A classification system for teachers’ motivational behaviors recommended in self-determination theory interventions.
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
Teachers’ behavior is a key factor that influences students’ motivation. Many theoretical models have tried to explain this influence, with one of the most thoroughly researched being self-determination theory (SDT). We used a Delphi method to create a classification of teacher behaviors consistent with SDT. This is useful because SDT-based interventions have been widely used to improve educational outcomes. However, these interventions contain many components. Reliably classifying and labeling those components is essential for implementation, reproducibility, and evidence synthesis. We used an international expert panel (N = 34) to develop this classification system. We started by identifying behaviors from existing literature, then refined labels, descriptions, and examples using the Delphi panel’s input. Next, the panel of experts iteratively rated the relevance of each behavior to SDT, the psychological need that each behavior influenced, and its likely effect on motivation. To create a mutually exclusive and collectively exhaustive list of behaviors, experts nominated overlapping behaviors that were redundant, and suggested new ones missing from the classification. After three rounds, the expert panel agreed upon 57 teacher motivational behaviors (TMBs) that were consistent with SDT. For most behaviors (77%), experts reached consensus on both the most relevant psychological need and influence on motivation. Our classification system provides a comprehensive list of TMBs and consistent terminology in how those behaviors are labeled. Researchers and practitioners designing interventions could use these behaviors to design interventions, to reproduce interventions, to assess whether these behaviors moderate intervention effects, and could focus new research on areas where experts disagreed. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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