The Intention of Generation Z to Use Mobile Learning: The Role of Self-Efficacy and Enjoyment
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| Title: | The Intention of Generation Z to Use Mobile Learning: The Role of Self-Efficacy and Enjoyment |
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| Language: | English |
| Authors: | Azmi Fitriati (ORCID |
| Source: | Turkish Online Journal of Distance Education. 2025 26(1):85-100. |
| Availability: | Anadolu University. Office of the Rector, Eskisehir, 26470, Turkey. Tel: +90-222-335-34-53; Fax: +90-222-335-34-86; e-mail: rektor@anadolu.edu.tr; e-mail: TOJDE@anadolu.edu.tr; Web site: http://tojde.anadolu.edu.tr/ |
| Peer Reviewed: | Y |
| Page Count: | 16 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Foreign Countries, College Students, Young Adults, Self Efficacy, Handheld Devices, Electronic Learning, Student Attitudes, Influence of Technology, Technology Uses in Education, Educational Technology, Emotional Experience |
| Geographic Terms: | Indonesia |
| ISSN: | 1302-6488 |
| Abstract: | The Technology Acceptance Model (TAM) is a concise and efficient predictive model used to explain the acceptance of m-learning technology. However, several studies have shown that TAM cannot fully explain the acceptance of m-learning among Generation Z. This study aims to formulate TAM as a model of m-learning acceptance for Generation Z. TAM developed based on self-efficacy and enjoyment is expected to explain the behavior of Generation Z in accepting m-learning. This study uses a survey approach, utilizing PLS-SEM as an analysis tool and primary data collected through questionnaires. Participants in this study were 563 students who used m-learning (on class application) at the Muhammadiyah University of Purwokerto, Indonesia. The results contribute to the formulation of a successful m-learning implementation model for Generation Z. These results provide empirical support indicating that self-efficacy and perceived enjoyment cause them to use m-learning now and in the future. Generation Z, who grew up in the digital era, has a high level of proficiency in using technology. Self-efficacy increases user optimism. They are confident in their ability to complete tasks and solve problems when using m-learning. Enjoyment can increase the belief that m-learning is user-friendly and useful. The results of this study support the theory of self-efficacy which states that user beliefs serve as the best predictors of their behavior in using technology in mobile learning. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1458632 |
| Database: | ERIC |
| Abstract: | The Technology Acceptance Model (TAM) is a concise and efficient predictive model used to explain the acceptance of m-learning technology. However, several studies have shown that TAM cannot fully explain the acceptance of m-learning among Generation Z. This study aims to formulate TAM as a model of m-learning acceptance for Generation Z. TAM developed based on self-efficacy and enjoyment is expected to explain the behavior of Generation Z in accepting m-learning. This study uses a survey approach, utilizing PLS-SEM as an analysis tool and primary data collected through questionnaires. Participants in this study were 563 students who used m-learning (on class application) at the Muhammadiyah University of Purwokerto, Indonesia. The results contribute to the formulation of a successful m-learning implementation model for Generation Z. These results provide empirical support indicating that self-efficacy and perceived enjoyment cause them to use m-learning now and in the future. Generation Z, who grew up in the digital era, has a high level of proficiency in using technology. Self-efficacy increases user optimism. They are confident in their ability to complete tasks and solve problems when using m-learning. Enjoyment can increase the belief that m-learning is user-friendly and useful. The results of this study support the theory of self-efficacy which states that user beliefs serve as the best predictors of their behavior in using technology in mobile learning. |
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| ISSN: | 1302-6488 |
