Lesson observation tool for project-based learning: a useful tool for learner-centered pedagogy enhancement
Bibliographic record
Abstract
Introduction The CBC has been implemented in pre-primary through secondary schools in Rwanda. However, a gap was found in assessing the implementation of the CBC since there is no documentation to fulfill the need. Methodology This study is a product of a validated and reliable Lesson Observation Tool for Project-based Learning (LOTPBL), designed to fill the gap in monitoring and assessing the implementation of a competence-based curriculum within a project-based learning (PjBL) framework in Rwanda. The tool was piloted to check for its construct. The tool was checked for reliability. The calculated Kappa coefficient was 0.8, indicating that the tool is suitable for use. The tool was used while observing one teacher during 60 lessons (30 lessons before and 30 after the intervention). Results The tool was found worthy to be used during lesson observations about project-based learning instructions. The analysis of the collected sample data revealed an improvement in the teacher employing key observations of PjBL during instructions (p-value = 0.0096; p < 0.05). The computed t-statistic of −3.38 with a two-tailed p-value of 0.0096 (p < 0.05) confirms that this improvement is statistically significant. Discussion These results indicate a notable enhancement in the implementation of strategies such as project initiation, student-centered learning, collaboration, and authentic assessment during instructions. The LOTPBL holds significant potential for supporting the global shift toward competency-based and active learning methodologies through project-based learning.
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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 | 0.013 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".