Student Peer Evaluated Line Balancing Competition
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 Student Peer Evaluated Line Balancing Competition is a 30-minute in-class problem-based learning experiential exercise that challenges student groups to design a feasible and efficient laptop computer assembly line. Each student group’s proposed design is publicly peer-reviewed by the rest of the class, enabling students to evaluate various alternatives and realize the key requirements for optimally balancing an assembly line. Evidence of effectiveness is provided, including student survey results and a statistical analysis of exam question performance both before and after the exercise was incorporated into our business undergraduate operations management class. The survey revealed that 96% of students recommended continued usage and 92% believed the competition helped them to be able to determine a feasible solution for line balancing problems. Exam question performance analysis revealed that our initial instructions for the competition actually resulted in lower performance compared to traditional lecture. We subsequently improved the instructions and found that this change has resulted in similar exam question performance as traditional lecture. The result is an exercise that significantly improves student engagement while maintaining student performance previously achieved through traditional lecture.
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 | 0.001 | 0.000 |
| 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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