How nursing students perform in problem-based learning tutorials-A South African perspective
Bibliographic record
Abstract
Background: Problem-based learning tutorials are considered the main vehicle for nursing students to acquire the skills needed to deal with the complexities of nursing practice. How students’ perform in these tutorials is an important measure of their learning development and skill acquisition. Purpose: The purpose of this two phased study was to determine and compare the performance of undergraduate nursing students in Problem-based Learning (PBL) tutorials using a validated evaluation instrument. In Phase-1 of the study the instrument was validated which led to the development of the computer-based: Tutorial Performance Evaluator (TPE). In Phase-2 the performance of undergraduate nursing students in PBL tutorials was assessed and described through the use of this instrument by the students and their facilitators. Methods: A cross-sectional, comparative design was used employing two sample sets: the first sample consisted of a cross-section of the total population of undergraduate nursing students (N = 53) in their first-year to fourth-year of study in a four year Bachelors degree. The second sample comprised the total population of facilitators (N = 6), who were directly involved in facilitating PBL tutorials. A computer-based TPE with seven main-items (skills) and 34 sub-items was used to elicit data on students’ self-assessment and facilitator-assessment of tutorial performance. Mean tutorial performance scores were calculated; correlations were drawn between student and facilitator scores and comparisons were made between the different years of study and within the main items to evaluate progress in skill acquisition. Results: Major findings included notable differences between facilitator-assessment and self-assessment together with a poor performance in all seven constructs on the evaluation instrument amongst first-year students. There was a significant improvement in the mean tutorial performance score from 27% in first-year students to 87% in fourth-year students. Conclusions: The findings suggest that first-year students struggle with PBL and a recommendation is to consider alternative educational strategies to prepare first year students for PBL.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".