Teacher emotions in the classroom and their implications for students
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
The present contribution provides a conceptualization of teacher emotions rooted in appraisal theory and draws on several complementary theoretical perspectives to create a conceptual framework for understanding the teacher emotion–student outcome link based on three psychological mechanisms: (1) direct transmission effects between teacher and student emotions, (2) mediated effects via teachers’ instructional and relational teaching behaviors, and (3) recursive effects back from student outcomes on teacher emotions, both directly and indirectly via teachers’ appraisals of student outcomes and their correspondingly adapted teaching behaviors. We then present a tour d’horizon of empirical evidence from this field of research, highlighting valence-congruent links in which positive emotions relate to desirable outcomes and negative emotions to undesirable outcomes, but also valence-incongruent links. Last, we identify two key challenges for teacher emotion impact research and suggest three directions for future research that focus on measurement, research design, and an extended scope considering emotion regulation.
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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) | 0.001 | 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