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Effectiveness of avatars representing teachers in M-learning in Saudi Arabia higher education

Alowayr, A. S. (2018) Effectiveness of avatars representing teachers in M-learning in Saudi Arabia higher education. PhD thesis, University of Reading

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To link to this item DOI: 10.48683/1926.00079819


The aim of this research has been to investigate how m-learning can be used to complement traditional learning environments in Higher Education in Saudi Arabia. Specific attention has been paid to how engagement and performance in learning can be influenced by the type of avatar representation of the teacher on the mobile device, which might be in the form of video, audio, image, cartoon or simple text. This study enhances the field of knowledge related to m-learning via three main contributions which are described and developed as the thesis progresses. Firstly, the research develops, as an extension to the traditional technology acceptance model (TAM), an educational model, MADE-ME (Multi Avatar Delivery Environment for Mobile Education). This model defines how students can interact with different avatar representations of the teacher to deliver learning content. The model shows the relationships between factors such as engagement, interactive elements, gender, major of study, pedagogical performance, etc. Secondly the research produces a framework MADE-ME (Multi Avatar Delivery Environment for Mobile Education) web-app that enables a range of avatars to represent the teacher in their purpose of delivering interactive learning content via mobile technologies, and which allows students to be tested on how much they have learnt from the content or lesson. Thirdly, a comprehensive case study is undertaken with student groups studying on a compulsory English language module as part of their higher education in Saudi Arabia to determine how they engaged with the mobile content and how effective their learning was to evaluate and to validate the MADE-ME model and app. The data was collected by a mixed methods approach and used REGRESSION and UNIANOVA techniques for analysing the quantitative data from questionnaires, and a thematic approach for analysing qualitative data from open-ended questions. The thesis concludes with recommendations for implementing m-learning in Saudi higher education, limitations of the current study and suggestions for further research.

Item Type:Thesis (PhD)
Thesis Supervisor:McCrindle, R.
Thesis/Report Department:School of Mathematical, Physical and Computational Sciences
Identification Number/DOI:
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:79819
Date on Title Page:2017


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