Chemistry professors’ descriptions of the impact of research engagement on teaching
Why this work is in the frame
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Bibliographic record
Abstract
AbstractProfessors endorse a symbiotic relationship between research and teaching, but empirical evidence supporting this relationship is inconsistent. Many studies operationalized research and teaching too narrowly to detect the believed relationship. Semi-structured, in-depth interviews were conducted with 27 chemistry professors from a large research-intensive university. Six themes characterized descriptions of how professors’ research engagement affects their teaching: it (1) enhances student interest, (2) promotes subject-matter currency, (3) generates research examples, (4) models ways of thinking in the discipline, (5) provides contextualization guidance for instruction and (6) helps them explain difficult concepts. Although most responses were conventional in the kinds of impact they reported, responses reflected professors regarding themselves as having taken some steps toward integrating their knowledge about the subject matter, how it is advanced in their field and how this can enhance their formal classroom teaching. Implications for undergraduate instruction were interpreted within Shulman's framework of teacher knowledge and beliefs.Keywords: higher educationpedagogical content knowledgeteaching and learningteaching-research nexus AcknowledgementsFunding was provided by Canada's Social Sciences and Humanities Research Council. Thank you to Evgeniya Makarova and Allison Cooper for insightful assistance with editing and methodological suggestions.
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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 | 0.022 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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