Concept Mapping: An Innovative Tool to Teach Critical Community Health Nursing Using the Example of Population Health Promotion
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
Introduction: Concept mapping is a tool that is used to visualize complex factors and the links between them. While concept mapping is represented in community health practice and research literature, we found little information about using concept mapping in community health nursing education. Background: We developed an innovative concept map assignment to assist students to visualize complex inter-related factors and begin thinking about appropriate and relevant nursing interventions, using the Population Health Promotion Model (PHPM). Discussion: Concept maps enhanced the quality of meaningful teaching and learning at the university level, acting as both a learning and assessment strategy. Students exhibited critical thinking and drew conclusions that involved larger systemic issues such as social justice and health equity. Conclusion: Concept mapping is a powerful tool that facilitates and assesses authentic student learning. The concept map assignment was also an effective tool to help students grasp and apply the PHPM.
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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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