The Ideal Psychology Teacher: Qualitative Analysis of Views from Brunei GCE A-Level Students and Trainee Psychology Teachers
Bibliographic record
Abstract
We qualitatively explored the notion of the ideal teacher from the context of pre-university Brunei General Certificate of Education Advanced Level (GCE A-Level) psychology students and trainee psychology teachers. Both previous research and our own analyses on this concept revealed that the so-called ideal teacher was neither a perfect nor a super teacher but rather an effective instructor who was firm, fair, and a good communicator. Psychology students of various ability levels (high achievers, average students, and low scorers) gave slightly different descriptive characteristics for the ideal teacher. More-able students preferred a cognitive-oriented teacher while less-able students emphasized the affective-oriented instructor. Students in the middle range of the ability scale endorsed both cognitive and affective traits in the ideal teacher traits. Trainee psychology teachers closely resembled the higher achieving GCE A-Level psychology students in their descriptions of the ideal teacher. The findings have implications for teaching and assessing psychology students that we discuss. Further mixed-methods research was recommended to generate more insightful outcomes.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".