A Delphi Study to Strengthen Research-Methods Training in Undergraduate Psychology Programs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Psychology programs often emphasize inferential statistical tests over a solid understanding of data and research design. This imbalance may leave graduates underequipped to effectively interpret research and employ data to answer questions. We conducted a two-round modified Delphi to identify the research-methods skills that the UK psychology community deems essential for undergraduates to learn. Participants included 103 research-methods instructors, academics, students, and nonacademic psychologists. Of 78 items included in the consensus process, 34 reached consensus. We coupled these results with a qualitative analysis of 707 open-ended text responses to develop nine recommendations for organizations that accredit undergraduate psychology programs-such as the British Psychological Society. We recommend that accreditation standards emphasize (1) data skills, (2) research design, (3) descriptive statistics, (4) critical analysis, (5) qualitative methods, and (6) both parameter estimation and significance testing; as well as (7) give precedence to foundational skills, (8) promote transferable skills, and (9) create space in curricula to enable these recommendations. Our data and findings can inform modernized accreditation standards to include clearly defined, assessable, and widely encouraged skills that foster a competent graduate body for the contemporary world.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.149 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.013 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it