Outcomes-Based Assessment in Action: Engineering Faculty Examine Graduate Attributes in their 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
In 2009, the Canadian Engineering Accreditation Board (CEAB) called for the assessment of 12 graduate attributes in all Canadianaccredited engineering programs. As part of this process, data are required from a variety of stakeholders, including the facultiesresponsible for teaching the host of courses offered in Canada’s diverse engineering programs. This paper describes the second yearof a three-year study in the Faculty of Engineering at the University of Manitoba that explores how the CEAB graduate attributesare manifested and measured in its curricula. The four attributes targeted were Problem Analysis, Use of Engineering Tools,Communication Skills, and Ethics and Equity. Fifteen instructors from each of the Departments of Biosystems, Civil, Electricaland Computer, and Mechanical Engineering considered the presence of these attributes in one of their engineering courses taughtin the academic year 2012–13, using a self-administered checklist. Findings indicated that the traditional attributes in engineeringwere assessed more frequently than the professional attributes, and that specifically, there was little assessment evidence of Ethicsand Equity and theOralfocus of Communication Skills. There was some evidence of formative assessment, but generallyassessments were limited to traditional quantitative, summative assessments. Competency levels were expressed in a variety of ways,highlighting the need for the development of a common language for assessment. The study underscores the different rolesassessment can take and the complexity of sustaining a faculty-wide, outcomes-based assessment protocol.
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 | 0.001 | 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