Analysing Adoption Patterns of E-Learning Platforms Among Female Secondary School Teachers in South Africa: A Methodological Framework
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
E-learning platforms have emerged as a significant tool in educational settings, particularly for female secondary school teachers who often face challenges in traditional classroom environments. A mixed-methods approach combining survey data collection from 200 participants and qualitative interviews with 10 teachers. Data analysis includes content validity and thematic analysis for themes emerging from the data. Female teachers reported an average adoption rate of 58% across all platforms, with a significant proportion (70%) indicating that E-learning has positively impacted their teaching methods. The study highlights the potential benefits of integrating E-learning platforms into secondary school education in South Africa, particularly for female educators who face unique challenges. School administrators should consider implementing structured training programmes to support teachers' effective use of E-learning tools and address any identified barriers to adoption. E-Learning Adoption Female Teachers Secondary Education South Africa Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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