Mathematics Teachers’ Use of WhatsApp Groups as a Platform for Continuous Professional Development in Tanzania
Bibliographic record
Abstract
Updating mathematics teachers’ pedagogical skills and content knowledge is inevitable as the trend of students’ performance in Tanzania is alarming. Currently, social media have been one of the strategies for elevating mathematics teachers’ professional competencies through online learning communities. The study aimed at examining how mathematics teachers use Informal WhatsApp Groups (IWGs) as one of the social media for Continued Professional Development (CPD). Key study questions are what are the perceptions of mathematics teachers on the benefits of IWGs in CPD? How do mathematics teachers use IWGs for CPD-related activities? What are the challenges they encounter? And what Mathematics teachers recommend for better use of IWGs for CPD? Two IWGs were involved with a total of 54 mathematics teachers who are currently teaching in secondary schools. The open-ended questionnaire was shared in the IWGs, and members accepted to fill it. Ten members including those who have been in the IWGs for a longer period, those who frequently posted or asked questions, and group leaders were invited for interviews. The findings show that the IWGs have contributed to teachers developing their pedagogical skills and content knowledge through sharing experience, and materials and demonstrating teaching practices in video clips. The challenges include the problem of internet accessibility, inactiveness of members, and lack of effective criteria for evaluating the validity and reliability of information shared. The recommendation is for the authorities to set supportive policies and practices that will create enabling environments for mathematics teachers on CPD.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".