Blended learning versus face-to-face learning in an undergraduate nursing health assessment course: A quasi-experimental study
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: Blended learning, which integrates face-to-face and online instruction, is increasingly being adopted. A gap remains in the literature related to blended learning, self-efficacy, knowledge and perceptions in undergraduate nursing. OBJECTIVES: To investigate outcomes of self-efficacy, knowledge and perceptions related to the implementation of a newly blended course. DESIGN: This was a quasi-experimental pre-post test design. SETTING: This study was conducted at an undergraduate university in Alberta, Canada. PARTICIPANTS: A total of 217 second-year undergraduate nursing students participated and 187 participants completed all study components. METHODS: A convenience sampling method was used. Data were collected at the start and end of the semesters. Data were analyzed using descriptive and inferential statistics using R(3.4.3) and R-Studio(1.1.423). RESULTS: There were no significant differences in self-efficacy scores between groups or in the pre-post surveys (p > 0.100) over time. There was no significant difference in knowledge between the blended online and face-to-face groups (p > 0.100). For students in the blended course, perceptions of the online learning environment were positive. CONCLUSION: Blended learning has the potential to foster innovative and flexible learning opportunities. This study supports continued use and evaluation of blended learning as a pedagogical approach.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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