The Impact of UNESCO MGIEP Digital Teacher Training on Nigerian Educators' Digital Pedagogy Competence and Confidence
Bibliographic record
Abstract
This study explores Nigerian educators’ perceptions of digital pedagogy competence and the impact of a UNESCO MGIEP digital teacher training course. The study employs a validated survey and paired sample t-tests to assess the efficacy of a 5-week intervention delivered through synchronous and asynchronous modes. The findings reveal statistically significant improvements in educators' digital pedagogy competence and confidence across multiple domains following Digital Teacher Training, with substantial increases in mean scores from pre-test to post-test (p < .001) and moderate to large effect sizes (Cohen's d ranging from 0.430 to 1.062). These results demonstrate the intervention's efficacy in enhancing educators' proficiency in leveraging digital technologies for instruction, assessment, and student engagement, although a marginal decline was observed in facilitating student self-monitoring through digital means.
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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 | 0.001 |
| 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 | 0.002 | 0.003 |
| Open science | 0.001 | 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 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".