Evaluation of Student Engagement, Communication, and Collaboration During Online Group Work: Experiences of Fourth-Year Veterinary Medicine Students
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
Accelerated by the COVID-19 pandemic, online teaching has become widely established in higher education in recent years. However, little is known about the influence of the online environment on collaborative student activities, which are an integral part of veterinary education. This study explored engagement, collaboration, and communication among fourth-year veterinary students working in groups on online case-based learning (CBL) activities. Data were collected by questionnaire (93/135) and anonymous peer assessment (98/135) at the end of the trimester. While most students (67%) enjoyed group work and 75% considered it of benefit to their learning, the results indicated that the students' interaction was mainly limited to task management and collating individual answers on shared documents. Rather than meeting online, students communicated by chat and messenger apps. Agreement of roles, rules, and the group contract were largely treated as box-ticking exercises. Conflict was the only factor that affected group work satisfaction and was largely avoided rather than addressed. Interestingly lack of student engagement in group work was not related to overall academic performance and had no impact on their end-of-term exam results. This study highlights high student satisfaction and engagement with online group CBL activities even when collaboration and communication were limited. Achieving higher levels of collaborative learning involving co-regulation of learning and metacognitive processing of learning content may require more specific, formal training in relevant skill sets from an early stage of the veterinary curriculum.
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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 | 0.013 | 0.003 |
| 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 it