Rethinking the potential role of African Indigenous knowledge systems in transforming STEM education
Bibliographic record
Abstract
This study explores the potential role of African Indigenous Knowledge Systems (AIKS) in transforming STEM education in Ghana. It advocates for the holistic integration of AIKS into the Ghanaian primary school STEM curriculum to support student learning and engagement. Using an Indigenous research methodology, data were collected from twenty (20) teachers in Ghana through sharing circles and follow-up conversational inquiry. The findings reveal the enduring impact of coloniality on curriculum content and pedagogical approaches which continue to shape the teaching and learning of STEM in Ghanaian schools. The study also shows that Ghana’s current primary school STEM curriculum largely privileges Euro-Western knowledge systems, leaving limited space for Indigenous Ghanaian scientific and mathematical knowledges. Teachers in this study expressed strong, positive beliefs about the value of integrating AIKS into STEM education. These findings highlight the pedagogical significance of integrating Indigenous knowledges into STEM lessons to help students better connect with the curriculum.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".