ASSESSING AND DEVELOPING THE INDIVIDUAL AND TEAM WORK ATTRIBUTE
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
Working effectively in teams is an essential skill that must be developed over the course of an engineering degree program. However, soft skills such as effective team behaviours can be difficult to assess and develop in students. Accordingly, the paper outlines our efforts to operationalize the Individual and Team Work attribute with the intention of outlining best practices in assessing, tracking, and enhancing the graduate attribute for both student development and accreditation purposes.A survey comprised of 40 Likert-scale items and 3 open-ended response questions was administered to all undergraduate students at a large North American university. The survey resulted in key findings, including that students rated their team work competencies significantly lower than they rated the perceived importance of those competencies for success in the workplace. Additionally, females reported significantly lower satisfaction and support in their team experiences than male students. These findings and others resulted in 12 evidence-based recommendations to strategically support the Individual and Team Work attribute.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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