Establishing Meaningful Learning in Online Nursing Postconferences
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
BACKGROUND: Effective teaching and learning strategies in online postconference can assist students to find meaning within clinical experiences. PURPOSE: To explore this, we completed a literature review about meaningful learning in online clinical postconferencing in prelicensure nursing education. METHODS: Articles that were peer-reviewed, published within the last 10 years, written in English, and addressed online learning in clinical postconferences in prelicensure nursing programs were included. RESULTS: Analysis revealed the following themes: connecting theory to practice, reflective practice, impact on future practice, peer and instructor support, mentoring and leadership development, giving and receiving feedback effectively, critical thinking, and engagement of active learners. Gaps were evident with minimal evidence-based practice described related to postconferences in general. Additionally, there is limited discussion of online postconferencing. CONCLUSIONS: Understanding the nuances of meaningful learning in online postconference is critical to facilitating students' ability to connect theory to 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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