A THREE-TIER EVALUATION RUBRIC FOR THE ASSESSMENT OF GROUP PROJECTS IN CHEMICAL ENGINEERING DESIGN COURSES
Bibliographic record
Abstract
Abstract – Group projects are often key to engineering design courses since they simultaneously develop teamwork and communication skills in the context of solving difficult engineering problems. However, fair, consistent, and transparent grading of these projects are difficult to achieve, and the individual contribution of students can likewise be difficult to evaluate.
 Standardized marking rubrics are often used to increase the consistency and fairness of project evaluations; however, these frequently lack a systematic means for evaluating individual effort within group work. Rubrics also are difficult to employ when there are numerous possible solutions and where some solutions are more elegant or challenging when compared to others.
 To provide a consistent accounting of individual effort and the difficulty of a submitted group design solution, a three-tier marking rubric was developed. Comparing the project grades between two cohorts in the same course showed that there was a broader distribution of grades when using the three-tier marking scheme.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".