How to cite this paper
Alshurideh, M., Abuanzeh, A., Kurdi, B., Akour, I & AlHamad, A. (2023). The effect of teaching methods on university students’ intention to use online learning: Technology Acceptance Model (TAM) validation and testing.International Journal of Data and Network Science, 7(1), 235-250.
Refrences
Abdekhoda, M., Ahmadi, M., Dehnad, A., Noruzi, A., & Gohari, M. (2016b). Applying electronic medical records in health care: physicians’ perspective”, Applied Clinical Informatics, 7(2), 341.
Afthanorhan, A., Awang, Z., & Aimran, N. (2020). An extensive comparison of CB-SEM and PLS-SEM for reliability and validity. International Journal of Data and Network Science, 4(4), 357–364.
Al-Fraihat, D., Joy, M., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in human behavior, 102, 67-86.
Al Jarrah, A., Thomas, M.K., & Shehab, M. (2018). Investigating temporal access in a flipped classroom: procrastination persists. International Journal of Educational Technology in Higher Education, 15(1), 1.
Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2016). Determinants of perceived usefulness of e-learning sys-tems. Computers in Human Behavior, 64, 843-858.
Atas, M. (2015). The reduction of speaking anxiety in EFL learners through drama techniques. Procedia - Social and Be-havioral Sciences, 176, 961–969.
Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 244–254.
Bakhsh, S. A. (2016). Using Games as a Tool in Teaching Vocabulary to Young Learners. English language teach-ing, 9(7), 120-128.
Buzzard, C., Crittenden, V. L., Crittenden, W. F., & McCarty, P. (2011). The use of digital technologies in the classroom: A teaching and learning perspective. Journal of Marketing Education, 33(2), 131-139.
Chen, C. P., Lai, H. M., & Ho, C. Y. (2015). Why do teachers continue to use teaching blogs? The roles of perceived vol-untariness and habit. Computers & Education, 82, 236-249.
Chen, Y. H., & Keng, C. J. (2018). Utilizing the Push-Pull-Mooring-Habit framework to explore users’ intention to switch from offline to online real-person English learning platform. Internet Research. 29, 167–193.
Cheng, S., Lee, S. J., & Choi, B. (2019). An empirical investigation of users’ voluntary switching intention for mobile per-sonal cloud storage services based on the push-pull-mooring framework. Computers in Human Behavior, 92, 198-215.
Dolmans, D. H., Loyens, S. M., Marcq, H., & Gijbels, D. (2016). Deep and surface learning in problem-based learning: a review of the literature. Advances in health sciences education, 21(5), 1087-1112.
Etikan, I., & Bala, K. (2017). Sampling and sampling methods. Biometrics & Biostatistics International Journal, 5(6), 149.
Fagan, M., Kilmon, C., & Pandey, V. (2012). Exploring the adoption of a virtual reality simulation: The role of perceived ease of use, perceived usefulness and personal innovativeness. Campus-Wide Information Systems, 29(2), 117-127.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Graham, K.L., Cohen, A., Reynolds, E.E., & Huang, G.C. (2019). Effect of a flipped classroom on knowledge acquisition and retention in an internal medicine residency program. Journal of Graduate Medical Education, 11(1), 92-97.
Hair Jr, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107–123.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. Eu-ropean Business Review, 31(1), 2–24.
Hendry, G. D., Ryan, G., & Harris, J. (2003). Group problems in problem-based learning. Medical Teacher, 25(6), 609-616.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.
Hsu, C. L., & Lin, J. C. C. (2008). Acceptance of blog usage: the roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management, 45(1), 65–74.
Ifinedo, P., Pyke, J., & Anwar, A. (2018). Business undergraduates’ perceived use outcomes of moodle in a blended learn-ing environment: the roles of usability factors and external support. Telematics and Informatics, 35(1), 93–102.
Islam, A. N. (2016). E-learning system use and its outcomes: Moderating role of perceived compatibility. Telematics and Informatics, 33(1), 48-55.
Jensen, J.L., Holt, E.A., Sowards, J.B., Ogden, T.H., & West, R.E. (2018). Investigating strategies for Pre-Class content learning in a flipped classroom. Journal of Science Education and Technology, 27(6), 1-13.
Jin, S.V., Muqaddam, A., & Ryu, E. (2019). Instafamous and social media influencer marketin. Marketing Intelligence & Planning, 37(5), 567-579.
Joo, Y. J., Lim, K. Y., & Kim, E. K. (2011). Online university student’s satisfaction and persistence: examining perceived level of presence, usefulness and ease of use as predictors in a structural model. Computers & Education, 57(2), 1654–1664.
