Research Topics: 30 Practical Ideas for Students
How to choose a research topic
You need a research topic for your thesis, but most lists online provide only titles. An interesting title is not enough to carry out the study. Before you commit, you need to know whom you will survey, which constructs you will measure, where the data will come from, and whether you will run the model in SPSS or SmartPLS.
A topic that suits a student usually has a manageable scope, clearly defined research variables, and respondents you can reach. If the topic requires internal data from a company that will not give you access, the main risk is data collection rather than analysis. You can also read how to identify a research topic before choosing a specific direction.
| Check criterion | Question you need to answer | Sign that you should keep the topic |
|---|---|---|
| Research problem | What does the topic explain or predict | The independent and dependent variables are clear |
| Survey population | Who will answer the questionnaire | You can reach this group during the thesis period |
| Scale | Are reference scales available for the constructs | You can adapt them into Likert indicators |
| Data | How will you obtain .sav or .csv data | You have a specific questionnaire distribution channel, not only an intention |
| Scope | Which location, age group, or industry does the topic cover | One student can complete it within the assigned deadline |
| Analysis | Which tool is needed to test the model | SPSS or SmartPLS can answer the research question |
| Ethics and privacy | Does the study involve sensitive or personal information | You collect only necessary information and provide a clear notice |
A practical check is to write three sentences: “I will survey whom?”, “Which variables will I measure?”, and “What will I use the results to explain?” If you cannot complete one of the three, the topic is still too broad. If you need data from several organizations, narrow the scope before presenting it to your supervisor.
Your research topic also needs to match your methods background. For a model with several latent variables and a Likert questionnaire, SPSS is suitable for Cronbach's Alpha, EFA, and regression. SmartPLS is suitable when the model includes latent variables, mediation relationships, or a structural model that needs to be assessed with PLS-SEM. Do not put both tools in your proposal if you cannot explain which question each tool answers.
Research topics by group
The scientific research topics below are written in a form that can be converted into a quantitative model. Each topic includes a research direction, independent variables, and a dependent variable. You still need to read the literature, select the context, and check the scales before using one.
Shopping behavior and e-commerce
1. The effect of e-commerce platform service quality on students' repurchase intention. The independent variables include reliability, responsiveness, security, and convenience. The dependent variable is repurchase intention. The survey population can be students who purchased from a specific platform within the last six months.
2. The effect of online reviews on young consumers' cosmetic purchase decisions. The independent variables include usefulness, credibility, and the number of reviews. The dependent variable is purchase decision. Define “young consumers” clearly by age or sample group instead of using an unclear concept.
3. The effect of sales livestreams on students' purchase intention. The independent variables can include interaction, seller attractiveness, and trust. The dependent variable is purchase intention. Data are usually easier to collect if you choose one platform and one product group.
4. The effect of perceived value on loyalty to food delivery applications. The independent variables include convenience value, economic value, and emotional value. The dependent variable is loyalty. Survey people who have used the application rather than people who have never had the relevant experience.
Technology and system acceptance
5. Factors affecting students' intention to use e-wallets. The independent variables can include perceived usefulness, perceived ease of use, trust, and perceived risk. The dependent variable is usage intention. This topic fits a TAM model, but you need to explain why each additional variable belongs in the model.
6. Factors affecting acceptance of AI tools for learning support. The independent variables include perceived usefulness, ease of use, concerns about accuracy, and subjective norm. The dependent variable is continued usage intention. Because these tools change quickly, the questionnaire should specify the type of tool and the survey period.
7. The effect of digital banking application quality on user satisfaction. The independent variables include efficiency, security, interface, and support. The dependent variable is satisfaction. Do not ask respondents to provide account numbers, phone numbers, or transaction data.
8. The effect of user experience on continued usage intention for online learning platforms. The independent variables include ease of use, content quality, and interaction. The dependent variable is continued usage intention. The sample can come from students who are currently taking or have completed an online course.
Education and employment
9. Factors affecting students' intention to enroll in online courses. The independent variables include usefulness, cost, flexibility, and social influence. The dependent variable is enrollment intention. The screening question should establish whether respondents know about this form of learning.
10. The effect of training service quality on student satisfaction. The independent variables include teaching quality, facilities, academic support, and responsiveness. The dependent variable is satisfaction. If you survey within one university, limit the study to one department or program so that the interpretation has a clear basis.
11. Factors affecting final-year students' intention to work for a company. The independent variables include development opportunities, expected income, work environment, and company reputation. The dependent variable is application intention. Distinguish between “intention” and a decision that has already occurred.
12. The effect of perceived career competence on job-search confidence. The independent variables include technical skills, communication skills, and internship experience. The dependent variable is job-search confidence. These variables need to be written as statements that respondents can rate on the same scale.
Marketing, services, and tourism
13. The effect of social media marketing on brand awareness among young customers. The independent variables include entertainment, interaction, informativeness, and personalization. The dependent variable is brand awareness. Choose one brand or industry instead of surveying “all brands.”
