DETERMINANTS OF TECHNOLOGY-ASSISTED LEARNING METHODS IN HIGHER EDUCATION ESTABLISHMENTS
DOI:
https://doi.org/10.46991/AFA/2025.21.2.88Keywords:
Behavior Intention, Actual Use , Digital Divide, Artificial Intelligence, Technology-Assisted LearningAbstract
The motivation behind this study is the emergence of technological tools that are rapidly transforming teaching and learning from passive knowledge acquisition confined to physical classrooms to active knowledge construction in the increasing virtual spaces. Despite the need to accelerate the digitization of learning, some institutions have demonstrated low uptake of technologically-assisted learning due to various factors, hence prompting a review study on the determinants of Technology-Assisted Learning Methods (TALM). For understanding, a qualitative research methodology has been employed involving the study of previously published research retrieved from Google Scholar, ERIC, and ScienceDirect databases and findings analyzed qualitatively alongside an in-depth exploration of the Unified Theory of Acceptance and Use of Technology (UTAUT). The findings reveal a positive influence of facilitating conditions, hedonic motivation, social influence, habit, performance expectancy and effort expectancy on behavior intention to adopt technology. Similarly, course assessment, course design and instructor characteristics have a strong relationship with actual use. The findings of this study will inform educators, university management boards and policy makers on the considerations before integrating technology types in learning programs. This work suggests further investigation of the determinants based on a country’s level of development.
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