Holistic Education: A Combination of Pedagogy Frameworks for Bangladesh
Bibliographic record
Abstract
Crafting an ideal, holistic curriculum (curriculum for all) is indeed a crucial piece of the quality-education puzzle, as we know that one size does not fit all. Curricular reform in Bangladesh is essential to ensure sensitivity to learners’ cultural and religious backgrounds and needs, place value on teachers’ skills and knowledge, and enable learners to successfully develop and interact within today’s complex and globalized world. The central ideas of holistic education are balance, inclusion and connectedness. This paper includes a description of sensational pedagogy approaches and the pedagogical framework of holistic education (transmission, transaction and transformation), using examples drawn from my own experience as a student in a non-formal setting. Finally, I bring out an example of contemplative practice of co-operative learning in math, art, music and visualization as a vehicle of holistic education. This paper offers a critical analysis for educators, curriculum designers, administrators, teachers and policy-makers interested in developing a holistic curriculum for the transformation of the Bangladeshi education system.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".