14. The effect of service quality on tourists' intention to return. The independent variables include reliability, responsiveness, empathy, and tangibles. The dependent variable is return intention. The questionnaire should specify which destination service the respondent used.
15. Factors affecting customer satisfaction at coffee shops. The independent variables include beverage quality, atmosphere, price, and service attitude. The dependent variable is satisfaction. Data collection is easier if you limit the study to one area or one chain.
16. The effect of brand experience on customer loyalty. The independent variables include sensory, emotional, and behavioral experience. The dependent variable is loyalty. The model needs to explain why these experiences relate to the selected brand.
Pharmacy and health research topics
17. Factors affecting consumers' intention to purchase dietary supplements. The independent variables include trust, perceived benefits, perceived risk, and social influence. The dependent variable is purchase intention. Distinguish dietary supplements from therapeutic medicines in the scope section.
18. The effect of knowledge and perceptions on students' use of over-the-counter medicines. The independent variables include knowledge, perceived risk, and access to information. The dependent variable is self-medication behavior. The questionnaire must be clear and neutral and should not ask respondents to disclose identifiable health information.
19. The effect of pharmacy counseling quality on customer satisfaction. The independent variables include clarity, completeness, attentiveness, and the ability to answer questions. The dependent variable is satisfaction. Specify the period during which customers received the counseling.
20. Factors affecting intention to use medication reminder applications. The independent variables include perceived usefulness, ease of use, trust, and privacy concerns. The dependent variable is usage intention. If your sample includes caregivers or patients, specify which group is the unit of analysis.
Pharmacy research topics often sit between user behavior and professional knowledge. If you do not have access to medical records, pharmacy data, or patient groups, choose a survey design about perceptions and intentions rather than claiming to measure treatment effectiveness.
Suggested models and scales
You can use TAM for technology acceptance topics, with perceived usefulness and perceived ease of use as explanatory variables for usage intention. The original source of TAM is (Davis, 1989). For behavioral intention generally, TPB provides the variable groups attitude, subjective norm, and perceived behavioral control (Ajzen, 1991).
If the topic focuses on technology services, UTAUT can suggest performance expectancy, effort expectancy, and social influence variables (Venkatesh et al., 2003). When studying consumer contexts, UTAUT2 adds factors that fit individual users more closely (Venkatesh et al., 2012). You do not need to include every variable from the original model. Keep only the variables that fit your research question and data-collection capacity.
| Topic group | Suggested model or scale | Common dependent variable | Suitable tool |
|---|---|---|---|
| E-wallets, AI, online learning | TAM, (Davis, 1989) | Usage intention | SPSS or SmartPLS |
| Consumer behavior and purchase intention | TPB, (Ajzen, 1991) | Purchase intention, purchase behavior | SPSS or SmartPLS |
| Digital platform acceptance | UTAUT, (Venkatesh et al., 2003) | Usage intention | SmartPLS if the model has latent variables |
| Personal consumer applications | UTAUT2, (Venkatesh et al., 2012) | Continued usage intention | SPSS or SmartPLS |
| Service quality | SERVQUAL, (Parasuraman et al., 1988) | Satisfaction, return intention | SPSS |
| Attitude scales | Likert, (Likert, 1932) | Latent-variable rating score | SPSS or SmartPLS |
When designing the model, draw an arrow from each independent variable to the dependent variable. Each arrow needs a hypothesis, such as “H1: Perceived usefulness has a positive effect on e-wallet usage intention.” For a model with a mediator or moderator, explain the mechanism before running the analysis. Do not add a variable simply because another paper included it.
For the scale, find the original paper, read the construct definition, and adapt the wording to your context. The indicators should measure in the same direction unless you deliberately design a reverse-coded item and recode it before running the analysis. Once the questionnaire is complete, state clearly that the scale is adapted from previous research and is not yet validated for your sample until you test it.
Where to obtain data and how large the sample should be
For a student survey, practical data sources can include classes, clubs, academic groups, or online communities that match the sampling criteria. For customers, you can distribute the questionnaire at a service location or through a user community, but you need screening questions. Keep the original data file, the cleaned file, and a record of every step used to remove responses.
You can use fillform.info, DoThesis's Vietnamese form tool, to create the questionnaire and collect responses. Google Forms is a familiar alternative. Whichever tool you use, make the main indicators required, limit respondents to one response when appropriate, and do not collect identifying information that the study does not need.
Sample size must be connected to the number of indicators and the analysis method. A commonly used rule is 5 to 10 observations per indicator (Hair et al., 2010). For regression, the practical formula of n at or above 50 + 8m, where m is the number of independent variables, is given in (Tabachnick and Fidell, 2013). This is a planning reference, not a reason to collect exactly the minimum when some data may later be removed.
| Situation | Initial estimate | Additional checks needed |
|---|---|---|
| Questionnaire with 20 indicators | 100 to 200 responses under the 5 to 10 times rule | Number of factors and model complexity |
| Regression with 6 independent variables | Minimum under 50 + 8m is 98 | Invalid responses and control variables |
| Known finite population | You can refer to the finite-population formula (Yamane, 1967) | Population size and response rate |
| EFA with several scale groups | The sample must be adequate for the number of variables and factor structure | KMO, communalities, and factor loadings |
Do not report the number of questionnaires distributed instead of the number of valid cases. If you receive 260 responses but 18 contain many missing answers or select the same column throughout, report the remaining number after cleaning. Keep the raw data file so you can explain why particular rows were removed if your supervisor asks.
