Examining activity-based learning (ABL) practices in public basic schools in the northern region of Ghana
Bibliographic record
Abstract
Background: Ghana has been the testing ground for many teaching and learning initiatives over the past 15–20 years. These initiatives, largely funded by donors, have sought to improve learning by introducing and reinforcing valuable teaching skills, materials and approaches, most of them child-friendly, learner-centred and involving activity-based learning (ABL). However, a problem in Ghana, also true of other countries in sub-Saharan Africa, is that whereas efforts over the past few decades have improved access to basic education in both pupil enrolment rates and teacher numbers, educational quality as measured by standardised test scores in key subject areas remains rather low.Purpose: This article reports on an aspect of a DfID (Ghana) – sponsored research project which examined how the quality of teaching and learning in Ghanaian basic schools could be improved through the utilisation of ABL pedagogy. The current article examines three overarching themes relative to ABL pedagogy, namely how participants conceptualise ABL; ways in which ABL practices reveal themselves in classrooms; and challenges of ABL practices in Ghanaian schools.Sample: Participants (comprising representatives of Colleges of Education, District Directors and frontline Deputy Directors of Education, headteachers and teachers) were drawn using purposive sampling technique from eight schools from within four districts of the northern region of Ghana.Design and Methods: A case study approach was adopted for the study. Data collection took the form of semi-structured interviews, focused group discussions and observation of ABL practices and lessons in selected schools. Data analysis was undertaken using a ‘processual analytical approach’ with the view to catching realities of ABL practices in the Ghanaian educational setting.Results: Our analysis reveals that whereas the literature on ABL emphasises multi-tasking and group work as essential ingredients of ABL pedagogy, the respondents conceptualised this as meaning pupils working on the same activity-related tasks at the same time in groups. Similarly, we found that, ideally, ABL practices reveal themselves through classroom practices such as display of pupils’ work in classrooms, organisation of the seating arrangements of pupils in groups, use of teaching and learning materials, formative assessment and activity-oriented lessons among others. However, in almost all the schools and classrooms we visited, these essential ingredients were missing owing to congestion and lack of furniture and logistics.Conclusions: We conclude against the backdrop of our findings that ABL techniques can be utilised more effectively in Ghanaian schools if its practices are initially promoted in model schools, for lessons to be learned, and then scaled-up as expertise is established in these model schools.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".