The effect of technical factors on acceptance of using mobile learning: An extended model / Saud Saleh Alghazi

Saud Saleh , Alghazi (2021) The effect of technical factors on acceptance of using mobile learning: An extended model / Saud Saleh Alghazi. PhD thesis, Universiti Malaya.

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Abstract

There is no doubt that mobile devices such as smartphones have become an important tool in the higher education domain. Even though the features and functions of these devices help learners in performing their learning activities, the usage of these devices for learning remains relatively limited amongst students. The low usage of these devices in learning field could be attributed to several reasons relating to technical or non-technical issues. Many acceptance models were developed to measure factors affecting usage of technology, as well as mobile learning. However, limited studies discussed the advantages of the technical aspects, such as device performance, connectivity, processing power, and memory of imparting knowledge through mobile learning. Therefore, there is a need to investigate these limitations of using mobile devices in education to understand the factors that could improve students' usage of these devices for mobile learning in higher education. In order to achieve this outcome, this study aimed to propose a model for measuring the acceptance of mobile learning that emphasises on technical factors to determine the main factors that influence the use of mobile learning by students. New technical factors were proposed, such as Device Compatibility, Device Connectivity, Device Memory Capacities, Device Performance, Device Processing Power, Security and Reliability of Mobile Learning on Device, Network Coverage, and Network Speed. These factors were used to extend The Unified Theory of Acceptance and Use of Technology model for a better understanding of students’ acceptance of mobile learning. Structural equation modelling was employed to analyse data collected from 612 students to verify the validity of the proposed model. The results indicated that factors such as Device Compatibility, Device Connectivity, Device Memory Capacities, Device Performance, Network Coverage and Network Speed have a significant and positive influence on the intention of students to use mobile learning. A guideline is proposed based on the proposed model. This research presents important recommendations for decision-makers and developers on understanding the needs of students in adopting M-learning effectively as a useful learning tool.

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