, online, or in-person)
• Design the survey questions and layout
• Distribute the survey
• Analyse the responses
• Write up the results

Surveys are a flexible method of data collection that can be used in many different types of research .

Table of contents

What are surveys used for, step 1: define the population and sample, step 2: decide on the type of survey, step 3: design the survey questions, step 4: distribute the survey and collect responses, step 5: analyse the survey results, step 6: write up the survey results, frequently asked questions about surveys.

Surveys are used as a method of gathering data in many different fields. They are a good choice when you want to find out about the characteristics, preferences, opinions, or beliefs of a group of people.

Common uses of survey research include:

• Social research: Investigating the experiences and characteristics of different social groups
• Market research: Finding out what customers think about products, services, and companies
• Health research: Collecting data from patients about symptoms and treatments
• Politics: Measuring public opinion about parties and policies
• Psychology: Researching personality traits, preferences, and behaviours

Surveys can be used in both cross-sectional studies , where you collect data just once, and longitudinal studies , where you survey the same sample several times over an extended period.

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Before you start conducting survey research, you should already have a clear research question that defines what you want to find out. Based on this question, you need to determine exactly who you will target to participate in the survey.

Populations

The target population is the specific group of people that you want to find out about. This group can be very broad or relatively narrow. For example:

• The population of Brazil
• University students in the UK
• Second-generation immigrants in the Netherlands
• Customers of a specific company aged 18 to 24
• British transgender women over the age of 50

Your survey should aim to produce results that can be generalised to the whole population. That means you need to carefully define exactly who you want to draw conclusions about.

It’s rarely possible to survey the entire population of your research – it would be very difficult to get a response from every person in Brazil or every university student in the UK. Instead, you will usually survey a sample from the population.

The sample size depends on how big the population is. You can use an online sample calculator to work out how many responses you need.

There are many sampling methods that allow you to generalise to broad populations. In general, though, the sample should aim to be representative of the population as a whole. The larger and more representative your sample, the more valid your conclusions.

There are two main types of survey:

• A questionnaire , where a list of questions is distributed by post, online, or in person, and respondents fill it out themselves
• An interview , where the researcher asks a set of questions by phone or in person and records the responses

Which type you choose depends on the sample size and location, as well as the focus of the research.

Questionnaires

Sending out a paper survey by post is a common method of gathering demographic information (for example, in a government census of the population).

• You can easily access a large sample.
• You have some control over who is included in the sample (e.g., residents of a specific region).
• The response rate is often low.

Online surveys are a popular choice for students doing dissertation research , due to the low cost and flexibility of this method. There are many online tools available for constructing surveys, such as SurveyMonkey and Google Forms .

• You can quickly access a large sample without constraints on time or location.
• The data is easy to process and analyse.
• The anonymity and accessibility of online surveys mean you have less control over who responds.

If your research focuses on a specific location, you can distribute a written questionnaire to be completed by respondents on the spot. For example, you could approach the customers of a shopping centre or ask all students to complete a questionnaire at the end of a class.

• You can screen respondents to make sure only people in the target population are included in the sample.
• You can collect time- and location-specific data (e.g., the opinions of a shop’s weekday customers).
• The sample size will be smaller, so this method is less suitable for collecting data on broad populations.

Oral interviews are a useful method for smaller sample sizes. They allow you to gather more in-depth information on people’s opinions and preferences. You can conduct interviews by phone or in person.

• You have personal contact with respondents, so you know exactly who will be included in the sample in advance.
• You can clarify questions and ask for follow-up information when necessary.
• The lack of anonymity may cause respondents to answer less honestly, and there is more risk of researcher bias.

Like questionnaires, interviews can be used to collect quantitative data : the researcher records each response as a category or rating and statistically analyses the results. But they are more commonly used to collect qualitative data : the interviewees’ full responses are transcribed and analysed individually to gain a richer understanding of their opinions and feelings.

Next, you need to decide which questions you will ask and how you will ask them. It’s important to consider:

• The type of questions
• The content of the questions
• The phrasing of the questions
• The ordering and layout of the survey

Open-ended vs closed-ended questions

There are two main forms of survey questions: open-ended and closed-ended. Many surveys use a combination of both.

Closed-ended questions give the respondent a predetermined set of answers to choose from. A closed-ended question can include:

• A binary answer (e.g., yes/no or agree/disagree )
• A scale (e.g., a Likert scale with five points ranging from strongly agree to strongly disagree )
• A list of options with a single answer possible (e.g., age categories)
• A list of options with multiple answers possible (e.g., leisure interests)

Closed-ended questions are best for quantitative research . They provide you with numerical data that can be statistically analysed to find patterns, trends, and correlations .

Open-ended questions are best for qualitative research. This type of question has no predetermined answers to choose from. Instead, the respondent answers in their own words.

Open questions are most common in interviews, but you can also use them in questionnaires. They are often useful as follow-up questions to ask for more detailed explanations of responses to the closed questions.

