EVALUATION OF INDIVIDUAL MEMBERS IN ENGINEERING DESIGN TEAMS
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
The curriculum of accredited engineering programs in Canada must culminate with a significant design experience where students must demonstrate an ability to work in teams. The determination of individual grades for work products submitted by a team is however a challenging task. To deter students from free riding on the efforts of their teammates, every team member should not simply receive the same grade. Individual grades in the senior process design course at the University of New Brunswick are determined by first assigning a team grade to team deliverables and then adjusting each team member’s grade up or down using a multiplier. The value of the multiplier is based on peer and mentor evaluations and on the level of participation of the student in course activities. The peer ratings collected in 2014-2015 are generally higher than the mentor ratings, likely because of peer pressures to give high ratings. The bias is greatly reduced however when the evaluations are normalized by dividing the rating for each student by the team average. Because of this bias, the mentor evaluations should complement the peer ratings when providing formative feedback to students and determining individual team member grades.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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