Lab to Life: A SWOT-AHP Model for Experiential Learning in Engineering Programs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Experiential learning has recently been recognized as a cornerstone of engineering education, as it provides students with hands-on experience. It also bridges the theoretical concepts with their applications in real world. The present study concerns with development of a structured methodology for assessment and enhancing experiential learning practices using a hybrid SWOT-AHP approach. A comprehensive questionnaire was distributed among faculty members in the Mechanical and Aerospace Engineering Department of Carleton University to identify key internal (strengths and weaknesses) and external (opportunities and threats) factors influencing experiential learning. The Analytic Hierarchy Process (AHP) was employed to rank and prioritize these factors based on the collected input. This study resulted in the development of a strategic SWOT matrix, which provides actionable recommendations to optimize teaching methodologies, institutional policies, and resource allocation in the department. The findings contribute to a data-driven framework for continuous improvement in the engineering education.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it