The content of the survey questions

To ensure the validity and reliability of your results, you need to carefully consider each question in the survey. All questions should be narrowly focused with enough context for the respondent to answer accurately. Avoid questions that are not directly relevant to the survey’s purpose.

When constructing closed-ended questions, ensure that the options cover all possibilities. If you include a list of options that isn’t exhaustive, you can add an ‘other’ field.

Phrasing the survey questions

In terms of language, the survey questions should be as clear and precise as possible. Tailor the questions to your target population, keeping in mind their level of knowledge of the topic.

Use language that respondents will easily understand, and avoid words with vague or ambiguous meanings. Make sure your questions are phrased neutrally, with no bias towards one answer or another.

Ordering the survey questions

The questions should be arranged in a logical order. Start with easy, non-sensitive, closed-ended questions that will encourage the respondent to continue.

If the survey covers several different topics or themes, group together related questions. You can divide a questionnaire into sections to help respondents understand what is being asked in each part.

If a question refers back to or depends on the answer to a previous question, they should be placed directly next to one another.

Before you start, create a clear plan for where, when, how, and with whom you will conduct the survey. Determine in advance how many responses you require and how you will gain access to the sample.

When you are satisfied that you have created a strong research design suitable for answering your research questions, you can conduct the survey through your method of choice – by post, online, or in person.

There are many methods of analysing the results of your survey. First you have to process the data, usually with the help of a computer program to sort all the responses. You should also cleanse the data by removing incomplete or incorrectly completed responses.

If you asked open-ended questions, you will have to code the responses by assigning labels to each response and organising them into categories or themes. You can also use more qualitative methods, such as thematic analysis , which is especially suitable for analysing interviews.

Statistical analysis is usually conducted using programs like SPSS or Stata. The same set of survey data can be subject to many analyses.

Finally, when you have collected and analysed all the necessary data, you will write it up as part of your thesis, dissertation , or research paper .

In the methodology section, you describe exactly how you conducted the survey. You should explain the types of questions you used, the sampling method, when and where the survey took place, and the response rate. You can include the full questionnaire as an appendix and refer to it in the text if relevant.

Then introduce the analysis by describing how you prepared the data and the statistical methods you used to analyse it. In the results section, you summarise the key results from your analysis.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviours. It is made up of four or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with five or seven possible responses, to capture their degree of agreement.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyse your data.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

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Academic surveys

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1. Define your research objectives

Clearly outline the goals and purpose of your survey. Knowing what you want to achieve will help you design a focused and relevant survey.

2. Review existing literature

Familiarize yourself with previous research on your topic to identify gaps and opportunities for further investigation.

3. Formulate a research question or hypothesis

Develop a specific research question or hypothesis to guide your survey design and data analysis.

4. Determine your target population

Identify the group of people you want to survey, and consider the sample size needed for statistically meaningful results. Ensure that the chosen sample is representative of the population you're studying.

5. Obtain ethics approval

If your survey involves human subjects, obtain approval from your institution's ethics committee or review board before beginning data collection.

6. Develop clear, concise questions

Write questions in simple, easy-to-understand language. Avoid technical terms, jargon, or acronyms that might confuse respondents.

7. Use a mix of question types

Combine multiple-choice, open-ended, and rating scale questions to obtain diverse responses. This will make the survey more engaging and provide richer data to analyze.

8. Avoid leading or biased questions

Ensure your questions are neutral and do not steer respondents toward a specific answer. This helps collect unbiased data.

9. Pilot your survey

Before distributing the academic survey, test it with a small group of people from your target population. This helps identify any issues, ambiguities, or biases in the questions, allowing for necessary adjustments.

10. Use appropriate distribution channels

Consider the most effective channels to reach your target population, such as email, social media, or online forums.

11. Set a timeline and send reminders

Establish a clear timeline for survey completion and send reminders to encourage participation. Be transparent about the purpose of the research and how the data will be used.

12. Analyze and report your findings

Use data analysis tools to identify trends, patterns, and relationships within the data. Interpret and report your findings in a clear and accurate manner, and discuss the implications of your results in the context of existing literature.

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What is an academic survey?

An academic survey is a research tool used by scholars to gather data on a particular topic or phenomenon. It involves asking a set of structured questions to a sample of individuals or groups to collect quantitative or qualitative data.

What are the benefits of conducting an academic survey?

An academic survey can help scholars gain insights into a particular topic or phenomenon, test hypotheses, and validate theories. It can also provide empirical evidence to support research findings, inform policy decisions, and contribute to the advancement of knowledge in a particular field.

Who can conduct an academic survey?

Anyone who is interested in conducting research can use LimeSurvey to conduct an academic survey, provided they have the necessary knowledge and skills to design and execute the survey.

What are the key steps involved in conducting an academic survey?

