A Survey of Teacher-Student Style Mismatches
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
An important aspect of the differences among students hasto do with their learning style. As with learning style, theconcept of teaching style is also important since a stylisticmismatch between teacher and student may determinehow well they get along, with important consequencesfor the learning process. This study is intended to findif there are serious teacher-student style mismatches incollege teaching. Four teachers and one hundred fiftysevencollege students are involved in this study. All ofthem are asked to complete the questionnaire designedby Juan Du (2003) to measure their teaching styles andlearning styles. Besides the questionnaire the presentauthor has designed an interview so as to get qualitativedata concerning the learning styles, the teaching stylesand mismatches between them. Key words: Individual difference; Learning style;Teaching style
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it