THE RESEARCH PROCESS

A Step-by-Step Lesson

Lesson goal: By the end of this lesson learners will understand the full sequence of steps in doing academic research, be able to plan a research project, choose appropriate methods, carry out analysis, and write up & present findings clearly and ethically.

1. Lesson overview (what this lesson covers)

A clear roadmap of academic research from idea → dissemination:

1. Choosing & refining a topic
2. Framing the problem & research questions/hypotheses
3. Reviewing the literature (context & gap identification)
4. Defining objectives and scope
5. Designing the study (approach, methods, sampling)
6. Preparing instruments & ethics approval
7. Collecting data
8. Analysing data
9. Interpreting results and drawing conclusions
10. Writing the report/thesis/article
11. Dissemination and follow-up (presentations, publication, policy briefs)

2. Learning objectives

After this lesson learners should be able to:

• Explain each major step of the research process and why it matters.
• Convert a broad interest into a precise research question.
• Choose an appropriate research design (qualitative, quantitative, mixed) for a question.
• Plan data collection and sampling in a way that supports valid conclusions.
• Describe common analysis techniques and match them to data types.
• Identify ethical issues and how to address them.
• Produce a clear, logically structured research report.

3. Step-by-step guide (with practical tips)

Step 1 — From interest to topic

• Start broad: note areas that interest you.
• Narrow down: use “who, what, where, when, why, how” to focus.
• Feasibility check: is data available? Do you have time/resources/expertise?
• Example: “Educational outcomes” → “Effect of teacher feedback on junior secondary students’ maths scores in Calabar.”

Tip: Write a short (1–2 sentence) problem statement — it forces clarity.

Step 2 — Problem statement, objectives, research question(s), hypotheses

• Problem statement: short description of the issue and why it’s important.
• General & specific objectives: what you aim to achieve.
• Research questions: precise, answerable, and aligned to objectives. Use PICO/PEO for health/education; use IV/DV framing for quantitative work.
• Hypotheses: testable predictions (only where applicable).

Good question: “How does X affect Y among Z?”
Bad question: “Why are students bad at maths?” (too vague)

Step 3 — Literature review

• Purpose: situate your study, show gaps, justify methods.
• Process: search databases, read critically, synthesize (not list).
• Structure: theoretical background → empirical findings → gap → how your study fills it.
• Output: annotated bibliography and a conceptual map/framework.

Tip: Use recent and seminal works; track citations and themes; summarize findings in a matrix.

Step 4 — Conceptual / theoretical framework

• Choose theory(ies) that explain relationships between key variables.
• Draw a diagram showing how concepts link (variables, moderators, mediators).
• Use this to guide measurement & analysis choices.

Step 5 — Research design & methodology

• Choose approach:
  • Quantitative — hypothesis testing, measurement, statistical inference.
  • Qualitative — meaning, experience, depth (interviews, focus groups, observations).
  • Mixed methods — combine strengths; sequence carefully (e.g., qual → quant or quant → qual).
• Design types: experimental, quasi-experimental, cross-sectional, longitudinal, case study, ethnography, action research, etc.
• Align research questions to design (don’t pick fancy design that you cannot execute).

Step 6 — Sampling & measurement

• Population vs sample: define clearly.
• Sampling methods: probability (simple random, stratified, cluster) vs non-probability (convenience, purposive). Choose based on goals and resources.
• Sample size: guided by power analysis for quantitative studies; for qualitative, use saturation logic.
• Measurement: choose validated instruments where possible; operationalize variables (define how you measure X). Pilot instruments.

Tip: Keep measurement reliable (consistent) and valid (measuring what you intend).

Step 7 — Ethics & approvals

• Common issues: informed consent, confidentiality, vulnerability, data storage, conflicts of interest.
• Action: prepare consent forms, anonymize data, seek Institutional Review Board (IRB)/Ethics Committee approval before data collection.
• When in doubt: err on the side of protecting participants.

Step 8 — Data collection

• Plan: timetable, roles, materials, training for data collectors.
• Modes: surveys, experiments, interviews, observation, secondary data.
• Quality control: pilot testing, supervision, data validation checks.
• Record keeping: keep logs, backups, metadata.

Tip: For surveys, track response rates and reasons for non-response.

