Peer Review as an Active Learning Strategy in a Large First Year Course
Bibliographic record
Abstract
Peer-review of writing is an instructional strategy used to develop students’ critical thinking skills, writing competence and as a way of engaging students as active agents in their learning process [1,3,4]. In the Fall 2013 semester, two peer-review assignments were introduced in a compulsory first year engineering course, Introduction to the Engineering Profession, taken by nearly 500 students (in two sections). The objectives of the peer-review assignments were two-fold: (1) to help improve students’ writing by providing them with constructive criticism and feedback and (2) to develop students’ critical thinking and editing skills. Using a rubric provided by the instructor, students were asked to evaluate their peers’ written assignments in three categories: overall presentation, clarity and coherence (organization), and justification/explanation of the topic being discussed/analyzed. One assignment addressed the inter-disciplinary nature of the engineering profession while the second focused on making ethical decisions. Evaluators were required to justify the score given in each category, as well as to provide a short written comment on the paper as a whole. At the end of term, a class survey was conducted where students reflected on the peer review assignment from a learning perspective. This study presents the results of an analysis of those reflections. Overall, students and the instructor valued this instructional approach. Implications of this type of instructional strategy for undergraduate engineering education are also discussed.
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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 | 0.001 |
| 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".