Designing a co-curricular program to support project-based learning in the engineering curriculum
Why this work is in the frame
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Bibliographic record
Abstract
There are many challenges related to the implementation of project-based learning (PBL) in the engineering curriculum. The amount of work required by instructors to design well-posed projects is a barrier to the broad adoption of PBL. On the other hand, poorly designed PBL activities often cause frustration among students, create extra work for instructors and students alike, and generally detract from the intended learning outcomes. In this paper we introduce a unique co-curricular program that supports instructors in the creation of high-quality and high-impact PBL activities. The program is innovative as it involves and benefits multiple stakeholders including students employed through the program, faculty, industry, and the engineering curriculum. The ongoing efforts to improve the program are also described.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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