Development of Attitudes in First Year Engineering Design
Bibliographic record
Abstract
Relatively few studies have been conducted to analyze how design courses change student attitudes towards engineering design. The first-year engineering program at USask includes an introductory design course that focuses on Problem Definition. One of the course learning objectives is the development of positive attitudes towards various facets of engineering design. As part of quality assurance in this regard, a survey tool was developed to assess student attitudes towards design. The survey, conducted in 2021 and 2022, included up to 18 statements. Each student rated their agreement with each statement on a 5-point Likert scale. Results were analyzed by comparing differences in response frequencies from students at the end of 2021 and 2022, and from before and after the design course in 2022. As well, one multiple-choice and two open-ended text responses were gathered and coded for each end-of-course survey. Results from the two cohorts were similar, in spite of some logistical differences between the two years. Also, attitudes across several of the statements were positively and significantly impacted by the design course suggesting that the course is meeting its objectives of developing positive attitudes towards design, and is doing so on a year-over-year basis.
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.
How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".