Does “Psychological Literacy” Feature in Non-Psychology Degrees? A Cross-Discipline Study of Student Perceptions
Bibliographic record
Abstract
Background: Psychological literacy is a set of attributes, which refer broadly to how students apply their subject-specific psychology knowledge to solving problems. However, the extent to which psychological literacy skills are unique to psychology as a discipline is unknown. Objective: We assessed whether students perceive psychological literacy attributes to be prominent in disciplines outside of psychology. Method: We recruited undergraduate students from Psychology, non-Psychology STEM subjects, and Humanities subjects ( N = 296) and asked them to identify the extent to which they perceive psychological literacy attributes to be prominent in their degrees. Results: Psychology students reported significantly higher perceived prominence of psychological literacy attributes in their degree, compared with Humanities and non-Psychology STEM students, in all but two of the psychological literacy attributes. Conclusion: These findings suggest that psychological literacy mostly represents attributes unique to psychology students, but some of these attributes are also developed within other disciplines. The facets of psychological literacy unique to psychology relate to knowledge of behavior, research skills, ethics, and socio-cultural issues. Teaching implications: This suggests that psychology students graduate with some subject specific attributes, which may make them uniquely advantaged in a competitive work context and affirms that psychology degrees do hold unique value.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".