Validating and applying an adapted OSLQ to examine adult learners’ online self-regulation
Dados Bibliográficos
| ID | 21555693 |
|---|---|
| Autores | Feng Lin (0000-0001-5240-5200, Teaching and Learning Centre, Singapore University of Social Sciences, Singapore, autor correspondente), Lyndon Lim (Teaching and Learning Centre, Singapore University of Social Sciences, Singapore), Yan Yin Ho (Teaching and Learning Centre, Singapore University of Social Sciences, Singapore), Bao Zhen Tan (0000-0002-1542-4530, Singapore University of Social Sciences), Wei Ying Lim (Teaching and Learning Centre, Singapore University of Social Sciences, Singapore) |
| Ano | 2023 |
| Volume | 42 |
| Fascículo | 7 |
| Páginas | 1684-1699 |
| Data de publicação | 2023-10-03 |
| Open Access | Não |
| Tipo | ARTICLE |
| Periódico | Higher Education Research & Development (JOURNAL) |
| Identificadores do periódico | ISSN: 0729-4360 • E-ISSN: 1469-8366 |
| Editora | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07294360.2023.2183938 |
| OpenAlex | W4324369030 |
| Idioma | EN |
| Citações recebidas | 2 |
| Referências citadas | 28 |
This study adapted and validated Barnard’s Online Self-Regulated Learning Questionnaire (OSLQ) to assess adult learners’ (n = 1302) online self-regulation, and examined its relation with attitude towards online learning and perceived online learning satisfaction. It was found that age and employment status were important demographic factors influencing adult learners’ online self-regulation. Specifically, middle- and late-career learners perceived themselves to be more self-regulated than early career learners, and self-employed learners perceived themselves to be more self-regulated than out-of-labour learners. Hierarchical regression analysis showed that online self-regulation contributed to adult learners’ perceived online learning satisfaction over and above attitude towards online learning and demographic variables. This suggests that online self-regulation is an important predictor of adult learners’ online learning satisfaction. Further, within the subscales of online self-regulation, it was found that the more participants set goals and sought help while learning online, the more satisfied they perceived their online learning. Implications for supporting adult learners’ online self-regulation and online learning were discussed
Computer-assisted web interviewing · Medical education · Multilevel model · Multimedia · Online learning · Online participation · Population · Self-regulated learning · The Internet · World Wide Web · Applied Psychology · Computer Science · Innovative Teaching and Learning Methods · Knowledge Management and Sharing · Medicine · Online and Blended Learning · Psychology · Social Psychology
Multivariate data analysis
Self‐regulation and learning strategies
Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses
Assessing Metacognitive Awareness
Measuring self-regulation in online and blended learning environments
Improving Students’ Learning With Effective Learning Techniques
Evaluating bifactor models
User Acceptance of Computer Technology
University students' interaction, Internet self-efficacy, self-regulation and satisfaction with online education during pandemic crises of Covid-19 (Sars-CoV-2)
Facilitating goal setting and planning to enhance online self-regulation of learning
Student learning ecologies in online higher education
Targeting student learning needs
Students’ motivation and engagement in higher education
Development and Preliminary Validation of the Moral Reasoning Questionnaire for Secondary School Students
Assessing Self-Regulation as a Cyclical, Context-Specific Phenomenon
Becoming a Self-Regulated Learner
| Citações por ano | 0,67 |
|---|---|
| Intervalo de citações | 2023 - 2024 (2) |
| Altamente citado | Não |