Influence of mobile devices’ scalability on individual perceived learning

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.

KEYWORDS:

• Individual learning
• scalable technology
• adaptive structuration theory
• mobile learning

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 In our official questionnaire, we asked ‘do you have your own mobile device’ and ‘have you ever had mobile learning experience’. If respondents choose ‘no’, the questionnaire will be closed directly. We use this method to identify situation (1) and (2). WenJuanXing provides filtering services that can filter responses from the same IP address or answer times shorter than the set number of seconds. This allows us to identify situation (3) and (4).

Additional information

Funding

The research reported in this paper has received funding from the National Natural Science Foundation of China: Research on Multi-source Heterogeneous Online Product Review DataFusion and Knowledge Discovery Based on Graph Model [grant number 71974075], awarded to He Li, Jilin University, Changchun, and Partners.