The key steps involved in conducting an academic survey include defining the research question, designing the survey instrument, selecting the sample, administering the survey, analyzing the data, and reporting the findings.

How can I design an effective survey instrument?

To design an effective survey instrument, you should ensure that the questions are clear, concise, and unbiased. You should also consider the target audience and tailor the questions to their level of understanding and knowledge.

What is sampling in academic survey research?

Sampling is the process of selecting a subset of individuals or groups from a larger population for the purpose of conducting a survey. The sample should be representative of the population being studied to ensure the findings are valid and generalizable.

What are the different types of survey questions?

There are two main types of survey questions: open-ended questions and closed-ended questions. Open-ended questions allow respondents to provide a detailed answer in their own words, while closed-ended questions provide a list of predefined response options to choose from.

How can I ensure the confidentiality of survey respondents?

To ensure the confidentiality of survey respondents, you should avoid asking for personal identifying information, such as names or addresses. You should also ensure that the data is stored securely and only accessible to authorized individuals.

How can I increase the response rate for my survey?

To increase the response rate for your survey, you can use various techniques such as offering incentives, keeping the survey short, using a clear and compelling subject line, and following up with non-respondents.

What are some common mistakes to avoid when conducting an academic survey?

Common mistakes to avoid when conducting an academic survey include using biased questions, using a non-representative sample, asking too many questions, and failing to pre-test the survey instrument.

How can I ensure the validity and reliability of my survey findings?

To ensure the validity and reliability of your survey findings, you should use a representative sample, ensure the survey questions are clear and unbiased, use appropriate statistical analysis, and report the findings accurately and transparently.

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Academic Research: What it is + Free Tools

Academic research is critical to the success of a university, involving the whole system participating in it, whether it’s students, faculty members, or administrators. Although research is stereotypically associated with being in a laboratory mixing substances, the reality is that academic research involves all disciplines.

As a university student, you probably have many subjects to take, pending projects, and academic research to do. As part of that research, collecting information and data is essential for a final delivery that will give you an A and a 100% reliable result. Researchers use academic papers to earn colleagues’ respect, be a pioneer in their respective fields, and participate in future related research.

But how do you create an excellent quality academic research paper? Why is data collection a crucial point to it? In the following blog post, you’ll find the answers to those questions.

What is academic research?

Academic research is the best tool universities have to create or enhance knowledge and facilitate learning. Additionally, most academic research helps solve different social and economic problems in the community surrounding the university where it originated.

Academic research is a systematic process of studying a research problem or situation, where the intention is to identify facts that help solve the problem or deal with the situation.

Academic research aims to generate new knowledge that improves social development. This research is one of the essential responsibilities of a faculty member working at an educational institution. 

Mainly this focuses on scientific discoveries, conducting studies into various aspects of life, with the eventual aim of developing a more in-depth knowledge of the subject.

It’s all about using new research techniques, creating studies into untouched areas of life, and giving us a better understanding of the world in which we live. There are four types of Academic Research:

• Exploratory research to identify new situations/problems. Because of its nature, this type of research is often qualitative; however, a study with a large sample in an exploratory manner can incorporate qualitative research.
• Descriptive research identifies the characteristics of a particular phenomenon without investigating its causes.
• Explanatory research identifies cause-and-effect relationships in a problem, allowing generalizations that can apply in similar situations.
• Correlational research identifies the relationship between two or more variables and the effect on the system when a change in one of them occurs.

Characteristics of academic research

Academic research is more than just choosing a topic, collecting data, and putting it together on paper. To be considered good research, this must meet specific criteria to ensure the quality of the research. Some of the characteristics of good research are:

• Good research anchors to its topic question; this is the critical factor in the research. When coming up with the research question, try using FINER criteria (Feasible, Interesting, Novelty, Ethical, and Relevant)
• Every research follows a systematic and appropriate methodology.
• Acknowledgment of previous research is critical for the discovery of new knowledge. Using articles, journals, and investigations done in the past will give you a notion of the study’s direction.
• The criteria of good research is that it is representative and generalizable; this refers to the sample’s ability to represent a larger group with minimal variation.
• External validation of the research is a huge differentiator, as it gives recognition to the investigation for it to be used in future studies. 

Objectives of academic research

Academic research seeks to advance new knowledge and has relevance based on solving problems that contribute to the improvement of society.

When you perform academic research, you are essentially trying to solve a mystery—you want to know how something works or why something happened. In other words, you want to answer a question that you, academics, and professionals have about the world. This is one of the most fundamental reasons for performing research.

The process doesn’t stop right after solving the problem. Academic research needs to be presented, the most common way is through an academic paper, but if the paper is outstanding in quality, it can be published in professional journals.

Importance of academic research

As we have said before, academic research facilitates learning, highlights key issues in society, and can promote the growth of students.

