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Influence of mobile devices' scalability on individual perceived learning.
- Source :
- Behaviour & Information Technology; Sep2021, Vol. 40 Issue 11, p1137-1153, 17p, 3 Diagrams, 4 Charts, 2 Graphs
- Publication Year :
- 2021
-
Abstract
- With the increased popularity of mobile learning, there is a growing demand on the understanding of how the scalable technology, such as mobile devices, influences individual learning behaviours as well as their learning outcome. A theoretical model was built based on the adaptive structuration theory (AST) and the knowledge spiral theory. Using this model, we examined the relationship between structural sources, individuals' adaptive structural behaviours, and their perceived learning. A Structural Equation Modeling method was employed in our empirical study. Findings indicate that users' task adaptation had a positive influence on their perceived learning, In addition, their exploitive technology adaptation influenced the ultimate perceived learning, but the impact of users' exploratory technology adaptation on learning was mediated by their task adaptation. Contrary to expectations, the effect of computer self-efficacy on exploitive and exploratory technology adaptation was negative, and exploratory technology adaptation negatively affected exploitive task adaptation. A detailed discussion of the findings and implications are provided in this paper. [ABSTRACT FROM AUTHOR]
- Subjects :
- ONLINE education
STRUCTURAL equation modeling
RESEARCH
RELATIVE medical risk
LEARNING theories in education
RESEARCH evaluation
MATHEMATICAL models
SMARTPHONES
LEARNING strategies
SELF-efficacy
ACADEMIC achievement
CONCEPTUAL structures
THEORY
INTELLECT
DESCRIPTIVE statistics
QUESTIONNAIRES
SCALE analysis (Psychology)
RESEARCH funding
EMPIRICAL research
DATA analysis software
PATH analysis (Statistics)
STATISTICAL correlation
EDUCATIONAL outcomes
Subjects
Details
- Language :
- English
- ISSN :
- 0144929X
- Volume :
- 40
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- Behaviour & Information Technology
- Publication Type :
- Academic Journal
- Accession number :
- 152741287
- Full Text :
- https://doi.org/10.1080/0144929X.2020.1742789