EXPERIENCES WITH REMOTE TEACHING OF MANUFACTURING ENGINEERING LABORATORY AND PROJECT COURSES
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
COVID-19 has profoundly affected many, if not all, Canadian engineering courses during the2020/2021 academic year, many of which transitioned to online teaching. Delivering hands-on, highly interactive laboratory and design project courses is particularly challenging to do remotely. We present and reflect on experiences with remote teaching of three hands-on laboratory courses in a new Manufacturing Engineering program at the University ofBritish Columbia (UBC). These courses include MANU 230: Manufacturing Laboratory, MANU 330: Manufacturing Engineering Project I, and MANU 386: Industrial Automation. All three courses are taught in the same laboratory/classroom by one of the authors. In general, it appears that the students appreciated the remote lab experiences provided. However, it wasapparent from both survey data and informal feedback that students preferred in-person laboratory sessions. While, perhaps not an ideal method of delivering these types of courses there appears to be some place for remote laboratory classes in the future.
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 | 0.000 | 0.000 |
| 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