• Facilitates the learning process: It is the best activity to develop or improve knowledge and allows to understand specific problems through varied angles that were never identified or talked about much. While conducting the study, you collect the evidence based on facts and rationale. This is how academic research papers open the doors for more discourse and debate.
• Highlights the problems: Generally, academic research highlights some problems that prevail in society, which could be related to cultural norms, health, education, specific practices, etc.
• Leads to the personal growth of students: This process helps in the development of skills. Students learn to identify a problem and arrive at a possible solution or develop a point of view on a specific issue. In addition, they develop skills such as big data analysis, critical thinking, time management, and organization.

Difference between academic and professional research  

There are several types of research, depending on the perspective and objective of each one. If we talk about academic research, it mainly focuses on making new discoveries for the scientific community.

Instead, professional research is more geared towards solving a specific problem for an organization, often a company or its clients. It could be called the next step of the investigation because it is at the same time collecting information and finding a solution, only applied to different approaches and objectives of life, one academic and one more from working life.

Academic research focuses on the research objectives and questions that arise from independent researchers. It uses formal, scientific, and systematic procedures to discover answers and to prove or reject existing theories.

On the other hand, professional research is defined as work carried out to achieve the objectives of an organization and focuses on the research objectives that arise from the requirements of the company. 

You may or may not use formal, scientific, and systematic procedures to discover answers. It is not based on theory and may not require a representative sample.

LEARN MORE: Descriptive Research vs. Correlational Research

Academic research methods

Research methods are the strategies, processes, or techniques used to collect data or analyze evidence to uncover new information or better understand a topic.

Different types of research methods use different tools for data collection. The principal tools for this type of research are interviews, focus groups, observation, and surveys.

• Interviews . A qualitative interview is the best research technique that allows the researcher to gather data from the subject using open-ended questions. The most important aspect of an interview is how it is made. Typically, it would be a one-on-one conversation focusing on the substance of the question.
• Focus group. Focus group is one of the best examples of qualitative data in education or in academic research. It is also a qualitative approach to gathering information. The main difference from an interview is that the group is composed of 6 – 10 people purposely selected to understand the perception of a social group. Rather than trying to understand a more significant population in the form of statistics, the focus group is directed by a moderator to keep the group in topic conversation. Hence, all the participants contribute to the research.
• Observation. Observation is a method of data collection that incorporates the researcher into the natural setting where the participants or the phenomenon is happening. This enables the researcher to see what is happening in real-time, eliminating some bias that interviews or focus groups can have by having the moderator intervene with the subjects.
• Surveys . A survey is a research method used to collect data from a determined population to gain information on a subject of interest. The nature of the survey allows for gathering the information at any given time and typically takes no time, depending on the research. Another benefit of a survey is its quantitative approach, which makes it easier to present it comprehensively.

Tips for doing academic research through surveys

Data collection is the process by which information is collected and measured based on our interests, taking the right path to answer specific research questions , test our hypotheses and predict the results.

The data collected should be similar to that of the study area, while the methods vary depending on the rules and regulations of each industry. Emphasis must be placed on ensuring accuracy and honesty in data collection, this is very important. 

Regardless of what qualitative and quantitative research methods you are conducting in your academic research, data collection must be accurate, which is essential to maintaining the integrity of academic research.

01. Perform effective sampling

Survey sampling size has to do with correctly defining the number of participants. This is one of the main steps in designing and organizing a survey. 

• Main concept : Before starting your academic research survey, you must confirm the study population and give it the correct follow-up. We must be aware that a change throughout the research process can critically affect the reality of the data collected. 
• Diversity: Ensuring the diversity of your sample and getting them to participate can be tedious work. However, it is very important to have a representative sample of the population to obtain richness in the responses. 
• Clarity : There are several limitations to determining the size and structure of the population sample. It is crucial that researchers describe their limitations and maintain the procedures they follow to select the sample transparently so that the results of surveys are seen from the correct perspective.

02. Select Survey Software 

We at QuestionPro are interested in fostering an interest in students in conducting effective academic research. It is because of students that we have different tools that will help them achieve it effectively:

The platform allows you to select different types of questions such as multiple choice , open , matrix type , satisfaction questions with smileys , and many more. 

In addition, our survey software allows students to email their survey, share it on social media, send it via SMS, etc., to facilitate data collection. 

03. Analysis of the responses

Analyzing the responses will help to know in detail the data obtained in the data collection process and confirm or refute the established hypothesis. 

With QuestionPro, it is possible to view survey data responses in real time. This way, you can effectively perform in-depth analysis for your academic research.

We have for you this article on data analysis, techniques, and step-by-step guide .

04. Research report

There are several essential points to consider when reporting the research results. All reports should be educational, relevant to the target audience, and customized to each company’s needs. 

The report of your academic research can be presented through visual presentations, written on an academic paper, or electronic reports. The way you present your survey results will make a big difference. A complete, formal report usually includes the following elements:

• Cover Sheet
• Introduction
• Research Purpose
• Survey Sample
• Methodology
• Conclusion and Recommendations
• Contact Information

QuestionPro platform also provides you with survey dashboards that will be very useful for presenting a report of results.

