Pre-Service Perspectives on E-Teaching: Assessing E-Teaching Using the EPEC Hierarchy of Conditions for E-Learning/Teaching Competence
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 article examines pre-service teacher perspectives of teaching with an online synchronous (live-time) platform as a part of their training. Fifty-three students who participated in a blended learning (including both face-to-face and online lectures) course were assessed in a teaching simulation through an online presentation, and participated in questionnaires and interviews about their experiences as e-learners using the platform. The EPEC hierarchy of conditions (Ease of use, Psychologically safe environment, e-learning/e-teaching Efficacy, and e-learning Competence) for e-learning competency, developed based on an analysis of pre-service teachers’ experience as e-learners in this same study, was used as a framework to assess teacher perspectives as e-teachers using this technology. Qualitative interview data were collected about students’ experiences using the platform, and analyzed via thematic content analysis. The findings showed that students generally favoured the online e-teaching synchronous platform over in-person presentations, and the quality of online presentations was considered at least as good as in person.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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