Past exam of the experimental design and methods course of the year 2 of the psychology (experimental) course of the University of Oxford / 2022 / 4

Qualitative research methods investigate meanings, experiences and processes in context. For example, interviews about why lecturers find scheduling difficult could reveal unanticipated constraints that a fixed-response questionnaire omits. Interviews, focus groups, observations and documents provide material; a clearly stated approach such as thematic analysis or qualitative content analysis organizes its interpretation. These methods can develop an explanation or refine a construct rather than estimate a population prevalence.

Recruit participants whose experiences address the research question, for example by purposive sampling across different teaching roles, and explain the basis for the sample's adequacy. Record and transcribe material where appropriate and agreed. Describe how the analysis moved from material to codes, interpretations and claims; support interpretations with contextualized, confidentiality-preserving extracts. Consider contrary cases, alternative interpretations and the researcher's role through researcher reflexivity. The criteria for quality should fit the analytic approach: agreement between coders is useful in some structured coding studies, but is not a universal validity criterion for every interpretive method. Informed consent and protection against identification are especially important when detailed accounts concern identifiable colleagues.

The normality assumption concerns the model's error distribution, not necessarily the pooled raw observations. In an independent-groups analysis of variance, errors around each group mean are modeled as following a normal distribution; combining groups with genuinely different means can produce a nonnormal pooled distribution even when this assumption holds. In a paired t-test, the relevant distribution is that of within-pair differences. Linear regression conventionally assumes normal errors conditional on the predictors for exact small-sample Student t-tests and F-tests.^[ref]

Inspect suitable within-group or fitted-model regression residuals using a quantile-quantile plot and examine outliers and asymmetry. A formal normality test is not a decisive automatic gatekeeper: with small samples it may miss important departures, while large samples can detect minor departures. Approximate robustness depends on the sample size, balance, tail behavior and intended inference. The central limit theorem concerns sampling distributions and does not make every raw observation normal or repair dependence. Depending on the question, a justified transformation, a better-fitting probability model, robust inference or an appropriate bootstrap may be preferable. The normality assumption, independence and equal variance are distinct assumptions.

Research ethics governs how a worthwhile question is investigated while respecting those involved. The British Psychological Society's framework emphasizes respect for autonomy, privacy and dignity, scientific integrity, social responsibility, and maximizing benefit while minimizing harm. Seek appropriate independent ethical review before recruitment and assess risks in the actual study context.^[ref]

Give understandable information, seek voluntary informed consent, explain the practical limits of withdrawal, and avoid pressure arising from a teacher–student or employer–employee relationship. Limit identifiable information, control access and distinguish confidential storage from genuine anonymity. Any justified withholding or research deception needs proportionate review and appropriate research debriefing; debriefing does not undo every possible harm. Explain relevant procedures and offer questions and support consistent with the study's risks.^[ref]

In the lecturer questionnaire study, make participation independent of employment evaluation and prevent identifiable responses reaching supervisors. Ethical reporting also requires honest analysis, disclosure of limitations and proportionate data sharing: open science does not require exposing confidential participant records.