The effect of extended UTAUT model on EFLs’ adaptation to flipped classroom (original) (raw)
References
Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665–683. Article Google Scholar
Almaiah, M. A., Alamri, M. M., & Al-Rahmi, W. (2019). Applying the UTAUT model to explain the students’ acceptance of mobile learning system in higher education. IEEE Access, 7, 174673–174686. Article Google Scholar
Almodaires, A. A., Alayyar, G. M., Almsaud, T. O., & Almutairi, F. M. (2019). The effectiveness of flipped learning: A quasi-experimental study of the perceptions of Kuwaiti pre-service teachers. International Education Studies, 12(1), 10–23. Article Google Scholar
Alzahrani, L., Al-Karaghouli, W., & Weerakkody, V. (2018). Investigating the impact of citizens’ trust toward the successful adoption of e-government: A multigroup analysis of gender, age, and internet experience. Information Systems Management, 35(2), 124–146. Article Google Scholar
Ameen, N., Willis, R., Abdullah, M. N., & Shah, M. (2019). Towards the successful integration of e-learning systems in higher education in Iraq: A student perspective. British Journal of Educational Technology, 50(3), 1434–1446. Article Google Scholar
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. Article Google Scholar
Aprianto, E., & Purwati, O. (2020). Multimedia-assisted learning in a flipped classroom: A case study of autonomous learning on EFL University students. International Journal of Emerging Technologies in Learning (iJET), 15(24), 114–127. Article Google Scholar
Badri, M., Al Nuaimi, A., Guang, Y., & Al Rashedi, A. (2017). School performance, social networking effects, and learning of school children: Evidence of reciprocal relationships in Abu Dhabi. Telematics and Informatics, 34(8), 1433–1444. Article Google Scholar
Basal, A. (2015). The implementation of a flipped classroom in foreign language teaching. Turkish Online Journal of Distance Education, 16(4), 28–37. Google Scholar
Bhimasta, R. A., & Suprapto, B. (2016). An empirical investigation of student adoption model toward mobile e-textbook: UTAUT2 and TTF model. In proceedings of the 2nd international conference on communication and information processing (pp. 167-173).
Bond, M. (2019). Flipped learning and parent engagement in secondary schools: A south Australian case study. British Journal of Educational Technology, 50(3), 1294–1319. Article Google Scholar
Cant, R. P., & Cooper, S. J. (2017). Use of simulation-based learning in undergraduate nurse education: An umbrella systematic review. Nurse Education Today, 49, 63–71. Article Google Scholar
Castro, M., Expósito-Casas, E., López-Martín, E., Lizasoain, L., Navarro-Asencio, E., & Gaviria, J. L. (2015). Parental involvement on student academic achievement: A meta-analysis. Educational Research Review, 14, 33–46. Article Google Scholar
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336. Google Scholar
Chua, P. Y., Rezaei, S., Gu, M. L., Oh, Y., & Jambulingam, M. (2018). Elucidating social networking apps decisions: Performance expectancy, effort expectancy and social influence. Nankai Business Review International, Elucidating social networking apps decisions.
Deng, X., Doll, W. J., & Truong, D. (2004). Computer self-efficacy in an ongoing use context. Behaviour and Information Technology, 23(6), 395–412. Article Google Scholar
Duderstadt, J., Atkins, D., & Houweling, D. (2002). Higher education in the digital age: Technology issues and strategies for American colleges and universities. Praeger.
El-Masri, M., & Tarhini, A. (2017). Factors affecting the adoption of e-learning systems in Qatar and USA: Extending the unified theory of acceptance and use of technology 2 (UTAUT2). Educational Technology Research and Development, 65(3), 743–763. Article Google Scholar
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39–50.
Gautam, V., Khandelwal, S., & Dwivedi, R. (2020). The impact of self-efficacy and need for achievement on management Students' perceptions regarding web based learning resources. International Journal of Education and Development using Information and Communication Technology, 16(2), 68–83. Google Scholar
Grolnick, W. S., & Slowiaczek, M. L. (1994). Parents' involvement in children's schooling: A multidimensional conceptualization and motivational model. Child Development, 65(1), 237–252. Article Google Scholar
Hair, J. F., Anderson, R. E., Babin, B. J., & Black, W. C. (2010). Multivariate data analysis: A global perspective (Vol. 7).
Hill, N. E., & Taylor, L. C. (2004). Parental school involvement and children's academic achievement: Pragmatics and issues. Current Directions in Psychological Science, 13(4), 161–164. Article Google Scholar
Hill, N. E., Witherspoon, D. P., & Bartz, D. (2018). Parental involvement in education during middle school: Perspectives of ethnically diverse parents, teachers, and students. The Journal of Educational Research, 111(1), 12–27. Article Google Scholar
Holden, H., & Rada, R. (2011). Understanding the influence of perceived usability and technology self-efficacy on teachers’ technology acceptance. Journal of Research on Technology in Education, 43(4), 343–367. Article Google Scholar
Hsieh, J. S. C., Huang, Y. M., & Wu, W. C. V. (2017). Technological acceptance of LINE in flipped EFL oral training. Computers in Human Behavior, 70, 178–190. Article Google Scholar
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1–55.
