Validation of the Mobile Information Software Evaluation Tool (MISET) With Nursing Students
Bibliographic record
Abstract
BACKGROUND: This study evaluated the Mobile Information Software Evaluation Tool (MISET) with a sample of Canadian undergraduate nursing students (N = 240). METHOD: Psychometric analyses determined how well the MISET assessed the extent that nursing students find mobile device-based information resources useful and supportive of learning in the clinical and classroom settings. RESULTS: The MISET has a valid three-factor structure with high explained variance (74.7%). Internal consistency reliabilities were high for the MISET total (.90) and three subscales: Usefulness/Helpfulness, Information Literacy Support, and Use of Evidence-Based Sources (.87 to .94). Construct validity evidence included significantly higher mean total MISET, Helpfulness/Usefulness, and Information Literacy Support scores for senior students and those with higher computer competence. CONCLUSION: The MISET is a promising tool to evaluate mobile information technologies and information literacy support; however, longitudinal assessment of changes in scores over time would determine scale sensitivity and responsiveness. [J Nurs Educ. 2016;55(7):385-390.].
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".