Engineering Elective Course Re-design to Promote Student Engagement
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
Computational Fluid Dynamics (CFD) for Engineering Design, is a 4th year mechanical engineering elective course. The course goal is for course graduates to be able to effectively use computer simulation tools to select optimal engineering designs based on the analysis of fluid flow performance. After being well received for many years, over several course offerings the class attendance, the student engagement in lectures, the student demonstration of key course concepts in the final summative project, and the student course evaluation scores all dropped.From student feedback to specific questions during the student course evaluation it was found that the students believed that their existing understanding of engineering fluid mechanics was sufficient to make well-informed design decisions and that the emphasized course concepts were not relevant to the engineering design process. This feedback informed a course re-design.After briefly describing the course context and objectives and the motivation theory that guided this course re-design, the two major features of the course re-design, pre/post-test activities and authentic engineering assignments, are described in some detail. Finally the impact of the re-design on student performance and outcomes from three offerings of the re-designed course is 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 | 0.001 | 0.001 |
| 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 | 0.001 | 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