Online surveys will help you obtain the data you need for decision-making in your academic research. However, it is important that before collecting a series of data, you choose the right topic, the right questions to ask, and the type of survey you will carry out. 

The design of your survey and the target audience, that is, the right people to answer the questions in your questionnaire, will depend on all of the above.

We know that surveys play an important role in educational projects. That is why our platform allows you to conduct quantitative and qualitative research, polls, questionnaires, and online surveys. 

QuestionPro is a global company concerned about education. That’s why we offer academic alliances so that university students and teachers obtain our tool to take online exams, create forms, conduct research projects, and perform data analysis.

If you are interested in using our platform to carry out academic research, we invite you to learn about the benefits of our academic alliances. Take advantage of everything you can achieve by implementing our tool into your education services and start carrying powerful research to your education institution.

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Academic Research & Scholarly Surveys

Student plan discount, discount request form, surveys for academics and students.

The collection and analysis of raw data is a vital part of many academic research and scholarly project. The collected data adds weight to your research and its analysis supports or disproves your theory. Surveys and questionnaires can be used across every discipline and responses collected using varying methodologies.

With our online survey tool you can download your results ready for including in your thesis or export data to excel for further analysis. Whichever methodology you choose, our student survey software is a convenient, affordable and efficient way to collect and analyse your data. We also offer a University Plan allowing site-wide access for staff and students to run surveys.

How to use online surveys in your academic research

Surveys are an imperative aspect of many academic and scholarly programmes and projects. When you have hundreds of responses to collect and data to analyse, conducting this research with paper surveys proves very time consuming. By using an online survey software, you remove the additional hard work so you can concentrate on analysing your findings.

With an online survey software you have the flexibility to conduct multiple studies using multiple methodologies, all from a centralised location. Whether you are conducting quantitative research with cross-sectional studies, opinion polls, longitudinal studies , social attitude questionnaires or qualitative research with open text surveys, SmartSurvey will be able to help.

Surveys can also be used to hone your research methodology. By sending a pre-test survey to a sample of your audience you can find out if your questions are easy to understand and ensure you’re using the best distribution channel. This will ultimately save you time and increase your survey completion rates.

Examples of academic research surveys

Here are a few types of research surveys and how they can be used by academics and scholars:

Economic and social research

Social science is, broadly speaking, the study of people and the way we influence the world around us. Social and economic research therefore plays a vital role in many organisations, from government to public sector services. Conducting surveys is an imperative aspect of this research, so we offer advanced and flexibility tools to manage most research projects.

Healthcare and medical research

Investigate patient demographics, identify common health issues, and assess healthcare access, and much more.

Business studies

Looking to find out what business are in your area, how many people they employ, or where there are gaps in the market? Reach out to these industries with quick to complete and user-friendly online surveys.

Lifestyle and sports science

Use lifestyle and health surveys to collect information from your target audience about their exercise habits, eating routines and sleeping patterns, and much more.

Childhood development and education

Online surveys are a user-friendly way to conduct research projects on classroom climate, parent and school relationships, student satisfaction and concentration, and lots more.

Dissertation research

One of the most commonly used methods of collecting data for dissertation topics is the online survey. SmartSurvey enables you to create surveys, distribute them and get the answers you need, quickly.

Demographic surveys

We can help you reach the exact target audience you need for your academic research. Select who you need to survey (age, gender, location, profession, household etc) and our Live Audience feature will do the rest. You’ll get the exact number of responses you need from the right people, fast.

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Research Question Examples 🧑🏻‍🏫

25+ Practical Examples & Ideas To Help You Get Started 

By: Derek Jansen (MBA) | October 2023

A well-crafted research question (or set of questions) sets the stage for a robust study and meaningful insights.  But, if you’re new to research, it’s not always clear what exactly constitutes a good research question. In this post, we’ll provide you with clear examples of quality research questions across various disciplines, so that you can approach your research project with confidence!

Research Question Examples

• Psychology research questions
• Business research questions
• Education research questions
• Healthcare research questions
• Computer science research questions

Examples: Psychology

Let’s start by looking at some examples of research questions that you might encounter within the discipline of psychology.

How does sleep quality affect academic performance in university students?

This question is specific to a population (university students) and looks at a direct relationship between sleep and academic performance, both of which are quantifiable and measurable variables.

What factors contribute to the onset of anxiety disorders in adolescents?

The question narrows down the age group and focuses on identifying multiple contributing factors. There are various ways in which it could be approached from a methodological standpoint, including both qualitatively and quantitatively.

Do mindfulness techniques improve emotional well-being?

This is a focused research question aiming to evaluate the effectiveness of a specific intervention.

How does early childhood trauma impact adult relationships?

This research question targets a clear cause-and-effect relationship over a long timescale, making it focused but comprehensive.

