The Impact of College Students’ Intrinsic and Extrinsic Motivation on Continuance Intention to Use English Mobile Learning Systems

Article Details

Chi-Cheng Chang, Chaoyun Liang, Chi-Fang Yan,, nan, Department of Technology Application & Human Resource Development, National Taiwan Normal University, Taipei, Taiwan
Ju-Shih Tseng, , Department of Technology Application & Human Resource Development, National Taiwan Normal University, Taipei, Taiwan

Journal: The Asia-Pacific Education Researcher
Volume 22 Issue 2 (Published: 2013-05-01)

Abstract

Mobile learning, with its features of ubiquitousness and flexibility, enables users to learn in any appropriate place and at any appropriate time. This emerging way of digital learning will be the future trend. Therefore, the technology acceptance model (TAM) proposed by Davis was extended with extrinsic motivation, perceived convenience, and intrinsic motivation, perceived playfulness, for examining the factors that affect continuance intention to use the English mobile learning system (EMLS) and the relationships among these factors. Participating in the study were 158 technical college students from the middle part of Taiwan who were studying English via EMLS using PDAs for 4 weeks. Data were collected by questionnaires and were analyzed by SmartPLS as an SEM analysis tool. The results revealed that perceived convenience, perceived playfulness, perceived ease of use, and perceived usefulness were antecedent factors that affected continuance intention to use the EMLS. Perceived usefulness had a greater impact on continuance intention than perceived playfulness. Overall, the extended TAM in the present study was effective at predicting and explaining the continuance intention to use the EMLS.

Keywords: Self-determination theory Perceived convenience Perceived playfulness Mobile learning Technology acceptance model

DOI: https://link.springer.com/article/10.1007/s40299-012-0011-7
  References:

Ahn, T., Ryu, S., & Han, I. (2007). The impact of Web quality and playfulness on user acceptance of online retailing. Information and Management, 44(3), 263–275.

Annear, K. D., & Yates, G. C. R. (2010). Restrictive and supportive parenting: Effects on children’s school affect and emotional responses. Australian Educational Researcher, 37(1), 63–82.

Berry, L. L., Seiders, K., & Grewal, D. (2002). Understanding service convenience. Journal of Marketing, 66(3), 1–17.

Burton-Jones, A., & Hubona, G. S. (2006). The mediation of external variables in the technology acceptance model. Information and Management, 43(6), 706–717.

Chen, C.-M., & Chung, C.-J. (2008). Personalized mobile English vocabulary learning system based on item response theory and learning memory cycle. Computers and Education, 51(2), 624–645.

Chinnery, G. M. (2006). Emerging technologies going to the MALL: Mobile assisted language learning. Language Learning and Technology, 10(1), 9–16.

Chiu, C. M., & Wang, T. G. (2008). Understanding Web-based learning continuance intention: The role of subjective task value. Information and Management, 45(3), 194–201.

Chung, J., & Tan, F. B. (2004). Antecedents of perceived playfulness: An exploratory study on user acceptance of general information-searching websites. Information and Management, 41(7), 869–881.

Churchill, D., & Churchill, N. (2008). Educational affordances of PDAs: A study of a teacher’s exploration of this technology. Computers and Education, 50(4), 1439–1450.

Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco: Jossey Bass.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of Information technology. MIS Quarterly, 13(3), 319–340.

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.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111–1132.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

Gagné, M., & Deci, E. L. (2005). Self-determination theory and work motivation. Journal of Organizational Behavior, 26(4), 331–362.

Gupta, S., & Kim, H.-W. (2007). The moderating effect of transaction experience on the decision calculus in on-line repurchase. International Journal of Electronic Commerce, 12(1), 127–158.

Hossain, M. M., & Prybutok, V. R. (2008). Consumer acceptance of RFID technology: An exploratory study. IEEE Transactions on Engineering Management, 55(2), 316–328.

Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195–204.

Kuo, Y.-F., & Yen, S.-N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computers in Human Behavior, 25(1), 103–110.

Lee, M. C. (2010). Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–Confirmation model. Computers and Education, 54(2), 506–516.

Lee, M. K. O., Cheung, C. M. K., & Chen, Z. (2007). Understanding user acceptance of multimedia messaging services: An empirical study. Journal of the American Society for Information Science and Technology, 58(13), 2066–2077.

Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40(3), 191–204.

Lin, K. M. (2011). e-Learning continuance intention: Moderating effects of user e-learning experience. Computers and Education, 56(2), 515–526.

Lin, C. S., Wu, S., & Tsai, R. J. (2005). Integrating perceived playfulness into expectation-confirmation models for web portal context. Information and Management, 42(5), 683–693.

Moon, J.-W., & Kim, Y.-G. (2001). Extending the TAM for a World-Wide-Web context. Information and Management, 38(4), 217–230.

Ong, C.-S., & Lai, J.-Y. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816–829.

Park, S. Y., Nam, M. W., & Cha, S. B. (2011). University students` behavioral intention to use mobile learning: Evaluating the technology acceptance model. British Journal of Educational Technology. doi:10.1111/j.1467-8535.2011.01229.x.

Peng, H., Su, Y.-J., Chou, C., & Tsai, C.-C. (2009). Ubiquitous knowledge construction: Mobile learning re-defined and a conceptual framework. Innovations in Education and Teaching International, 46(2), 171–183.

Ringle, C. M., Wende, S., & Will, S. (2005). SmartPLS 2.0 (M3) Beta, Hamburg, http://www.smartpls.de.

Roca, J. C., & Gagné, M. (2008). Understanding e-learning continuance intention in the workplace: A self-determination theory perspective. Computers in Human Behavior, 24(4), 1585–1604.

Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67.

Saade, R. G., & Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: An extension of the technology acceptance model. Information and Management, 42, 317–327.

Shang, R.-A., Chen, Y.-C., & Shen, L. (2005). Extrinsic versus intrinsic motivations for consumers to shop on-line. Information and Management, 42(3), 401–413.

Shih, J.-L., Chuang, C.-W., & Hwang, G.-J. (2010). An inquiry-based mobile learning approach toe Enhancing social science learning effectiveness. Journal of Educational Technology and Society, 13(4), 50–62.

Shin, D.-H. (2007). User acceptance of mobile Internet: Implication for convergence technologies. Interacting with Computers, 19(4), 472–483.

Thornton, P., & Houser, C. (2005). Using mobile phones in English education in Japan. Journal of Computer Assisted Learning, 21(3), 217–228.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.

Walton, G., Childs, S., & Blenkinsopp, E. (2005). Using mobile technologies to give health students access to learning resources in the UK community setting. Health Information and Libraries Journal, 22(Suppl 2), 51–65.

Wang, Y.-S., Wu, M.-C., & Wang, H.-Y. (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology, 40(1), 92–118.

Webster, J., & Martocchio, J. J. (1992). Microcomputer playfulness: Development of a measure with workplace implications. MIS Quarterly, 16(2), 201–226.

Yeung, P., & Jordan, E. (2007). The continued usage of business e-learning courses in Hong Kong corporations. Education and Information Technologies, 12(3), 175–188.

Yoon, C., & Kim, S. (2007). Convenience and TAM in a ubiquitous computing environment: The case of wireless LAN. Electronic Commerce Research and Applications, 6(1), 102–112.

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