Student satisfaction with use of an online peer feedback system
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
We contribute to the growing evidence of the positive effect of use of online peer feedback tools on students’ teamwork skills development. We do so by exploring individual and contextual factors underlying satisfaction with using a peer feedback system alongside team projects. Employing path analytical framework and bootstrap methods, we analysed data from an international sample of 100 project teams in management studies. Drawing on procedural justice theory, we theorised and found support that students’ uncertainty avoidance orientation and virtuality in collaboration were positively related to their satisfaction with use of a peer feedback system. Such satisfaction in turn allowed them to be more effective team members. Our findings provide evidence for higher education institutions and instructors considering the adoption of online peer feedback systems alongside teamwork in their curricula. Specifically, peer feedback appears to be effective in the development of teamwork skills and students appreciate the opportunity to provide feedback to their peers in a structured and dedicated environment. Our findings are timely and of important practical significance as educational institutions increasingly rely on the use of computer-mediated technology during the COVID-19 pandemic.
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 | 0.000 | 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) | 0.002 | 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