Using Video Feedback Through Smartphone Instant Messaging in Fundamental Nursing Skills Teaching: Observational Study
Bibliographic record
Abstract
BACKGROUND: Video feedback has been shown to be an effective teaching tool that can improve student learning when having them view their own performance. However, the literature on the effect of integrating smartphones with video feedback in fundamental nursing skills teaching is sparse. OBJECTIVE: This study aimed to explore the potential effects of video feedback through smartphone-based instant messaging on teaching undergraduate nursing students fundamental nursing skills. METHODS: We conducted a study on teaching fundamental nursing skills to 6 classes of second-year undergraduate nursing students. In 2 classes (the intervention group), the instructor elected to use smartphone-based video feedback to facilitate teaching; instructors in the other 4 classes (the control group) elected to use routine methods of teaching without video feedback. Scores from the final examination, in-class assignments, and the General Self-Efficacy Scale questionnaire were collected and compared between the two groups. Multiple linear regression analysis was performed to estimate the independent effect of video feedback after adjusting for gender, age, and prior experience in the use of WeChat/QQ in learning applications. An ad hoc questionnaire was used for student evaluation of the novel smartphone-based video feedback teaching method. RESULTS: A total of 195 nursing students (65 in the video feedback group and 130 in the control group) completed the study and were included in the final analysis. Mean and standard deviation of scores on the final examination, bed making, aseptic procedure, vital signs measurement, and oxygen therapy were 91.29 (SD 2.36), 90.52 (SD 3.18), 93.23 (SD 3.16), 91.65 (SD 4.21), and 92.06 (SD 3.58), respectively, in the video feedback group and 89.99 (SD 3.12), 81.71 (SD 8.63), 87.12 (SD 5.50), 87.45 (SD 8.00), and 90.37 (SD 6.36), respectively, in the control group (differences were statistically significant). The mean and standard deviation of scores for assignments in catheterization and enema and General Self-Efficacy Scale were 89.69 (SD 3.22), 91.14 (SD 3.15), and 24.52 (SD 5.35), respectively, in the video feedback group and 88.82 (SD 7.48), 90.79 (SD 6.08), and 24.50 (SD 6.16), respectively, in the control group (differences were not statistically significant). The majority (over 98%) of nursing students were satisfied with this smartphone-based video feedback teaching method. CONCLUSIONS: Video feedback through smartphone-based instant messaging may be an effective way to improve nursing students' academic performance and professional skills.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".