LINKING THE CEAB GRADUATE ATTRIBUTE COMPETENCIES TO EMPLOYABILITY SKILLS 2000+: EQUIPPING STUDENTS WITH THE LANGUAGE AND TOOLS FOR CAREER/EMPLOYMENT SUCCESS
Bibliographic record
Abstract
Graduate attributes are a relevant and pressing topic for engineering educators as we work to find innovative ways to teach and assess them in our courses and programs. The graduate attributes defined by the Canadian Engineering Accreditation Board (CEAB) are left to faculty of accredited Canadian Engineering programs to characterize into manageable,authentic and assessable indicators. Faculty are then responsible for demonstrating that their students possess these competencies, and that their programs are effective in training students in the skills, knowledge, behaviours, attitudes and values that are fundamental to the 12 graduate attributes. It has been a mammoth task that is still, in many cases, in its inception.What if we could approach identifying and assessing the CEAB graduate attributes in another way? Should we be expecting faculty to be solely responsible for assessing students’ graduate attribute competencies? Applying Knowles Theory of Andragogy and Super’s Theory on Developmental Process of Vocational Behaviour, we are able to explain how students, as adult learners, are motivated to identify and assess their own skills and competencies, influenced by their life situations and therelevance of employment to their immediate and future career goals.If we provide the framework for establishing the transference of the CEAB graduate attributes to their employment and career goals, students can be given the motivation to identify, and indeed, showcase their own competencies. Connecting the CEAB graduate attributes to the Conference Board of Canada Employability Skills 2000+ translates the attributes into a language recognizable and relevant to all engineering stakeholders, and may inspire students to seek understanding of the required engineering competencies as they focus on gaining employment, and ultimately achieving career success
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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 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".