Access Type

Open Access Dissertation

Date of Award

January 2017

Degree Type


Degree Name



Instructional Technology

First Advisor

Ke Zhang


The rapid development of technology has encouraged Saudi universities to establish initiatives to improve learning. Mobile learning technology is one of the technologies targeted by eLearning and distance education deanships among Saudi universities. However, few studies have been done in investigating mobile learning technology acceptance in the Saudi context. This study aims to provide policy and decision makers in the Saudi higher education with reliable data in order to employ mobile learning technology in learning process. Therefore, this study modified Unified Theory of Acceptance and Use of Technology (UTAUT) to investigate students’ acceptance of mobile learning technology. To this end, seven questions were proposed to explore the effect of learning expectancy, effort expectancy, social influence, facilitating conditions, mobile learning technology characteristics, and self-management of learning on students’ behavioral intentions and use behaviors of mobile learning technology. In addition, age, gender, and eLearning experience were proposed to moderate such an effect. This study employed sequential mixed method to procced the exploration. A questionnaire and semi-structured interview were developed to collect the data. 1203 participants were included in the quantitative data collection while fifteen participants were included in the qualitative data collection. Multiple regression analyses were used in the quantitative analysis and thematic analysis was used in the qualitative analysis.

The results of this study assert that learning expectancy, effort expectancy, social influence, and mobile learning characteristics are significant predictors of students’ intentions to use mobile learning technology regardless the moderating effects of gender, age, and eLearning experience. Unexpectedly, the social influence construct is the only construct that was moderated by gender where men show a stronger behavioral intention to use mobile learning than women. Facilitating conditions and self-management of learning in this study were found insignificant constructs in predicting students’ behavioral intention and use behavior of mobile learning technology. These findings are justified in the literature of UTAUT. The exploratory analysis revealed an interesting finding that distance education students showed significantly higher intentions to use mobile learning technology than on-campus students, but there was no significant difference between them in the actual use of mobile learning technology.