Double Trouble: Student perspectives on the transition from online prescribed labs, to in-person and open-ended problem-based labs
Bibliographic record
Abstract
In the Department of Chemical and Biological Engineering (CHBE) at UBC, the lab courses in 2nd and 3rd year require students to complete prescribed (curated and self-contained) experiments, and the 4th year course follows an open-ended Problem-Based Lab (PBL) model which provides students with much less explicit direction. Like other institutions in Canada, all instruction at UBC, including the lab courses, had to shift to remote delivery during the 2020-2021 academic year in response to the pandemic. The result of this is that 3rd and 4th year CHBE students faced either one or two transitions in their lab courses, namely the transition from online to in-person education, and from prescribed to open-ended problem-based labs, each of which presents particular challenges. Students were invited to complete a survey to share their perspectives on the general value of their lab courses for their training as engineers, their perception of the value of online lab course delivery, and their experiences with one or both of the aforementioned transitions. The results are presented here.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.009 |
| Scholarly communication | 0.020 | 0.008 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".