RN to BSN Students’ communication satisfaction with asynchronous discussion forums: Audio-video versus text-based responses
Bibliographic record
Abstract
Objective: This pilot study examined an innovative strategy for an RN to BSN online program, specifically focused on the required asynchronous discussion forums. The aim of the study was to compare RN to BSN students’ communication satisfaction with audio-video discussion responses versus the traditional text-based responses.Methods: Utilizing a pretest-posttest design, RN to BSN student’s communication satisfaction with traditional text-based discussion responses was measured using a 5-point Likert scale survey at the end of fall semester. Audio-video responses were the required discussion response format during the subsequent spring semester. Students’ communication satisfaction with asynchronous audio-video discussion responses was measured at the end of the spring semester. Paired t-tests and descriptive statistics were conducted.Results: Students satisfaction significantly increased with audio-video discussion responses for the extent communication was positive, accurate and free flowing. There were no statistically significant differences in students’ satisfaction between text and audio-video format related to the extent communication motivated them to meet course goals and identify with the discussion, or with the extent instructors offered guidance and were open to ideas and attention to content.Conclusions: Although limited by a small sample size and low power (N = 16 pre-test, N = 17 post-test) the findings of this study may be of interest to online nurse educators who are seeking innovative strategies to improve student satisfaction within asynchronous discussion forums. With further research, the use of audio-video discussion responses may provide an alternative to the traditional text-based responses related to communication satisfaction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".