Step 9 — Data preparation and analysis

• Cleaning: check for missing values, outliers, entry errors. Document all cleaning steps.
• Analysis choices:
  • Quantitative: descriptive stats, t-tests/ANOVA, regression, logistic regression, multilevel modelling, factor analysis, etc.
  • Qualitative: coding (open, axial, selective), thematic analysis, framework analysis, narrative analysis.
  • Mixed methods: integrate results at interpretation stage — triangulation, complementarity, explanation.
• Interpretation: link back to research questions and literature. Report effect sizes and confidence intervals, not just p-values.

Tip: Pre-register hypotheses / analysis plan if possible to reduce bias.

Step 10 — Writing up results & discussion

• Typical structure for an academic report/thesis:
  1. Title page, abstract
  2. Introduction (problem statement, objectives, RQs/hypotheses)
  3. Literature review & conceptual framework
  4. Methodology (design, sampling, instruments, procedures)
  5. Results (clear tables, figures; raw findings only)
  6. Discussion (interpretation, link to literature, limitations)
  7. Conclusion & recommendations
  8. References & appendices (instruments, consent forms, extended tables)
• Abstract: concise — objective, methods, main findings, conclusion.
• Style: be precise, report limitations honestly, and avoid overstating claims.

Step 11 — Referencing & academic integrity

• Use consistent citation style (APA, Chicago, Harvard, etc.).
• Keep a reference manager (Mendeley, Zotero, EndNote) to avoid errors.
• Avoid plagiarism — paraphrase properly and cite sources.

Step 12 — Dissemination & impact

• Options: thesis defense, journal article, conference paper, policy brief, workshop, community presentation.
• Tailor your message to the audience (academic vs practitioner vs community).
• Consider data sharing (anonymized) if ethical and beneficial.

4. Common pitfalls & how to avoid them

• Vague questions: refine to be measurable/answerable.
• Mismatch of methods and questions: choose method that can answer your question.
• Underpowered studies: calculate sample size in advance.
• Poor documentation: keep research diary & versioned files.
• Ignoring ethics: get approvals early.
• Overclaiming: stick to what your data supports.

5. Practical classroom activities (apply the steps)

1. Topic narrowing exercise (10–15 min): give broad topics; students produce 2–3 refined researchable topics with problem statements.
2. Research question workshop (20 min): convert objectives into measurable RQs and, where relevant, hypotheses.
3. Method match game (20 min): provide RQs; students choose design, sampling and instruments and justify choice.
4. Mini literature synthesis (homework): find 5 sources, write a 300–400 word synthesis identifying the gap.

6. Assessment ideas

• Formative: class participation, short quizzes on definitions (RQ vs hypothesis vs objective).
• Summative: a mini research proposal (2,500–4,000 words) including problem statement, literature review, methodology, ethical considerations, and a brief plan for analysis.

7. Quick checklist for a research project (use before you start data collection)

• Clear problem statement & RQs/hypotheses
• Literature mapped and gap identified
• Theoretical/conceptual framework drawn
• Chosen design aligns with questions
• Sampling plan and sample size justified
• Instruments piloted & validated where possible
• Ethics approval obtained and consent forms ready
• Data collection plan with backups & quality control
• Analysis plan (basic tests, software) written down
• Plan for writing, referencing, and dissemination

8. Short example (applied)

Topic: Impact of teacher feedback on junior secondary mathematics performance in Calabar.

• Problem: Low pass rates; unclear whether feedback style affects scores.
• RQ: Does formative feedback by teachers improve mathematics scores among JSS2 students in Calabar?
• Design: Quasi-experimental (two comparable schools — treatment vs control)
• Sample: Stratified sample of classrooms; power calculation indicates n ≈ 120 students per group.
• Instruments: Standardized math test; teacher feedback checklist; classroom observation.
• Analysis: Pre/post mean comparisons (paired t), ANCOVA controlling baseline scores, thematic coding of observation notes.
• Ethics: Parental consent, anonymized reporting, school permission.

9. Useful resources & tools

• Reference managers: Zotero, Mendeley, EndNote.
• Survey tools: KoboToolbox, Google Forms, Qualtrics (if available).
• Analysis: SPSS, R, Stata, NVivo/Atlas.ti for qualitative.
• Guides: Your university’s thesis handbook; recent well-written theses in your field.

10. Final tips

• Start small and scalable — you can always extend a pilot into a larger study.
• Keep clear records — reproducibility starts with good documentation.
• Be ready to revise: research questions and methods often improve as you read the literature and pilot.
• Talk about your work often — peer feedback early saves time later.