Class Experiences with Inquiry Learning Spaces in Go-Lab in African Secondary Schools
Bibliographic record
Abstract
Inquiry Based Learning (IBL) is a form of active learning, often used in STEM education to promote conceptual learning and to acquire scientific investigation skills. This paper reports on a study in which teachers in Kenya, Nigeria and the Republic of Benin implemented IBL embedded in online and offline Inquiry Learning Spaces (ILS) in their classes using the Go-Lab platform (https://www.golabs.eu). After a brief description of the IBL methodology, of lab work and in particular virtual labs for STEM education, of the process of preparing teachers to use IBL in class, and of the context of this study, we highlight the methodology used, and finally report our results. These show that the introduction and class enactment of a digital inquiry based learning platform such as Go-Lab in Africa (i) is possible, although challenging, (ii) does lead to student learning, (iii) for this to take place teacher training is necessary, (iv) the digital infrastructure is present in the schools though minimal and fragile, and (v) a local partner needs to provide assistance when required.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".