Assessing blended and online-only delivery formats for teacher professional development in Kenya
Bibliographic record
Abstract
The present study compared the learning and experiences of Kenyan teachers randomly assigned to either an online or a blended 12-week intensive teacher professional development program (TPD). The TPD addressed the fundamentals of early literacy development as well as how to use early literacy software to support students learning. TPD outcomes were assessed through surveys, course performance and discussion elements. Teachers demonstrated pre- to post-test gains in domain knowledge, lesson plan construction and comfort teaching early literacy skills. Few differences were observed between the online versus blended formats. However, teachers endorsed a blended instructional format over online-only or in-person formats. Challenges regarding resources and infrastructure were identified as barriers to technology integration within the classroom. Some cultural challenges were identified as potential barriers for young learners using software developed in Western countries. Overall, both online and blended formats appear to be effective TPD delivery systems for Kenyan teachers, however, findings highlighted challenges that need to be addressed to optimize learning when using technology. Future research recommendations include broadening the teacher sample to assess potential differences due to regionalism, associated differences in access to resources, and further examination of teaching experience on learning in the two types of online formats.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".