Higher education appears to be changing in Saudi Arabia, which has made considerable progress in the adoption of more student-centered learning approaches as a reaction to the global pedagogical shift. Saudi Arabia has prioritized instructional technology integration in its educational system. The proliferation and popularity of mobile handheld devices, particularly among young students, will significantly make the future of Mobile learning, or M-learning in higher education bright and promising. However, M-learning in higher education is still in its embryonic stage of implementation, especially in developing countries such as Saudi Arabia; therefore, an in-depth study of each aspect of this issue is necessary. To ensure the success of M-learning in higher education, it is crucial to examine the students' intention to use M-learning as the first step in the process of implementing it into higher education.;A quantitative, non-experimental survey research design and descriptive research were conducted on the determinants---performance expectancy, effort expectancy, and social influence--- that predict undergraduate Saudi students' intention at King Khalid University (KKU) to use M-learning, based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003) as the framework. Data were collected by means of a self-administered online questionnaire. The hypothesized model was validated empirically using data collected from 1,207 undergraduate students at KKU, Saudi Arabia. A multiple linear regression was administered to test the proposed hypothesis. The proposed model was supported and explained up to 52% of the variance in behavioral intention to use M-learning.;The results indicate that performance expectancy, effort expectancy, and social influence were all statistically significant predictors of behavioral intention to use M-learning. Despite the great potential of mobile handheld devices to provide students and institutions with many benefits, such as study aids, accessibility to information, and universal communication, students may be constrained by limited or no internet connectivity, limited screen size, short battery life, and low memory, all of which may dampen student interest in using M-learning. Therefore , these obstacles need to be solved for the betterment of M-learning.This study contributes to the literature on M-learning by identifying determinants that predict student's behavioral intention to adopt and use M-learning and also confirms further Venkatesh et al.'s (2003) UTAUT model as a valid model in studying technology acceptance and use. Based on the results of this study, recommendations were made for instructional practice and future research to implement M-learning for academic purposes.
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