Blended Learning in an Upper Year Engineering Course: The Relationship between Students’ Program Year, Interactions with Online Material, and Academic Performance
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
At a comprehensive, public university in Western Canada, a fourth-year course in risk and safety management was recently made a requirement for all engineering students; depending on their program, students may take this course in their second, third, fourth, or fifth year of their program. As a result of increasing class sizes, this course was shifted from traditional to blended instruction. Since blending and opening this course to students with varying years of undergraduate engineering experience, instructors noted a difference in students’ maturity (e.g., a change in quantity and quality of in-class discussion, questions, participation, student-teacher interactions, and problem solving capabilities) and questioned whether this impacted their interactions with online material. Research examining the impact of blended learning in Engineering has primarily focused on large first-year undergraduate courses; research about blended learning in upper-year engineering courses is sparse. Studies investigating courses with students of varying years of experience in the program are virtually non-existent. Therefore, to better understand students’ interactions with online material during blended learning as connected to years in their program, we examined the relationship between levels of interaction and performance of students by year in program. This study analyzed approximately 2000 students’ interactions with online material and performance across five sections of a risk-management course in engineering. We found that students who had completed more years of their program interacted less with online material than students earlier in their undergraduate careers. Academic performance, on the other hand, was higher for students who had interacted more with online material and slightly higher for students who had completed more years in their program. These results suggest that the delivery of instructional materials may need to be tailored to students’ year in their program. Further implications and areas of future study are discussed.
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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 | 0.012 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.006 |
| 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