Nursing students’ perceptions of effective problem-based learning tutors
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
Aim To explore baccalaureate nursing students' perceptions of what makes an effective tutor in problem-based learning courses, and the influence of effective teaching on students' learning and experience. Method Students enrolled in all four years of a baccalaureate nursing programme completed online surveys (n=511) and participated in focus groups (n=19). Data were analysed and combined using content analysis. Findings The data were summarised using five themes, the '5 Ps' of effective teaching in problem-based learning. Nursing students perceived effective problem-based learning tutors to be prepared with knowledge and facilitation skills, person-centred, passionate, professional and able to prepare students for success in the nursing programme. Effective tutors adjusted their approaches to students throughout the four years of the nursing programme. Conclusion Effective teaching in problem-based learning is essential and has significant effects on nursing students' learning, motivation and experience. Important attributes, skills and strategies of effective problem-based learning tutors were identified and may be used to enhance teaching and plan professional development initiatives.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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