The power of affective learning strategies on social justice development in nursing education
Bibliographic record
Abstract
Nursing professional values are critical for the practice of nurses, yet the development of curricula fundamentally supporting these values has been slow to develop. The question remains as to the best teaching strategies that foster the integration of these core values as a key focus for nurses throughout their professional practice. The purpose of this article is to report the findings of a research project related to an affective learning strategy, and the potential of such strategies to guide undergraduate nursing students in the development of professionalism. While conducting a study related to the use of poverty simulation and the attitudes of nursing students, participants provided compelling narratives highlighting a greater understanding of the constructs of social justice; a potentially more profound purpose for this pedagogical strategy. Focus group narratives revealed themes focusing on the concepts of professional nursing values, specifically social justice. The themes included: The American Dream Isn’t for Everyone, Trapped in my Own Life, Completely out of Control, and It’s Just Not Enough. Findings showed that participants experienced grave realizations regarding not only the experience of poverty, but of the widespread social norms that contribute to injustices for a vast population in our society. This research contributes to the body of literature regarding the use of affective learning strategies as an effective way to teach nursing professional values, such as social justice, to enhance nursing graduates’ ability to integrate these values in their own practice.
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How this classification was reachedexpand
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 | 0.003 | 0.005 |
| 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".