Online Teaching During COVID-19: An Analysis of Changing Self-Efficacy Beliefs
Bibliographic record
Abstract
This quantitative study investigated teachers’ self-efficacy for teaching online compared to teaching in-person during the COVID-19 pandemic. Teacher self-efficacy is a significant predictor of both teacher practice and student outcomes. During the pandemic, teachers were forced to suddenly shift their teaching online and as a result, many new challenges were faced. Teachers from three teaching contexts (public, private, and virtual public schools) in Ontario, Canada completed the Ohio State Teacher Efficacy Scale (OSTES) and questionnaires measuring online teaching experience and training in May–June 2020 (phase 1) and again one year later, in May–June 2021 (phase 2). Results indicated that while the perceived self-efficacy of teachers improved over the course of the study, specifically in classroom management and student engagement, their perceived self-efficacy did not reach the levels reported for self-efficacy for in-person teaching, highlighting the persisting limitations educators experience in online learning environments. Additionally, efficacy for instructional strategies had not significantly increased by phase 2, indicating a particular need of targeted instruction for future teacher education programs. These results offer insights into the kind of experience and tools teacher education programs can extend to enhance teacher preparedness, and the conditions that best encourage improvements in self-efficacy for in-service teachers.
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".