Kemp, A., Palmer, E., & Strelan, P. (2019). A taxonomy of factors affecting attitudes towards educational technologies for use with technology acceptance models. British Journal of Educational Technology, 50(5), 2394-2413.
Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford publications, New York, London.
Lai, H. M., & Chen, C. P. (2011). Factors influencing secondary school teachers’ adoption of teaching blogs. Computers & Education, 56(4), 948-960.
Liu, C. H., & Huang, Y. M. (2015). An empirical investigation of computer simulation technology acceptance to explore the factors that affect user intention. Universal Access in the Information Society, 14(3), 449-457.
Liu, M., Kalk, D., Kinney, L., & Orr, G. (2012). Web 2.0 and its use in higher education from 2007-2009: A review of lit-erature. International Journal on E-Learning, 11(2), 153-179.
Nistor, N. (2014). When technology acceptance models won’t work: Non-significant intention-behavior effects. Comput-ers in Human Behavior, 34, 299–300.
Mei, B., Brown, G. T., & Teo, T. (2017). Toward an understanding of preservice English as a Foreign Language teachers’ acceptance of Computer-Assisted Language Learning 2.0 in the People’s Republic of China. Journal of Educational Computing Research, 56(1), 74–104.
Merrill, M. D. (2012). First principles of instruction. Hoboken: Wiley.
Mok, C. K. F., Dodd, B., & Whitehill, T. L. (2009). Speech-language pathology students’ approaches to learning in prob-lem-based learning curriculum. International Journal of Speech-Language Pathology, 11(6), 472–481.
Murillo-Zamorano, L. R., Sánchez, J. Á. L., & Godoy-Caballero, A. L. (2019). How the flipped classroom affects knowledge, skills, and engagement in higher education: Effects on students' satisfaction. Computers & Education, 141, 103608.
Newland, B., & Byles, L. (2014). Changing academic teaching with Web 2.0 technologies. Innovations in Education and Teaching International, 51(3), 315-325.
Sandford, R., Ulicsak, M., & Facer, K. (2006). Teaching with Games: using computer games in formal educa-tion. Futurelab, Bristol.
Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., & Gudergan, S. P. (2016). Estimation issues with PLS and CBSEM: Where the bias lies! Journal of Business Research, 69(10), 3998–4010.
Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equa-tion modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13-35.
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J.-H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347.
Sinclair, P. M., Kable, A., Levett-Jones, T., & Booth, D. (2016). The effectiveness of Internet-based e-learning on clini-cian behaviour and patient outcomes: a systematic review. International journal of nursing studies, 57, 70-81.
Teo, T., Milutinović, V., Zhou, M., & Banković, D. (2017). Traditional vs. innovative uses of computers among mathe-matics pre-service teachers in Serbia. Interactive Learning Environments, 25(7), 811–827.
Tondeur, J., Kershaw, L. H., Vanderlinde, R., & van Braak, J. (2013). Getting inside the black box of technology integra-tion in education: Teachers’ stimulated recall of classroom observations. Australasian Journal of Educational Tech-nology, 29(3), 434–449.
Toni Mohr, A., Holtbrügge, D., & Berg, N. (2012). Learning style preferences and the perceived usefulness of e-learning. Teaching in Higher Education, 17(3), 309-322.
Van der Heijden, H. (2003). Factors influencing the usage of websites: the case of a generic portal in The Netherlands. In-formation & Management, 40(6), 541–549.
Van Merrienboer, J. J. G., & Kirschner, P. A. (2013). Ten steps to complex learning. 2nd ed., New York: Routledge.
Whitton, N., & Moseley, A. (Eds.). (2012). Using games to enhance learning and teaching. Taylor & Francis.
Wu, J., & Du, H. (2012). Toward a better understanding of behavioral intention and system usage constructs. European Journal of Information Systems, 21(6), 680–698.
Yi, M. Y., & Hwang, Y. (2003). Predicting the use of web-based information systems: self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model. International Journal of Human-Computer Studies, 59(4), 431–449.
Yusof, N., & Alas, Y. (2021). Benefits and Students’ Perception on Role-Play Teaching Technique: Progressive & Fun Learning Experiences in Brunei. Indonesian Journal on Learning and Advanced Education (IJOLAE), 3(3), 225-234.
Zainuddin, Z., Zhang, Y., Li, X., Chu, S.K.W., Idris, S., & Keumala, C.M. (2019). Research trends in flipped classroom empirical evidence from 2017 to 2018: a content analysis. Interactive Technology and Smart Education, 16(3).