Is there a correlation between screen time and depression in teenagers?

This research question focuses on an in-demand current issue and a specific demographic, allowing for a focused investigation. The key variables are clearly stated within the question and can be measured and analysed (i.e., high feasibility).

Examples: Business/Management

Next, let’s look at some examples of well-articulated research questions within the business and management realm.

How do leadership styles impact employee retention?

This is an example of a strong research question because it directly looks at the effect of one variable (leadership styles) on another (employee retention), allowing from a strongly aligned methodological approach.

What role does corporate social responsibility play in consumer choice?

Current and precise, this research question can reveal how social concerns are influencing buying behaviour by way of a qualitative exploration.

Does remote work increase or decrease productivity in tech companies?

Focused on a particular industry and a hot topic, this research question could yield timely, actionable insights that would have high practical value in the real world.

How do economic downturns affect small businesses in the homebuilding industry?

Vital for policy-making, this highly specific research question aims to uncover the challenges faced by small businesses within a certain industry.

Which employee benefits have the greatest impact on job satisfaction?

By being straightforward and specific, answering this research question could provide tangible insights to employers.

Examples: Education

Next, let’s look at some potential research questions within the education, training and development domain.

How does class size affect students’ academic performance in primary schools?

This example research question targets two clearly defined variables, which can be measured and analysed relatively easily.

Do online courses result in better retention of material than traditional courses?

Timely, specific and focused, answering this research question can help inform educational policy and personal choices about learning formats.

What impact do US public school lunches have on student health?

Targeting a specific, well-defined context, the research could lead to direct changes in public health policies.

To what degree does parental involvement improve academic outcomes in secondary education in the Midwest?

This research question focuses on a specific context (secondary education in the Midwest) and has clearly defined constructs.

What are the negative effects of standardised tests on student learning within Oklahoma primary schools?

This research question has a clear focus (negative outcomes) and is narrowed into a very specific context.

Need a helping hand?

Examples: Healthcare

Shifting to a different field, let’s look at some examples of research questions within the healthcare space.

What are the most effective treatments for chronic back pain amongst UK senior males?

Specific and solution-oriented, this research question focuses on clear variables and a well-defined context (senior males within the UK).

How do different healthcare policies affect patient satisfaction in public hospitals in South Africa?

This question is has clearly defined variables and is narrowly focused in terms of context.

Which factors contribute to obesity rates in urban areas within California?

This question is focused yet broad, aiming to reveal several contributing factors for targeted interventions.

Does telemedicine provide the same perceived quality of care as in-person visits for diabetes patients?

Ideal for a qualitative study, this research question explores a single construct (perceived quality of care) within a well-defined sample (diabetes patients).

Which lifestyle factors have the greatest affect on the risk of heart disease?

This research question aims to uncover modifiable factors, offering preventive health recommendations.

Examples: Computer Science

Last but certainly not least, let’s look at a few examples of research questions within the computer science world.

What are the perceived risks of cloud-based storage systems?

Highly relevant in our digital age, this research question would align well with a qualitative interview approach to better understand what users feel the key risks of cloud storage are.

Which factors affect the energy efficiency of data centres in Ohio?

With a clear focus, this research question lays a firm foundation for a quantitative study.

How do TikTok algorithms impact user behaviour amongst new graduates?

While this research question is more open-ended, it could form the basis for a qualitative investigation.

What are the perceived risk and benefits of open-source software software within the web design industry?

Practical and straightforward, the results could guide both developers and end-users in their choices.

Remember, these are just examples…

In this post, we’ve tried to provide a wide range of research question examples to help you get a feel for what research questions look like in practice. That said, it’s important to remember that these are just examples and don’t necessarily equate to good research topics . If you’re still trying to find a topic, check out our topic megalist for inspiration.

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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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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

Research Question Generator: Best Tool for Students

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The choice of research topic is a vital step in the process of any academic task completion. Whether you’re working on a small essay or a large dissertation, your topic will make it fail or fly. The best way to cope with the naming task and proceed to the writing part is to use our free online tool for title generation. Its benefits are indisputable.

• The tool generates research questions, not just topics
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Research Question Generator: How to Use

Using our research question generator tool, you won’t need to crack your brains over this part of the writing assignment anymore. All you need to do is:

• Insert your study topic of interest in the relevant tab
• Choose a subject and click “Generate topics”
• Grab one of the offered options on the list

The results will be preliminary; you should use them as an initial reference point and refine them further for a workable, correctly formulated research question.

Research Questions: Types & Examples

Depending on your type of study (quantitative vs. qualitative), you might need to formulate different research question types. For instance, a typical quantitative research project would need a quantitative research question, which can be created with the following formula:

Variable(s) + object that possesses that variable + socio-demographic characteristics

You can choose among three quantitative research question types: descriptive, comparative, and relationship-based. Let's consider each type in more detail to clarify the practical side of question formulation.

