An Investigation into Smartphone Use of Undergraduate Students in the Academic Environment and Its Predictors

Mobile phones have become essential learning tools with their extensive features and functionalities, contributing to the emergence of mobile learning. These devices enable communication and collaboration both inside and outside the classrooms while also aiding in information seeking, collection, and content generation. Yet, the use of mobile phones in education is met with varying opinions; while some view them as potentially distracting, others see them as facilitators of learning environments. Personal traits, such as previous knowledge, motivation, and needs, significantly influence the educational use of mobile phones. Consequently, this study aimed to investigate undergraduate students’ educational mobile phone use and explore the effect of certain learner characteristics (demographic characteristics, technology-use-related characteristics, the motives for mobile phone use, self-directed learning, and self-efficacy beliefs) on mobile phone use in an academic environment (MPUAE). The participants consisted of 1928 students from all departments of Middle East Technical University, which were selected by stratified sampling method. The results showed that students used their mobile phones primarily for communication and interaction, and then for getting/searching for information. To predict the contribution of the personal factors on the total MPUAE scores, a hierarchical regression analysis was performed. The findings revealed that personal factors, except self-directed learning, significantly predicted students’ total MPUAE scores, which explained 32% of the variance in educational mobile phone use. Specifically, the motives of mobile phone use and self-efficacy beliefs were the most notable predictors based on the analysis.
Technology, Knowledge and Learning
Citation Formats
N. Yasan-Ak and İ. S. Yıldırım, “An Investigation into Smartphone Use of Undergraduate Students in the Academic Environment and Its Predictors,” Technology, Knowledge and Learning, pp. 0–0, 2024, Accessed: 00, 2024. [Online]. Available: