Engineering Co-op and Internship Experiences: The Roles of Workplaces, Academic Institutions and Students
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
Work-integrated learning, particularly in theform of co-ops and internships, has long been an integralpart of many engineering programs. While recentgovernment interest in work-integrated learning hasraised its profile, it is unclear how the three main actors –the workplace, the academic institution and studentsthemselves – interact with each other to enhance students’learning experiences and outcomes. This paper attemptsto fill this gap by examining engineering co-op andinternship literature as well as programming practices atnineteen North American universities. In light of aconceptual framework foregrounding organizationalstructure, human agency and learning outcomes, weidentified five themes that demonstrated the interactionsbetween organizational and individual factors involved inthe workplace learning process of engineering co-ops andinternships. The paper contributes to the discussion onwork-integrated engineering education by highlightingthe usefulness of the conceptual framework to empiricalresearch on workplace learning and the practicalimplications of the findings for engineering educators,employers, and engineering co-op and internshipstudents.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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