Crafting Research Questions
A research question is the central, organising inquiry of your study. It is not a topic, a hypothesis, or a statement of intent — it is a precise, answerable question that determines the scope, methodology, and direction of everything that follows. According to Creswell & Creswell (2018), a well-formulated research question is the single most important element of a research design.
A research question is a clear, focused, concise, complex, and arguable question around which you centre your research. It must be specific enough to be feasibly answered within the scope of your study, yet broad enough to be academically significant.
Why Research Questions Matter
Research questions serve three foundational purposes in academic research:
1. Direction: They establish what the study will investigate, preventing scope creep and ensuring methodological coherence. Studies without clear research questions tend to produce diffuse, inconclusive findings (Punch, 2014).
2. Delimitation: They define what the study will not investigate, which is equally important for maintaining rigour and manageability.
3. Evaluation: They provide the benchmark against which the study's conclusions are measured. A study succeeds when it provides a defensible answer to its stated research question.
Types of Research Questions
| Type | Purpose | Example | Typical Method |
|---|---|---|---|
| Descriptive | Describes characteristics of a phenomenon | What study habits do first-year university students report using? | Survey, observation |
| Comparative | Compares two or more groups or conditions | How do study outcomes differ between students in online vs. face-to-face courses? | Quasi-experiment, survey |
| Relational / Correlational | Examines relationships between variables | What is the relationship between sleep duration and academic performance? | Correlation, regression |
| Causal / Explanatory | Tests cause-and-effect relationships | To what extent does peer tutoring improve test scores in secondary school students? | Experiment, RCT |
| Exploratory | Explores little-known phenomena | What factors influence students' decision to withdraw from postgraduate programmes? | Interviews, grounded theory |
| Evaluative | Assesses the effectiveness of an intervention | How effective is the university's writing support programme in improving essay quality? | Mixed methods, pre-post |
Too broad: "What affects student success?" — this could generate thousands of variables and no clear method.
Too narrow: "Do male students in Room 204 score higher than female students on Tuesday?" — not generalisable or academically significant.
Binary/closed: "Does social media cause depression?" — reduces a complex phenomenon to a yes/no and forecloses nuanced analysis.
Not researchable: "Should universities be free?" — this is a normative policy question, not an empirical research question.
Moving from Topic to Question
Many researchers struggle to move from a broad area of interest to a specific research question. The process involves progressive narrowing: start with your field, identify a gap or problem in the literature, and refine until you have a focused, answerable question.
Topic area: Mental health and university students
Narrowed focus: Anxiety among first-year students during academic transition
Research question: To what extent does perceived social support moderate the relationship between academic transition stress and generalised anxiety symptoms among first-year undergraduate students?
This question is specific (first-year undergraduates), involves defined variables (stress, social support, anxiety), implies a clear methodology (moderation analysis), and is answerable within a bounded study.
The FICSARRA Criteria
The FICSARRA framework, adapted from Ranjit Kumar's (2019) research methodology work, provides a systematic checklist for evaluating the quality of a research question. Each letter represents an essential criterion your question must satisfy.
A research question that fails even one FICSARRA criterion will likely undermine the entire study. Most poorly received dissertations can be traced back to a research question that was not feasible (too ambitious), not arguable (trivially answerable), or not significant (a question the field has already answered).
Conceptual & Theoretical Frameworks
A framework is the structural scaffold of your research — it makes explicit the assumptions, concepts, and relationships that underpin your investigation. Without a framework, research lacks coherence; findings cannot be interpreted systematically, and the study's contribution to knowledge remains unclear.
Theoretical vs. Conceptual: A Critical Distinction
| Dimension | Theoretical Framework | Conceptual Framework |
|---|---|---|
| Source | Existing, established theory (e.g., Bandura's Social Learning Theory) | Researcher-constructed from multiple concepts and literatures |
| Function | Tests, extends, or challenges a specific theory | Maps the concepts, variables, and relationships specific to this study |
| Appropriate when | A well-developed theory directly applies to your research problem | No single theory fits; you are synthesising multiple perspectives |
| Example | Using Vygotsky's Zone of Proximal Development to frame a study on peer tutoring | Developing a custom model linking self-efficacy, motivation, and engagement |
| Flexibility | Lower — you are bound by the theory's assumptions | Higher — you construct the relationships based on your literature review |
Visual Framework: IV → Moderator → DV
A conceptual framework is best communicated visually. The diagram below shows a standard moderation model — one of the most common framework structures in social science research.
Widely Used Theoretical Frameworks
Proposes that behaviour is influenced by personal factors, environmental conditions, and behaviour itself — the triadic reciprocal causation model. Central constructs include self-efficacy (belief in one's ability to succeed), observational learning, and outcome expectations. Widely applied in education, health behaviour, and organisational research.
Best used for: Studies examining motivation, self-regulated learning, behaviour change, or skill development.
