A Framework for Strengthening Teacher Professional Development Systems with ICT
Bibliographic record
Abstract
<b>Purpose of this framework</b><br></br> \nTeacher professional development (TPD) is an essential component in the transformation of teaching and learning to meet the targets of Sustainable Development Goal 4. <br></br> \nThe purpose of the framework presented here is to support countries in strengthening their TPD systems by harnessing the power of information and communication technologies (ICT). It provides a way of thinking about how to effectively incorporate ICT in the design and implementation of professional learning programs for all teachers in ways that address equity concerns and take account of contextual factors.<br></br> \n<b>How was the framework developed?</b><br></br> \nThe framework draws on international research and fieldwork findings from the Global Partnership for Education Knowledge and Innovation Exchange (GPE KIX) multi-site empirical TPD@Scale research project, “Adapting and Scaling Teacher Professional Development Approaches in Ghana, Honduras, and Uzbekistan.” This study sought to identify how ICT can be utilized at scale to improve equity, quality and efficiency in TPD systems. <br></br> \nThe framework was developed by international experts including researchers, practitioners and representatives of national agencies. It builds on the TPD@Scale Coalition for the Global South’s working paper, “TPD@Scale: Designing Teacher Professional Development with ICTs to Support System-Wide Improvement in Teaching” (Wolfenden, 2022)
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".