Design Of An Instrument To Assess Understanding Of Engineering Design
Bibliographic record
Abstract
Engineering design education is an important element of any undergraduate engineering curriculum.It is also an element undergoing constant evolution, reflecting the rapidly evolving needs of engineering industry and academia.Engineering graduates are expected to contribute effectively as members of multidisciplinary engineering design teams.Enabling this success requires that engineering design educators develop an understanding of the diverse disciplinary perspectives on engineering design and of the evolving perspectives of their students.This paper first describes the disciplinary perspectives that emerged as a result of some preliminary research on engineering design education, and then describes the development of an instrument for evaluating individual understandings of engineering design.Disciplinary perspectives were explored through interviewing the instructors of four capstone design courses in different engineering disciplines within a large engineering Faculty.Each instructor was asked about their instructional history, the requirements and expectations of graduates from their respective engineering undergraduate program, and their past attempts to understand course outcomes.Although instrument testing is still required, the instrument developed can be presented to a group of students at the beginning, mid-stream and completion of their capstone design course.It can also be used to track changes in students' perceptions, as well as the influence that a particular discipline may have on an individual's understanding of engineering design.Course instructors will then be able to identify which aspects of their courses are most influential and which require more development.Recognition of the design methodologies and expectations within specific engineering disciplines is an important first step in developing a curriculum that enables engineers to work across those disciplines.An instrument that supports the analysis of a Faculty's progression towards this end is a valuable addition to the engineering design educator's toolbox.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".