Topics to avoid
Avoid topics that use the word “comprehensive” without defining the population, location, or period. A topic such as “factors affecting online shopping behavior among Vietnamese consumers” is beyond the sampling capacity of most students. Narrow it to students at one university, users of one platform, or customers buying one product group.
Be careful with topics that require proprietary data. Research on a bank's business performance, patients' medication adherence, or employee productivity will be difficult if you cannot access the data. You can shift to perceptions, intentions, or satisfaction measured through a questionnaire if the research question permits it.
A topic with too many mediators, moderators, and hypotheses can also exceed your available time. A model with many arrows is not automatically stronger. Each variable increases the number of items, the sample-size requirement, and the amount of explanation needed in the results chapter.
Finally, do not choose a topic only because there are many sample papers to copy. Using their structure as a reference is reasonable, but copying wording, questionnaires, or models without citing the source creates plagiarism risk. Check your citations and similarity level with Turnitin checking, and review the guidance on plagiarism before submitting the draft.
Common mistakes when finalizing a topic
The first mistake is naming the topic before identifying the variables. This forces you to fill a title that is already too broad. Start with the problem, population, and dependent variable, then write the title.
The second mistake is using “effect” when the design measures self-reported data at one point in time through a questionnaire. In the proposal, you can study relationships or effects within a theoretical model, but the conclusion must remain cautious and should not turn an observed association into an absolute causal claim.
The third mistake is failing to keep the unit of analysis consistent. If the questionnaire is for e-wallet users, each row of data must represent one eligible respondent. You cannot mix responses from people who have never used an e-wallet with those from frequent users and interpret them as one group.
The fourth mistake is taking a scale from one paper without reading its definition. A construct can have the same name but be measured differently in another context. Create a table with the variable name, definition, source, number of indicators, and adaptation method before putting it into the questionnaire.
The fifth mistake is promising a sample size without a collection channel. In the proposal, state where you will distribute the questionnaire, what the sampling criteria are, how long collection is expected to take, and how invalid responses will be removed. If you are writing an undergraduate thesis, also check your department's formatting and methods requirements.
Frequently asked questions
What is a research topic, and how is it different from a thesis topic?
A research topic is a question or problem studied through a systematic method. A thesis topic is a research topic developed within an educational program, usually with limits on time, sample, and the department's presentation requirements.
For a student conducting quantitative research, a good topic must be convertible into a model, hypotheses, questionnaire, and analyzable data. The title is only the starting point and does not replace the research design.
How do I choose a scientific research topic for which data will be easy to collect?
Choose a group that you can reach legally and consistently, such as students, users of one application, or customers of one service type. Before presenting the topic, ask several people from the intended sample whether they fit the criteria and are willing to complete the questionnaire.
You should also write the screening question in advance. If you do not know how you will confirm that a respondent is eligible, the sample scope may still be unclear.
Which variables should I choose for a pharmacy research topic?
You can study perceptions, trust, usage intention, satisfaction, or the behavior of medicine and pharmacy-service users. The variables must match your access to data and your professional background.
If you do not have clinical data or patient records, avoid setting a goal of evaluating treatment effectiveness. A survey about pharmacy counseling quality or intention to use a medication reminder application is more suitable for questionnaire data if you define the population clearly.
How large should the sample be for a research topic?
There is no fixed number for every study. Consider the number of indicators, number of independent variables, analysis method, factor structure, and proportion of responses that may be removed. The rule of 5 to 10 observations per indicator (Hair et al., 2010) and the regression formula 50 + 8m (Tabachnick and Fidell, 2013) can provide planning benchmarks.
Collect more than the expected minimum if your survey channel allows it. Then report transparently how many responses you received, how many were removed, and how many were used in the analysis.
Can I use a previous student's topic as the basis for a new topic?
You can use an older topic to find a context, model, and scale sources, but you must cite the source and identify your own extension. The extension may involve a different population, location, additional variable, or relationship being tested.
Do not copy the title, questionnaire, hypotheses, and interpretation word for word. If you are preparing a thesis, create a source list while you read so that you do not confuse referenced material with your own writing.
What should I do after choosing a topic?
First, lock down four parts: the research question, model, sampling criteria, and data-collection plan. Then create the scale table, write a pilot questionnaire, check the variables in SPSS or SmartPLS, and save each data version throughout the cleaning process.
How to write this in your thesis: Open your proposal file now, choose one topic from the relevant group, write three sentences about “whom I will survey, which variables I will measure, and what I will explain,” then move to the undergraduate thesis topic guide to compare possible directions. When you need to build the model, scales, and questionnaire for the selected topic, use M3 in DoThesis.