This research examined the essential factors that significantly impact the perceived learning and continuance intention of M-Learning among art and design major undergraduate students from one private university in Chengdu of China. The factors studied in conceptual framework included self-efficacy, engagement , perceived ease of use, perceived usefulness, satisfaction, perceived learning, as well as continuance intention. This research was the Quantitative methods. It was used to distribute questionnaires to 500 target respondents online, and 476 valid questionnaires were finally recovered. Purposive sampling and quota sampling were used in the sampling procedures. Before the data gathering, the content validity and reliability of questionnaire was tested by Item-Objective Congruence (IOC) and pilot test (n=30). After the data collection, the Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM) was employed to validate the goodness-of-fit of model and confirm hypotheses. This study had been shown to achieve the research objectives and showed that all variables have significant effects in their pairings, with engagement having the greatest impact on perceived learning. Furthermore, PU had the strongest significant impact on CI. For M-Learning designer, they are supposed to pay attention to enhance PU, PEOU, meanwhile raising students’ SA to improve CI of M-Learning. For academic practitioners, attention should be paid to building the classroom atmosphere of M-Learning and creating high-quality online courses, so as to enhance students’ EN and enhance students’ PL are supposed to.

Jingzhi Zhang. Factors Impacting Perceived Learning and Continuation Intention of Art and Design Major Undergraduates Towards M-Learning in Chengdu. Frontiers in Art Research (2023) Vol. 5, Issue 8: 22-27. https://doi.org/10.25236/FAR.2023.050804.

[1] Bandura A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory.  Englewood Cliffs, N.J.: Prentice-Hall. 

[2] Davis F. D., Bagozzi R. P., & Warshaw P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003. https://doi.org/ 10.1287/ mnsc.35.8.982

[3] Oberer B. & Erkollar A. (2013). M-Learning in higher education: a marketing course design project in Austria. Procedia - Social and Behavioral Sciences, 93, 2125-2129.

[4] Li Y., Duan Y., Fu Z. & Alford P. (2012). An empirical study on behavioural intention to reuse e-learning systems in rural china. British Journal of Educational Technology, 43(6), 933-948.