Empowering Engineering Students: A Targeted Strategy to Strengthen Mathematical Foundations Through Adaptive Learning Tools
Why this work is in the frame
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Bibliographic record
Abstract
The Canadian Engineering Accreditation Board (CEAB) requires mathematical competency for engineers. Assessments at Université de Sherbrooke revealed significant gaps in students’ mathematical prior knowledge, necessitating enhanced preparation to meet CEAB standards. Purpose: This project aims to bridge first-year engineering students’ mathematical prior knowledge gaps through a self-paced educational strategy using a tailored platform, strengthening foundational understanding and abstraction skills. Approach: A three-tiered support framework was integrated as a self-paced computer-assisted platform into the curriculum alongside Problem and Project-Based Learning (PBL). It comprises a range of supplementary individual activities, including a review of students’ mathematical backgrounds, personalized learning experiences, interactive modules with immediate feedback, and continuous progress monitoring. Outcomes: Implemented in Fall 2024 for 198 students, 67.7% engaged with the platform, completing an average of 6.7 modules out of 14.8 recommended modules. Engagement was higher (85%) among students with a technical background. Feedback indicated that 76% of students would recommend the platform to new students, and 58% felt the modules were appropriately aligned with the PBL units. Conclusion: The engagement with the platform surpassed initial hopes, underscoring the significance of tailored educational strategies in effectively preparing students, particularly in mathematics, to meet the engineering challenges of tomorrow.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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