Descriptive

As its name suggests, a descriptive research question inquires about the number, frequency, or intensity of something and aims to describe a quantitative issue. Some examples include:

• How often do people download personal finance apps in 2022?
• How regularly do Americans go on holidays abroad?
• How many subscriptions for paid learning resources do UK students make a year?

Comparative

Comparative research questions presuppose comparing and contrasting things within a research study. You should pick two or more objects, select a criterion for comparison, and discuss it in detail. Here are good examples:

• What is the difference in calorie intake between Japanese and American preschoolers?
• Does male and female social media use duration per day differ in the USA?
• What are the attitudes of Baby Boomers versus Millennials to freelance work?

Relationship-based

Relationship-based research is a bit more complex, so you'll need extra work to formulate a good research question. Here, you should single out:

• The independent variable
• The dependent variable
• The socio-demographics of your population of interest

Let’s illustrate how it works:

• How does the socio-economic status affect schoolchildren’s dropout rates in the UK?
• What is the relationship between screen time and obesity among American preschoolers?

Research Question Maker FAQ

In a nutshell, a research question is the one you set to answer by performing a specific academic study. Thus, for instance, if your research question is, “How did global warming affect bird migration in California?," you will study bird migration patterns concerning global warming dynamics.

You should think about the population affected by your topic, the specific aspect of your concern, and the timing/historical period you want to study. It’s also necessary to specify the location – a specific country, company, industry sector, the whole world, etc.

A great, effective research question should answer the "who, what, when, where" questions. In other words, you should define the subject of interest, the issue of your concern related to that subject, the timeframe, and the location of your study.

If you don’t know how to write a compelling research question, use our automated tool to complete the task in seconds. You only need to insert your subject of interest, and smart algorithms will do the rest, presenting a set of workable, interesting question suggestions.

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• Writing Strong Research Questions | Criteria & Examples

Writing Strong Research Questions | Criteria & Examples

Published on October 26, 2022 by Shona McCombes . Revised on November 21, 2023.

A research question pinpoints exactly what you want to find out in your work. A good research question is essential to guide your research paper , dissertation , or thesis .

All research questions should be:

• Focused on a single problem or issue
• Researchable using primary and/or secondary sources
• Feasible to answer within the timeframe and practical constraints
• Specific enough to answer thoroughly
• Complex enough to develop the answer over the space of a paper or thesis
• Relevant to your field of study and/or society more broadly

Table of contents

How to write a research question, what makes a strong research question, using sub-questions to strengthen your main research question, research questions quiz, other interesting articles, frequently asked questions about research questions.

You can follow these steps to develop a strong research question:

• Choose your topic
• Do some preliminary reading about the current state of the field
• Narrow your focus to a specific niche
• Identify the research problem that you will address

The way you frame your question depends on what your research aims to achieve. The table below shows some examples of how you might formulate questions for different purposes.

Using your research problem to develop your research question

Note that while most research questions can be answered with various types of research , the way you frame your question should help determine your choices.

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Research questions anchor your whole project, so it’s important to spend some time refining them. The criteria below can help you evaluate the strength of your research question.

Focused and researchable

Feasible and specific

Complex and arguable

Relevant and original

Chances are that your main research question likely can’t be answered all at once. That’s why sub-questions are important: they allow you to answer your main question in a step-by-step manner.

Good sub-questions should be:

• Less complex than the main question
• Focused only on 1 type of research
• Presented in a logical order

Here are a few examples of descriptive and framing questions:

• Descriptive: According to current government arguments, how should a European bank tax be implemented?
• Descriptive: Which countries have a bank tax/levy on financial transactions?
• Framing: How should a bank tax/levy on financial transactions look at a European level?

Keep in mind that sub-questions are by no means mandatory. They should only be asked if you need the findings to answer your main question. If your main question is simple enough to stand on its own, it’s okay to skip the sub-question part. As a rule of thumb, the more complex your subject, the more sub-questions you’ll need.

Try to limit yourself to 4 or 5 sub-questions, maximum. If you feel you need more than this, it may be indication that your main research question is not sufficiently specific. In this case, it’s is better to revisit your problem statement and try to tighten your main question up.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .

A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis —a prediction that will be confirmed or disproved by your research.

As you cannot possibly read every source related to your topic, it’s important to evaluate sources to assess their relevance. Use preliminary evaluation to determine whether a source is worth examining in more depth.

This involves:

• Reading abstracts , prefaces, introductions , and conclusions
• Looking at the table of contents to determine the scope of the work
• Consulting the index for key terms or the names of important scholars

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (“ x affects y because …”).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses . In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

Formulating a main research question can be a difficult task. Overall, your question should contribute to solving the problem that you have defined in your problem statement .

