Typology and Hierarchy of Students’ Motivations to Use Technology in Learning
DOI:
https://doi.org/10.3127/ajis.v22i0.1492Keywords:
digital technology enabled learning, motivations, digital natives, typology, hierarchical framework.Abstract
Considerable discussion has taken place in practice and academe regarding the need for changes to the educational system to better suit current student’s approaches and preferences for technology use in learning. Much of this discussion involves assumptions about the current students (referred to by some as ‘digital natives’) preference for independent learning and that students are motivated in similar ways to use technology to achieve and support their preferred learning style. This study sought to better understand student’s motivations for technology use in learning and whether assumptions about the homogeneity of motivations are warranted. We sought to identify students’ motivation typology and any groupings within these typologies, and understand the inter-relationship between motivations. Using data collected from 16 Information Systems (IS) students via the Repertory Grid Interview technique (RGT), a cluster analysis segmented respondents into two distinct groups: ‘Independent Learners’ and ‘Traditional Learners’. A hierarchical framework of technology use motivations was developed for each group using Interpretive Structural Modelling (ISM) and Cross-impact Matrix Multiplication Applied to Classification (MICMAC) was used to categorise each group’s motivation factors. Results show that the two groups were driven to achieve the same learning goals by different paths and hence questioning the assumption of homogeneity in technology use motivations among the current student cohort.Downloads
Published
2018-03-15
How to Cite
Stevens, K. J., Guo, Z., & Li, Y. (2018). Typology and Hierarchy of Students’ Motivations to Use Technology in Learning. Australasian Journal of Information Systems, 22. https://doi.org/10.3127/ajis.v22i0.1492
Issue
Section
Research on Educational Technologies
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