Zulfiqar, S., Zhou, R., Asmi, F., & Yasin, A. (2018). Using simulation system for collaborative learning to enhance learn-er’s performance. Cogent Education, 5(1), 1424678.
Afthanorhan, A., Awang, Z., & Aimran, N. (2020). An extensive comparison of CB-SEM and PLS-SEM for reliability and validity. International Journal of Data and Network Science, 4(4), 357–364.
Al-Fraihat, D., Joy, M., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in human behavior, 102, 67-86.
Al Jarrah, A., Thomas, M.K., & Shehab, M. (2018). Investigating temporal access in a flipped classroom: procrastination persists. International Journal of Educational Technology in Higher Education, 15(1), 1.
Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2016). Determinants of perceived usefulness of e-learning sys-tems. Computers in Human Behavior, 64, 843-858.
Atas, M. (2015). The reduction of speaking anxiety in EFL learners through drama techniques. Procedia - Social and Be-havioral Sciences, 176, 961–969.
Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 244–254.
Bakhsh, S. A. (2016). Using Games as a Tool in Teaching Vocabulary to Young Learners. English language teach-ing, 9(7), 120-128.
Buzzard, C., Crittenden, V. L., Crittenden, W. F., & McCarty, P. (2011). The use of digital technologies in the classroom: A teaching and learning perspective. Journal of Marketing Education, 33(2), 131-139.
Chen, C. P., Lai, H. M., & Ho, C. Y. (2015). Why do teachers continue to use teaching blogs? The roles of perceived vol-untariness and habit. Computers & Education, 82, 236-249.
Chen, Y. H., & Keng, C. J. (2018). Utilizing the Push-Pull-Mooring-Habit framework to explore users’ intention to switch from offline to online real-person English learning platform. Internet Research. 29, 167–193.
Cheng, S., Lee, S. J., & Choi, B. (2019). An empirical investigation of users’ voluntary switching intention for mobile per-sonal cloud storage services based on the push-pull-mooring framework. Computers in Human Behavior, 92, 198-215.
Dolmans, D. H., Loyens, S. M., Marcq, H., & Gijbels, D. (2016). Deep and surface learning in problem-based learning: a review of the literature. Advances in health sciences education, 21(5), 1087-1112.
Etikan, I., & Bala, K. (2017). Sampling and sampling methods. Biometrics & Biostatistics International Journal, 5(6), 149.
Fagan, M., Kilmon, C., & Pandey, V. (2012). Exploring the adoption of a virtual reality simulation: The role of perceived ease of use, perceived usefulness and personal innovativeness. Campus-Wide Information Systems, 29(2), 117-127.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Graham, K.L., Cohen, A., Reynolds, E.E., & Huang, G.C. (2019). Effect of a flipped classroom on knowledge acquisition and retention in an internal medicine residency program. Journal of Graduate Medical Education, 11(1), 92-97.
Hair Jr, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107–123.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. Eu-ropean Business Review, 31(1), 2–24.
Hendry, G. D., Ryan, G., & Harris, J. (2003). Group problems in problem-based learning. Medical Teacher, 25(6), 609-616.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.
Hsu, C. L., & Lin, J. C. C. (2008). Acceptance of blog usage: the roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management, 45(1), 65–74.
Ifinedo, P., Pyke, J., & Anwar, A. (2018). Business undergraduates’ perceived use outcomes of moodle in a blended learn-ing environment: the roles of usability factors and external support. Telematics and Informatics, 35(1), 93–102.
Islam, A. N. (2016). E-learning system use and its outcomes: Moderating role of perceived compatibility. Telematics and Informatics, 33(1), 48-55.
Jensen, J.L., Holt, E.A., Sowards, J.B., Ogden, T.H., & West, R.E. (2018). Investigating strategies for Pre-Class content learning in a flipped classroom. Journal of Science Education and Technology, 27(6), 1-13.
Jin, S.V., Muqaddam, A., & Ryu, E. (2019). Instafamous and social media influencer marketin. Marketing Intelligence & Planning, 37(5), 567-579.
Joo, Y. J., Lim, K. Y., & Kim, E. K. (2011). Online university student’s satisfaction and persistence: examining perceived level of presence, usefulness and ease of use as predictors in a structural model. Computers & Education, 57(2), 1654–1664.
Kemp, A., Palmer, E., & Strelan, P. (2019). A taxonomy of factors affecting attitudes towards educational technologies for use with technology acceptance models. British Journal of Educational Technology, 50(5), 2394-2413.
Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford publications, New York, London.
Lai, H. M., & Chen, C. P. (2011). Factors influencing secondary school teachers’ adoption of teaching blogs. Computers & Education, 56(4), 948-960.
Liu, C. H., & Huang, Y. M. (2015). An empirical investigation of computer simulation technology acceptance to explore the factors that affect user intention. Universal Access in the Information Society, 14(3), 449-457.
Liu, M., Kalk, D., Kinney, L., & Orr, G. (2012). Web 2.0 and its use in higher education from 2007-2009: A review of lit-erature. International Journal on E-Learning, 11(2), 153-179.
Nistor, N. (2014). When technology acceptance models won’t work: Non-significant intention-behavior effects. Comput-ers in Human Behavior, 34, 299–300.
Mei, B., Brown, G. T., & Teo, T. (2017). Toward an understanding of preservice English as a Foreign Language teachers’ acceptance of Computer-Assisted Language Learning 2.0 in the People’s Republic of China. Journal of Educational Computing Research, 56(1), 74–104.
Merrill, M. D. (2012). First principles of instruction. Hoboken: Wiley.
Mok, C. K. F., Dodd, B., & Whitehill, T. L. (2009). Speech-language pathology students’ approaches to learning in prob-lem-based learning curriculum. International Journal of Speech-Language Pathology, 11(6), 472–481.
Murillo-Zamorano, L. R., Sánchez, J. Á. L., & Godoy-Caballero, A. L. (2019). How the flipped classroom affects knowledge, skills, and engagement in higher education: Effects on students' satisfaction. Computers & Education, 141, 103608.
Newland, B., & Byles, L. (2014). Changing academic teaching with Web 2.0 technologies. Innovations in Education and Teaching International, 51(3), 315-325.
Sandford, R., Ulicsak, M., & Facer, K. (2006). Teaching with Games: using computer games in formal educa-tion. Futurelab, Bristol.
Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., & Gudergan, S. P. (2016). Estimation issues with PLS and CBSEM: Where the bias lies! Journal of Business Research, 69(10), 3998–4010.
Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equa-tion modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13-35.
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J.-H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347.
Sinclair, P. M., Kable, A., Levett-Jones, T., & Booth, D. (2016). The effectiveness of Internet-based e-learning on clini-cian behaviour and patient outcomes: a systematic review. International journal of nursing studies, 57, 70-81.
Teo, T., Milutinović, V., Zhou, M., & Banković, D. (2017). Traditional vs. innovative uses of computers among mathe-matics pre-service teachers in Serbia. Interactive Learning Environments, 25(7), 811–827.
Tondeur, J., Kershaw, L. H., Vanderlinde, R., & van Braak, J. (2013). Getting inside the black box of technology integra-tion in education: Teachers’ stimulated recall of classroom observations. Australasian Journal of Educational Tech-nology, 29(3), 434–449.
Toni Mohr, A., Holtbrügge, D., & Berg, N. (2012). Learning style preferences and the perceived usefulness of e-learning. Teaching in Higher Education, 17(3), 309-322.
Van der Heijden, H. (2003). Factors influencing the usage of websites: the case of a generic portal in The Netherlands. In-formation & Management, 40(6), 541–549.
Van Merrienboer, J. J. G., & Kirschner, P. A. (2013). Ten steps to complex learning. 2nd ed., New York: Routledge.
Whitton, N., & Moseley, A. (Eds.). (2012). Using games to enhance learning and teaching. Taylor & Francis.
Wu, J., & Du, H. (2012). Toward a better understanding of behavioral intention and system usage constructs. European Journal of Information Systems, 21(6), 680–698.
Yi, M. Y., & Hwang, Y. (2003). Predicting the use of web-based information systems: self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model. International Journal of Human-Computer Studies, 59(4), 431–449.
Yusof, N., & Alas, Y. (2021). Benefits and Students’ Perception on Role-Play Teaching Technique: Progressive & Fun Learning Experiences in Brunei. Indonesian Journal on Learning and Advanced Education (IJOLAE), 3(3), 225-234.
Zainuddin, Z., Zhang, Y., Li, X., Chu, S.K.W., Idris, S., & Keumala, C.M. (2019). Research trends in flipped classroom empirical evidence from 2017 to 2018: a content analysis. Interactive Technology and Smart Education, 16(3).
Zulfiqar, S., Zhou, R., Asmi, F., & Yasin, A. (2018). Using simulation system for collaborative learning to enhance learn-er’s performance. Cogent Education, 5(1), 1424678.