Student Response to Remote-Online Case-Based Learning: A Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Case-based learning (CBL) typically involves face-to-face interaction in small collaborative groups with a focus on self-directed study. To our knowledge, no published studies report an evaluation of Web conferencing in CBL. OBJECTIVE: The primary aim of this study was to explore student perceptions and attitudes in response to a remote-online case-based learning (RO-CBL) experience. METHODS: This study took place over a 2-week period in 2013 at Monash University, Victoria, Australia. A third year cohort (n=73) of physiotherapy students was invited to participate. Students were required to participate in 2 training sessions, followed by RO-CBL across 2 sessions. The primary outcome of interest was the student feedback on the quality of the learning experience during RO-CBL participation. This was explored with a focus group and a survey. RESULTS: Most students (68/73) completed the postintervention survey (nonparticipation rate 8%). RO-CBL was generally well received by participants, with 59% (40/68) of participates stating that they'd like RO-CBL to be used in the future and 78% (53/68) of participants believing they could meet the CBL's learning objectives via RO-CBL. The 4 key themes relevant to student response to RO-CBL that emerged from the focus groups and open-ended questions on the postintervention survey were how RO-CBL compared to expectations, key benefits of RO-CBL including flexibility and time and cost savings, communication challenges in the online environment compared to face-to-face, and implications of moving to an online platform. CONCLUSIONS: Web conferencing may be a suitable medium for students to participate in CBL. Participants were satisfied with the learning activity and felt they could meet the CBL's learning objectives. Further study should evaluate Web conferencing CBL across an entire semester in regard to student satisfaction, perceived depth of learning, and learning outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".