Emotion and Emotion Regulation Matter: A Case Study on Teachers’ Online Teaching Experience During COVID-19
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 explored higher education instructors' emotional experience and regulation strategies as they shifted to online teaching during COVID-19.The purpose of this study is twofold: (a) to gain insight into teachers' perceptions of emotional experience in reacting to the transition from in-person teaching to online teaching during and (b) to investigate the strategies teacher adopted to regulate emotions when they teach remotely.Data for analysis involved in-depth semi-structured interviews.All interviewees were Canadian university instructors from a wide range of backgrounds.A deductive thematic analysis procedure and text mining technique were applied.Findings for (a): supportive relationships/good cooperation with colleagues promote teachers' positive appraisals; lacking connections with students/colleagues facilitates the feeling of isolation.And for (b): teachers applying reappraisal strategies in response to perceived challenges in online contexts enables them to manage negative emotional experiences.Implications for higher education in online contexts are further discussed.
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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 | 0.001 | 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