Huang, Y. N., & Hong, Z. R. (2016). The effects of a flipped English classroom intervention on students’ information and communication technology and English reading comprehension. Educational Technology Research and Development, 64(2), 175–193. ArticleMathSciNet Google Scholar
Ifinedo, P. (2017). Examining students' intention to continue using blogs for learning: Perspectives from technology acceptance, motivational, and social-cognitive frameworks. Computers in Human Behavior, 72, 189–199. Article Google Scholar
Joo, Y. J., Park, S., & Lim, E. (2018a). Factors influencing preservice teachers’ intention to use technology: TPACK, teacher self-efficacy, and technology acceptance model. Journal of Educational Technology & Society, 21(3), 48–59. Google Scholar
Joo, Y. J., So, H. J., & Kim, N. H. (2018b). Examination of relationships among students' self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs. Computers & Education, 122, 260–272. Article Google Scholar
Kim, M. K., Kim, S. M., Khera, O., & Getman, J. (2014). The experience of three flipped classrooms in an urban university: An exploration of design principles. Internet and Higher Education, 22, 37e50. Article Google Scholar
Kissi, P. S., Nat, M., & Armah, R. B. (2018). The effects of learning–family conflict, perceived control over time and task-fit technology factors on urban–rural high school students’ acceptance of video-based instruction in flipped learning approach. Educational Technology Research and Development, 66(6), 1547–1569. Article Google Scholar
Kong, S. (2015). A pedagogical framework for content-language integrated teaching at middle school level. Journal of Asia TEFL, 12(4).
Kurfalı, M., Arifoğlu, A., Tokdemir, G., & Paçin, Y. (2017). Adoption of e-government services in Turkey. Computers in Human Behavior, 66, 168–178. Article Google Scholar
Lai, C. L., & Hwang, G. J. (2016). A self-regulated flipped classroom approach to improving students’ learning performance in a mathematics course. Computers & Education, 100, 126–140. Article Google Scholar
Lakhal, S., & Khechine, H. (2016). Student intention to use desktop web-conferencing according to course delivery modes in higher education. The International Journal of Management Education, 14(2), 146–160. Article Google Scholar
Lakhal, S., Khechine, H., & Pascot, D. (2013). Student behavioural intentions to use desktop video conferencing in a distance course: Integration of autonomy to the UTAUT model. Journal of Computing in Higher Education, 25(2), 93–121. Article Google Scholar
Le Roux, I., & Nagel, L. (2018). Seeking the best blend for deep learning in a flipped classroom–viewing student perceptions through the Community of Inquiry lens. International Journal of Educational Technology in Higher Education, 15(1), 1–28. Google Scholar
Lee, D. Y., & Lehto, M. R. (2013). User acceptance of YouTube for procedural learning: An extension of the technology acceptance model. Computers & Education, 61, 193–208. Article Google Scholar
Lei, M., & Lomax, R. G. (2005). The effect of varying degrees of nonnormality in structural equation modeling. Structural Equation Modeling, 12(1), 1–27. ArticleMathSciNet Google Scholar
Li, Y. Z., He, T. L., Song, Y. R., Yang, Z., & Zhou, R. T. (2018). Factors impacting donors’ intention to donate to charitable crowd-funding projects in China: A UTAUT-based model. Information, Communication & Society, 21(3), 404–415. Article Google Scholar
Liao, C., Palvia, P., & Chen, J. L. (2009). Information technology adoption behavior life cycle: Toward a technology continuance theory (TCT). International Journal of Information Management, 29(4), 309–320. Article Google Scholar
Liew, B. T., Kang, M., Yoo, E., & You, J. (2013). Investigating the determinants of mobile learning acceptance in Korea. In EdMedia+ innovate learning (pp. 1424-1430). Association for the Advancement of computing in education (AACE).
Lim, C. K. (2001). Computer self-efficacy, academic self-concept, and other predictors of satisfaction and future participation of adult distance learners. American Journal of Distance Education, 15(2), 41–51. Article Google Scholar
Lo, C. K., & Hew, K. F. (2017). A critical review of flipped classroom challenges in K-12 education: Possible solutions and recommendations for future research. Research and Practice in Technology Enhanced Learning, 12(1), 4. Article Google Scholar
Long, T., Cummins, J., & Waugh, M. (2019). Investigating the factors that influence higher education instructors’ decisions to adopt a flipped classroom instructional model. British Journal of Educational Technology, 50(4), 2028–2039. Article Google Scholar
Ma, Q., & Liu, L. (2004). The technology acceptance model: A meta-analysis of empirical findings. Journal of Organizational and End User Computing (JOEUC), 16(1), 59–72. Article Google Scholar
Maduku, D. K. (2017). Understanding E-book continuance intention: Empirical evidence from E-book users in a developing country. Cyberpsychology, Behavior and Social Networking, 20(1), 30–36. Article Google Scholar
Mikalef, P., Pappas, I. O., & Giannakos, M. (2016). An integrative adoption model of video-based learning. The International Journal of Information and Learning Technology.
