ArticleHeliyon2024
Medical and nursing students' satisfaction with e-learning platforms during the COVID-19 pandemic: Initial findings of an experimental project in China.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Review
- Looking Back on Digital Medical Education Over the Last 25 Years and Looking to the Future: Narrative Review.Journal of medical Internet research · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Satisfaction with learning management systems (LMSs) is an essential indicator of students' e-learning experiences and reflects the quality of e-learning. Applying the technology satisfaction model, the present study aimed to investigate medical and nursing students' satisfaction with LMSs and its predictors. We conducted our survey at a medical university located in East China and received a total of 329 effective responses. Structural equation modelling was used to analyse the data. Our findings confirmed that perceived ease of use and perceived usefulness were two direct predictors of medical and nursing students' satisfaction with LMSs. Furthermore, the influence of perceived usefulness on satisfaction was more powerful than that of perceived ease of use. This study also substantiated that computer self-efficacy and perceived ease of use can indirectly impact medical and nursing students' satisfaction with LMSs. Our research effectively links the theoretical hypotheses with empirical findings, highlighting the central role of Computer Self-Efficacy (CSE), perceived ease of use, and perceived usefulness in shaping medical and nursing students' satisfaction with LMSs. Our findings contributed to the understanding of the technology satisfaction model and medical and nursing students' e-learning during the COVID-19 pandemic.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.