Connecting Practice to Evidence Using Laptop Computers in the Classroom
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
Evidenced-based practice is no longer a "frill" but a necessity, demanded by an evolving healthcare system and the needs of practice, professional nursing bodies, and American consumers who want safe, quality care. Although its importance has been touted by the profession, incorporating evidence into practice is not a skill for which nurses at point of care are ready. Preparation for evidence-based practice must begin in basic educational programs. Yet, the process of using evidence to guide practice is complex especially for undergraduate students who are only beginning to ask questions let alone answer them. Nursing schools have responded to the professional call to evidence-based practice with the use of a variety of teaching approaches. This article presents a unique approach, not previously described, involving the use of laptops in an undergraduate nursing research course to equip students for evidence-based practice, giving students hands-on experience with the process and introducing students to online resources. Student feedback and educator reflections highlight the value of the technology in expediting student learning and comfort with evidence-based practice.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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