The Impact of Switching Intention of Teachers’ Online Teaching in the COVID-19 Era: The Perspective of Push-Pull-Mooring
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
In response to the COVID-19 pandemic, many educational institutions switched to online learning to maintain learning activities. With the global pandemic, the educational environment was forced to shift from traditional face-to-face teaching or blended learning to a fully online learning model. In February 2020, China took the lead in announcing the implementation of online learning, encouraging most teachers to use it. Exploring the potential of online learning to replace traditional face-to-face teaching is a topic deserving consideration. This study explored the factors that influenced teachers’ intention to switch to online learning during the pandemic, using a push-pull-mooring model. The study analyzed 283 valid responses gathered through an online questionnaire and found that push effects, pull effects, and habits significantly impact teachers’ intention to switch from offline to online teaching. The findings provide additional insights into the future of higher education after the pandemic.
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 | 0.012 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it