Difficult incidents and tutor interventions in problem‐based learning tutorials
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
CONTEXT: Tutors report difficult incidents and distressing conflicts that adversely affect learning in their problem-based learning (PBL) groups. Faculty development (training) and peer support should help them to manage this. Yet our understanding of these problems and how to deal with them often seems inadequate to help tutors. OBJECTIVES: The aim of this study was to categorise difficult incidents and the interventions that skilled tutors used in response, and to determine the effectiveness of those responses. METHODS: Thirty experienced and highly rated tutors in our Year 1 and 2 medical curriculum took part in semi-structured interviews to: identify and describe difficult incidents; describe how they responded, and assess the success of each response. Recorded and transcribed data were analysed thematically to develop typologies of difficult incidents and interventions and compare reported success or failure. RESULTS: The 94 reported difficult incidents belonged to the broad categories 'individual student' or 'group dynamics'. Tutors described 142 interventions in response to these difficult incidents, categorised as: (i) tutor intervenes during tutorial; (ii) tutor gives feedback outside tutorial, or (iii) student or group intervenes. Incidents in the 'individual student' category were addressed relatively unsuccessfully (effective < 50% of the time) by response (i), but with moderate success by response (ii) and successfully (> 75% of the time) by response (iii). None of the interventions worked well when used in response to problems related to 'group dynamics'. Overall, 59% of the difficult incidents were dealt with successfully. CONCLUSIONS: Dysfunctional PBL groups can be highly challenging, even for experienced and skilled tutors. Within-tutorial feedback, the treatment that tutors are most frequently advised to apply, was often not effective. Our study suggests that the collective responsibility of the group, rather than of the tutor, to deal with these difficulties should be emphasised.
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 | 0.002 | 0.006 |
| 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) | 0.000 | 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