The Impact of Gagné, Vygotsky and Skinner Theories in Pedagogical Practices of Mathematics Teachers in Brunei Darussalam
Bibliographic record
Abstract
Pedagogy in a classroom is not just for the sake of teaching but it also embodies the learning process where appropriately correct conceptual knowledge is being transferred to the learners. Educational theories that we currently come to know play an important role in the effectiveness of the teaching and learning processes. In this study, the teaching practices of three Mathematics teachers in one of the secondary schools in Brunei Darussalam were observed and examined based on the work of three educational theorists, Robert Mills Gagné, Lev Semyonovich Vygotsky and Burrhus Frederic Skinner. The observational vantage points of the research focused on the learning conditions of the lesson, students’ interaction with their teachers and peers, and the teachers’ responses to their learners’ behaviour during the lesson. The qualitative reports indicated that the most commonly “not seen” events by the three teachers were gaining students attention, assessing the performance and enhancing retention and transfer; social interactions for example, discussions were absent in all three observed lessons; and all the three teachers gave some kind of reinforcements, such as praises and extra activities, during their lessons.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".