Faculty enjoyment, anxiety, and boredom for teaching and research: instrument development and testing predictors of success
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
This study examined the role of emotions in predicting university faculty teaching and research performance while addressing the methodological limitations of past research. Recruited using social media, 312 early-career faculty completed an online survey containing six newly adapted multi-item emotion scales assessing enjoyment, anxiety, and boredom related to both teaching and research. Analyses supported the reliability as well as convergent and divergent validity of the scales. Results of structural equation modeling revealed that enjoyment positively predicted perceived success whereas anxiety and boredom negatively predicted success in both teaching and research, even after accounting for social-environmental predictors. The emotions also significantly related to faculty research publication and citation counts. In terms of implications for faculty development, the findings suggest that fostering value and control may be a mechanism for improving faculty emotions and performance in teaching and research. The discussion includes future theoretical and methodological contributions.
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.
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) | 0.000 | 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 it