Technology-Supported Guidance Models Stimulating the Development of Critical Thinking in Clinical Practice: Mixed Methods Systematic Review
Bibliographic record
Abstract
BACKGROUND: Nursing education has increasingly focused on critical thinking among nursing students, as critical thinking is a desired outcome of nursing education. Particular attention is given to the potential of technological tools in guiding nursing students to stimulate the development of critical thinking; however, the general landscape, facilitators, and challenges of these guidance models remain unexplored, and no previous mixed methods systematic review on the subject has been identified. OBJECTIVE: This study aims to synthesize existing evidence on technology-supported guidance models used in nursing education to stimulate the development of critical thinking in nursing students in clinical practice. METHODS: This mixed methods systematic review adopted a convergent, integrated design to facilitate thematic synthesis. This study followed the guidelines of the Joanna Briggs Institute Manual for Evidence Synthesis. RESULTS: We identified 3 analytical themes: learning processes implemented to stimulate critical thinking, organization of the learning process to stimulate critical thinking, and factors influencing the perception of the learning process. We also identified 4 guidance models, all based on facilitator or preceptorship models using tailored instructional or learning strategies and one or several technological tools that were either generic or custom-made for specific outcomes. The main facilitators of these technology-supported guidance models were nurse educators or nurse preceptors, and the main challenges in using technology-supported guidance models were the stress associated with technical difficulties or increased cognitive load. CONCLUSIONS: Although we were able to identify 4 technology-supported guidance models, our results indicate a research gap regarding the use of these models in nursing education, with the specific aim of stimulating the development of critical thinking. Both nurse preceptors and nurse educators play a crucial role in the development of critical thinking among nursing students, and technology is essential for such development. However, technology-supported guidance models should be supervised to mitigate the associated stress. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/25126.
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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 | 0.069 | 0.204 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.013 |
| Bibliometrics | 0.026 | 0.020 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".