ArticlePloS one2022
Understanding student perceptions of social computing and online tools to enhance learning.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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.
- Students' perception and self-efficacy in blended learning of medical nutrition course: a mixed-method research.BMC medical education · 2024Article
- Correction: Understanding student perceptions of social computing and online tools to enhance learning.PloS one · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Social computing software and online tools are gaining credence in teaching and learning spaces, including higher education contexts. However, the adoption of social computing software does not automatically translate into effective teaching and learning if students' views and needs are not considered along with course learning outcomes. Thus, this study was conducted to explore students' perspectives and preferences for social computing software and online tools in a university elective course. We employed quantitative and qualitative approaches to understand students' shared and nuanced thoughts about social computing applications in the study. A questionnaire with quantitative and open-ended qualitative questions was used to collect data. Data were analyzed using descriptive statistics and an inductive thematic analysis approach. Our findings indicated mixed students' viewpoints, with some tools reported as highly beneficial while others were less beneficial. For instance, students valued asynchronous sessions, assignment feedback, online discussion, videos, and gamification but reported less interest in phones, journals, icons, and blogs. Students' specializations also appeared to influence their choice of tools. Those from Arts, Humanities, and Social Sciences expressed a slightly different preference than their comparts from Medicine and Health Sciences. Drawing on the findings, we discuss the implications for effective teaching and learning using social computing software, focusing on essential stakeholders. For instance, instructors must regularly conduct diagnostic feedback to determine appropriate tools that can effectively customize students' learning.
Indexed as
Identifiers
What OpenQuestion holds
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.