Using Brunerian Learning Theory with Educational Simulations to Teach Concepts
Bibliographic record
Abstract
The present study maintains that consistently effective leaming materialscan best be generated if the prescriptions instructional designers use are founded on learning theory. It is also considered critical that cognitive processes central to the task demands and strategies employed to address them be established. To be practical, we further recommend that only a single, process-oriented lesson, rather than individualized treatment, be implemented. Instructional simulations met these criteria, being tightly bound to Bruner's theoretical approach, and inherently capable of addressing aptitude deficiencies. Subjects were assessed for spatial visualization ability, grouped, randomly assigned to simulation or non-simulation treatments, and tested immediately, one week, and five weeks after instruction. The simulation significantly increased the high-aptitude learners' efficiency (and initially effectiveness), and low-aptitude learners' effectiveness. The validity of a theory-based, aptitude-enhancing, standardized approach was supported, andis discussed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".