A macro-theory of human motivation distinguishing between intrinsic motivation (driven by inherent interest), extrinsic motivation (driven by external rewards), and amotivation. Identifies three basic psychological needs — autonomy, competence, and relatedness — whose satisfaction predicts wellbeing and optimal functioning.
Best used for: Studies on academic motivation, workplace engagement, health behaviour, or wellbeing interventions.
Conceptualises human development as embedded within nested environmental systems: microsystem (immediate environment), mesosystem (interactions between microsystems), exosystem (indirect environments), macrosystem (cultural context), and chronosystem (time dimension). Essential for contextualising individual behaviour within broader social structures.
Best used for: Studies on child development, educational outcomes, community health, or policy impact.
Predicts intentional behaviour based on three components: attitude toward the behaviour, subjective norms (perceived social pressure), and perceived behavioural control (self-efficacy analog). Intention is the immediate antecedent of behaviour. Extensively validated across health, environmental, and consumer behaviour research.
Best used for: Studies predicting health behaviours, pro-environmental actions, or adoption of new technologies.
Holds that knowledge is actively constructed by the learner through experience and social interaction, rather than passively received. Piaget emphasised cognitive stages and schema development; Vygotsky stressed social mediation, the Zone of Proximal Development (ZPD), and the role of language. Foundational in education research and pedagogy.
Best used for: Studies on learning, teaching practices, curriculum design, or educational technology.
Choose a framework that genuinely fits your research problem — not the most prestigious or commonly cited theory. A well-applied minor theory always outperforms a poorly applied grand theory. Ask: Does this framework's key assumptions align with my research question? Do its constructs map onto my variables?
Hypothesis Formulation
A hypothesis is a specific, testable prediction about the relationship between variables, derived from theory and prior research. Not all research requires hypotheses — qualitative and exploratory studies typically do not — but quantitative and mixed-methods studies testing relationships or differences almost always do.
A hypothesis is a declarative statement that predicts a specific relationship, difference, or effect between two or more variables, formulated in advance of data collection and tested against empirical evidence.
Types of Hypotheses
The default assumption that no significant effect exists. Statistical tests attempt to reject H₀.
The hypothesis the researcher expects to support, based on theory and literature.
Predicts not only that a relationship exists, but its direction (positive/negative, greater/lesser).
Used when literature is insufficient to predict direction, or when exploring bidirectional effects.
The IF–THEN–BECAUSE Structure
A reliable method for constructing hypotheses is the IF–THEN–BECAUSE template, which ensures your hypothesis is grounded in theory:
IF [the independent variable is manipulated/observed in this way], THEN [the dependent variable will respond in this predicted way], BECAUSE [theory or prior evidence supports this prediction].
Example: IF undergraduate students are exposed to mindfulness-based stress reduction training, THEN their self-reported anxiety scores will decrease significantly over 8 weeks, BECAUSE mindfulness interventions have been consistently shown to reduce cortisol and improve emotional regulation (Kabat-Zinn, 1990; Hofmann et al., 2010).
Criteria for a Good Hypothesis
| Criterion | Satisfied ✓ | Not Satisfied ✗ |
|---|---|---|
| Testable | ✓ | "Social media causes unhappiness" can be operationalised and measured |
| Falsifiable | ✓ | Data could potentially disprove it (Popper's criterion) |
| Grounded in theory | ✓ | Derived from existing literature, not personal opinion |
| Specific variables stated | ✓ | Both IV and DV clearly named |
| Declarative sentence | ✓ | Not a question or a vague statement |
| One relationship per hypothesis | ✓ | Multiple relationships should generate separate hypotheses |
Variable Identification
Variables are the measurable constructs at the heart of quantitative and mixed-methods research. Identifying and defining them precisely is not a bureaucratic exercise — it determines what data you collect, how you analyse it, and what claims you can legitimately make.
Operationalisation: From Concept to Measurement
Every variable must be operationalised — translated from an abstract concept into a specific, measurable indicator. This is one of the most common weaknesses in student research proposals.
| Abstract Concept | Operationalised Variable | Measurement Instrument |
|---|---|---|
| Academic performance | GPA at end of semester | Official academic transcript |
| Anxiety | Generalised anxiety symptoms | GAD-7 (Spitzer et al., 2006) |
| Social support | Perceived availability of emotional support | MSPSS (Zimet et al., 1988) |
| Motivation | Intrinsic academic motivation | AMS-C 28 (Vallerand et al., 1992) |
| Socioeconomic status | Annual household income bracket | Self-report ordinal scale |
| Teaching quality | Student evaluation of teaching | SET questionnaire (Likert 1–5) |
Never use a measurement instrument without checking its validity (does it measure what it claims?) and reliability (does it produce consistent results?). Always cite the original validation study when using a published scale. Using an unvalidated or self-invented scale without pilot testing is a critical methodological weakness.
Research Question Checker
Enter your draft research question below and the tool will evaluate it against seven key quality criteria. Use the feedback to refine your question before submission.
Module Knowledge Quiz
Test your understanding of research questions, frameworks, hypotheses, and variables. Ten questions covering all module topics.