How do medical students form impressions of the effectiveness of classroom teachers?
Bibliographic record
Abstract
CONTEXT: Teaching effectiveness ratings (TERs) are used to provide feedback to teachers on their performance and to guide decisions on academic promotion. However, exactly how raters make decisions on teaching effectiveness is unclear. OBJECTIVES: The objectives of this study were to identify variables that medical students appraise when rating the effectiveness of a classroom teacher, and to explore whether the relationships among these variables and TERs are modified by the physical attractiveness of the teacher. METHODS: We asked 48 Year 1 medical students to listen to 2-minute audio clips of 10 teachers and to describe their impressions of these teachers and rate their teaching effectiveness. During each clip, we displayed either an attractive or an unattractive photograph of an unrelated third party. We used qualitative analysis followed by factor analysis to identify the principal components of teaching effectiveness, and multiple linear regression to study the associations among these components, type of photograph displayed, and TER. RESULTS: We identified two principal components of teaching effectiveness: charisma and intellect. There was no association between rating of intellect and TER. Rating of charisma and the display of an attractive photograph were both positively associated with TER and a significant interaction between these two variables was apparent (p < 0.001). The regression coefficient for the association between charisma and TER was 0.26 (95% confidence interval [CI] 0.10-0.41) when an attractive picture was displayed and 0.83 (95% CI 0.66-1.00) when an unattractive picture was displayed (p < 0.001). CONCLUSIONS: When medical students rate classroom teachers, they consider the degree to which the teacher is charismatic, although the relationship between this attribute and TER appears to be modified by the perceived physical attractiveness of the teacher. Further studies are needed to identify other variables that may influence subjective ratings of teaching effectiveness and to evaluate alternative strategies for rating teaching effectiveness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.005 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".