Teacher Change in Bangladesh: A Study of Teachers Adapting and Implementing Active Learning into their Practice
Bibliographic record
Abstract
The purpose of this study is to investigate the teacher change process and extend our understanding of how variability in the ways that primary school teachers in Bangladesh implement innovative pedagogical practices, such as active learning, reflects variations in their understanding, attitude, experience, and skill in the use of those pedagogical approaches. Multiple forms of data gathering were employed based on the concerns-based adoption model (CBAM) including an open-ended statement of concern, interviews, and class observations from a purposive sample of ten teachers working in ten different schools. Additional interviews were also conducted with staff responsible for the teachers' professional development. Five main findings emerged from the research. First, there was a split between novice teachers who were committed to following the prescriptive lesson plans and more experienced teachers who adapted \ntheir lessons to accommodate differences in student readiness and performance. Second, the majority of teachers appeared to be satisfied with their use active learning methods and the mandated lessons with little projected variation in how they will implement the innovation in the future. Third, the class observation findings indicate that the majority of teachers were rated as ideal users of active learning methods in the classroom. Fourth, findings indicate that professional development and a commitment to building networks among teachers and support staff helped facilitate teachers' confidence and competency. Fifth, among the most influential factors shaping teachers' use of active learning methods were the availability of supplementary learning and teaching resources. Implications for professional development and support for teachers, the applicability of CBAM-based research in low-income country contexts like Bangladesh, as well as future areas of comparative, international, and development education research are discussed in light of those findings.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".