Moghavvemi, S., & Salarzadeh Janatabadi, H. (2018). Incremental impact of time on students' use of E-learning via Facebook. British Journal of Educational Technology, 49(3), 560–573. Article Google Scholar
Mohamed, H., & Lamia, M. (2018). Implementing flipped classroom that used an intelligent tutoring system into learning process. Computers & Education, 124, 62–76. Article Google Scholar
Nurrohmah, I., Dewi, M. A. A., & Sahadi, N. (2017). Measuring the e-government maturity in Indonesia using the ranking of e-government of Indonesia (PeGI). American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS), 32(1), 49–63. Google Scholar
Olasina, G. (2019). Human and social factors affecting the decision of students to accept e-learning. Interactive Learning Environments, 27(3), 363–376. Article Google Scholar
Oluwajana, D., Nat, M., & Fadiya, S. (2019). An investigation of students’ interactivity in the classroom and within learning management system to improve learning outcomes. Croatian Journal of Education: Hrvatski časopis za odgoj i obrazovanje, 21(1), 77–102. Article Google Scholar
Rakic, S., Pavlovic, M., Softic, S., Lalic, B., & Marjanovic, U. (2019). An evaluation of student performance at e-learning platform. In 2019 17th international conference on emerging eLearning technologies and applications (ICETA) (pp. 681-686). IEEE.
Roach, T. (2014). Student perceptions toward flipped learning: New methods to increase interaction and active learning in economics. International review of economics education, 17, 74–84. Article Google Scholar
Sergis, S., Sampson, D. G., & Pelliccione, L. (2018). Investigating the impact of Flipped Classroom on students' learning experiences: A Self-Determination Theory approach. Computers in Human Behavior, 78, 368–378.
Sidik, D., & Syafar, F. (2020). Exploring the factors influencing student’s intention to use mobile learning in Indonesia higher education. Education and Information Technologies, 25(6), 4781–4796. Article Google Scholar
Soliman, N. A. (2016). Teaching English for academic purposes via the flipped learning approach. Procedia-Social and Behavioral Sciences, 232, 122–129. Article Google Scholar
Suki, N. M., & Suki, N. M. (2017). Determining students’ behavioural intention to use animation and storytelling applying the UTAUT model: The moderating roles of gender and experience level. The International Journal of Management Education, 15(3), 528–538. Article Google Scholar
Šumak, B., & Šorgo, A. (2016). The acceptance and use of interactive whiteboards among teachers: Differences in UTAUT determinants between pre-and post-adopters. Computers in Human Behavior, 64, 602–620. Article Google Scholar
Sung, H. N., Jeong, D., Jeong, Y. S., & Shin, J. I. (2015). The relationship among self-efficacy, social influence, performance expectancy, effort expectancy, and behavioral intention in mobile learning service. International Journal of u-and e-Service, Science and Technology, 8(9), 197–206. Article Google Scholar
Tan, P. J. B. (2013). Applying the UTAUT to understand factors affecting the use of English e-learning websites in Taiwan. SAGE Open, 3(4), 2158244013503837. Article Google Scholar
Tarhini, A., Masa’deh, R. E., Al-Busaidi, K. A., Mohammed, A. B., & Maqableh, M. (2017). Factors influencing students’ adoption of e-learning: A structural equation modeling approach. Journal of International Education in Business, 10(2), 164–182. Article Google Scholar
Venkatesh, V (2000). Determinants of perceived ease of use: Integrating control, intrinsic mo- tivation, and emotion into the technology acceptance model. Information Systems Research, 11, 4 (2000), 342–36.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Wang, M. T., & Sheikh-Khalil, S. (2014). Does parental involvement matter for student achievement and mental health in high school? Child Development, 85(2), 610–625. Article Google Scholar
Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221–232. Article Google Scholar
Yamane, T. (1967). Statistics: An introductory analysis (no. HA29 Y2 1967).
Yamarik, S. (2019). Flipping the classroom and student learning outcomes: Evidence from an international economics course. International review of economics education, 100163.
Yang, H. H., Feng, L., & MacLeod, J. (2019). Understanding college students’ acceptance of cloud classrooms in flipped instruction: Integrating UTAUT and connected classroom climate. Journal of Educational Computing Research, 56(8), 1258–1276. Article Google Scholar
Yeap, J. A., Ramayah, T., & Soto-Acosta, P. (2016). Factors propelling the adoption of m-learning among students in higher education. Electronic Markets, 26(4), 323–338. Article Google Scholar