Problem-Based Lab Education: Redesign of a Senior Year Chemical Engineering Lab Course to Promote Autonomy, Critical Thinking, and Problem-Solving Skills
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This abstract is submitted to the 2019 ASEE PNW conference to be considered for an abstract-reviewed presentation (not a full paper). Upper-year engineering students are quite adept at collecting and organizing experimental data as part of prescribed laboratory exercises. Although these labs provide good opportunities to develop analytical skills, they offer few avenues to apply creative problem-solving or experimental design skills. Furthermore, when students are faced with technical difficulties in the lab, many rely on TAs or instructors to solve them and are reluctant to, or simply assume that it is not up to them to, attempt a solution themselves. To alleviate some of these issues, building on previous work, the senior year chemical engineering lab course at UBC was redesigned using a Problem-Based Learning (PBL) framework and greatly reduced formal supervision, with the aim to promote resourcefulness and problem-solving, troubleshooting, and critical thinking skills. The structure and deliverables of this course will be described, student performance assessed, and the feedback of students regarding this approach will be presented. In this course, student teams perform a single multi-week PBL lab per term. An instruction manual for the relevant equipment is provided, but with no suggested experimental design or data collection protocol. Open-ended industrially-relevant problem statements, consisting of design, optimization or investigative objectives, are provided as suggested context, but teams are not bound by these statements and are encouraged to propose alternative problems based on their interests. Before beginning their experimental work, each team prepares a formal project proposal, which includes a comprehensive review of background theory, experimental design, budget an environmental impact assessment, and safety audit of the procedure. At the beginning of each experimental session, teams provide an updated work plan outlining the work performed to date, the work to be performed during that lab session, and any changes to the original proposal deemed necessary, mirroring industrial protocols. Students present their work both orally and as a written report at the end of the session. To increase the independence and self-reliance of the teams, TA and instructor involvement is greatly reduced. TAs are only present in the lab for the first hour of each experimental session to review and evaluate the work plan, ensure the students are prepared, and that they are able to perform their experiments safely. TAs are instructed not to directly answer technical questions and are there only as observers. This forced students to make their own decisions and judgements, troubleshoot any technical issues or unexpected results, and experiment with the process themselves. When initially presented with the course structure, many students were apprehensive, with some voicing their displeasure at having traditional supports and direction removed. At the conclusion of the course however, student feedback, collected through a survey, was overwhelmingly positive. The vast majority of students reported benefitting from the independence and responsibility for their work, with the majority self-reporting improvements in confidence in their engineering judgement and critical thinking skills. A comprehensive analysis of student feedback will be presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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