An analysis of engineering educators’ understanding of complementary studies courses using the repertory grid technique
Why this work is in the frame
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Bibliographic record
Abstract
Accreditation bodies such as the Engineering Council of South Africa and the Canadian Engineering Accreditation Board have a group of courses that fall under the umbrella of Complementary Studies. This term is used to describe a set of engineering courses that include knowledge areas other than the more common mathematical sciences, natural sciences, engineering sciences, design and synthesis, and workintegrated learning. Studies have shown that engineering educators sometimes view these courses negatively. They are seen as distracting the focus of the students on the so-called technical courses, which the educators feel are more important. This paper reports on a research study that explored the way that engineering educators make sense of complementary studies courses within an industrial engineering curriculum. The repertory grid technique was used to explore complementary studies courses when compared to other engineering courses within the same curriculum. The relationships between elements and constructs in the grids were analysed using the repertory grid techniques of principal component analysis and cluster analysis. What became clear was that while most of the educators interviewed did recognise complementary studies courses as different to courses considered as core or technical, what made them different was very unclear. Each educator had a very different conception of what defines, differentiates or constitutes a complementary studies course. This range of variation may go some way to explaining why complementary courses seem out of place in engineering programs by educators and students alike.
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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 | 0.000 |
| 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) | 0.007 | 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