However, it should also fulfill criteria in three main areas:

• Researchability
• Feasibility and specificity
• Relevance and originality

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McCombes, S. (2023, November 21). Writing Strong Research Questions | Criteria & Examples. Scribbr. Retrieved September 25, 2024, from https://www.scribbr.com/research-process/research-questions/

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Report: Stop-Outs Don’t Know About Support Services on Campus

Not all college students know about support measures available to them at their college, making them more vulnerable to stopping out. New research indicates that institutional leaders should work to bridge communication gaps to increase student success.

By  Ashley Mowreader

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A majority of students aren’t aware of all the student services provided by their college or university, but students who stopped out are more likely to be unfamiliar with supports.

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Each year, a large number of college students walk away from their education because of personal and financial concerns, as well as academic challenges that impede their success. A new study shows students who stop out are less likely to be aware of resources that were available to them at their institution, which could be tied to their decision to leave.

In Tyton Partners’ annual Listening to Learners study, only half of all students surveyed say their institution offered academic and career advising, financial aid counseling, and mental health counseling, despite an overwhelming majority of institutions providing these supports. Students who had stopped out are less likely to know these services were offered, with only 44 percent recognizing academic advising was available and 32 percent being aware of mental health supports.  

By the Numbers 

The number of students with some college but no credential has grown to 40 million, as of June data from the National Student Clearinghouse Research Center.

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Tyton Partners’ research shows learners who are aware of a greater number of support offices are more likely to remain enrolled in higher education, indicating that increased communication about resources and supports can support student persistence and completion.  

General lack of awareness: Many colleges and universities offer a suite of student support services that can aid in students’ learning, health and well-being, and future planning, as well as guide them through higher education. A majority of students, however, remain unaware of the full range of services available to them, and some student groups are more likely to be left behind.

Methodology 

The Listening to Learners 2024 survey includes current and former undergraduates at 850 unique two- and four-year institutions. Of the 1,600 respondents, over one-quarter of respondents were first-generation students and 19 percent were over 25 years old.

The report also uses staff, faculty and administrator survey responses from Driving Toward a Degree 2024 to compare against student responses.

Among all respondents, students are most likely to report their institution offers financial aid counseling (55 percent), followed by academic advising (51 percent), career advising (51 percent) and mental health counseling (50 percent).

Traditional academic support offerings, such as the registrar’s office (31 percent), tutoring (34 percent) and library assistance (35 percent) are only recognized by around one-third of students and used by fewer than one-quarter.

Students reported the least awareness of accessibility or disability services, emergency assistance and military benefits, which could be tied in part to the specific populations these services support.

Vulnerable students: Tyton Partners’ research revealed some student groups were less likely than their peers to be aware of services that could support their success.

Students who had left higher education (n=66) say their previous college or university offered financial aid counseling (55 percent), academic advising (44 percent), career advising (36 percent) or mental health counseling (32 percent). Fewer than one-third of respondents indicate they had ever interacted with academic advising, and just around one-quarter used financial aid counseling. Only 12 percent had interacted with mental health counseling, despite mental health being one of the most commonly cited reasons students stop out of higher education.

The report also identified large gaps in awareness among students who took classes fully online (n=490) or who have a disability (n=325). While both groups have higher awareness of mental health resources (50 percent), online students are more likely to point to IT or tech support as an available resource (44 percent) over academic advising (26 percent).

Students with disabilities are most aware of campus police or security (46 percent) and only 27 percent of these learners know about the disability services office. More concerningly, only 12 percent of students with disabilities say they had personally interacted with the accommodations office.

Fewer than 2 percent of online students and students with disabilities participated in tutoring or academic support, as well.

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So what? Colleges and universities should work to bridge this awareness gap because it has implications for student retention, according to the report. Some specific actions campus leaders can take:

• Streamline communication. Just over half (55 percent) of respondents say the institution effectively communicates information about support services to learners. Eighteen percent disagree or strongly disagree. Students say they prefer to receive information via email (personal or institutional address) or via mobile text.
• Increase awareness of all resources. Students who indicated they were aware of five or more student support services are 13 percentage points more likely to say they would persist in higher education (77 percent), compared to their peers who are aware of one to four services (64 percent). In a previous survey, practitioners indicate a lack of coordination across departments as their greatest barrier to effective communication (33 percent), so breaking institutional silos and streamlining support awareness can aid this effort.
• Address student safety. Students are more likely to say they would stay in higher education (at their institution or at another institution) if they have high confidence in their physical and emotional safety, compared to their peers who express lower levels of physical and emotional safety. “A high sense of safety is critical for institutions to foster a supportive and inclusive environment where students feel secure, valued, and motivated to pursue their academic and personal goals,” according to the report.
• Consider the role of financial aid. Tyton’s report includes data from students who had left higher education but returned (n=447). These students are more likely to say the Free Application for Federal Student Aid has impacted their enrollment decision, compared to their peers who have never stopped out, with 28 percent indicating they would wait to re-enroll until they understand their financial aid for the next year and 19 percent considering transferring because of FAFSA delays.

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