Advertisement

Understanding the continued use of flipped classroom instruction: a personal beliefs model in Chinese higher education

  • Jin Cai
  • Harrison Hao YangEmail author
  • Di Gong
  • Jason MacLeod
  • Sha Zhu
Article

Abstract

The flipped classroom has gained much attention for its pedagogical success in higher education. However, continued use of this technology-supported instructional approach has been problematic. To support the success and continuation of flipped classroom implementation, this study employs structural equation modeling techniques to examine the relationships between five key factors of influence (computer self-efficacy, perceived technological pedagogical content knowledge, perceived ease of use, perceived usefulness, perceived organizational support) and instructors’ continued use intention. The results identify that instructors’ perceived organizational support and perceived technological pedagogical content knowledge are the only factors examined that directly impact continued use intention. Instructors’ technological pedagogical content knowledge also mediates between perceived organizational support and computer self-efficacy to continued use intention. These findings provide empirical evidence of such relationships and indicate that personal beliefs regarding technology itself are not the strongest factors influencing the continued use of flipped classroom instruction. Rather, instructors’ beliefs relating to their environmental surroundings and personal knowledge regarding technology usage for instructional purposes are the key factors of instructors’ continued use intention in Chinese higher education.

Keywords

Flipped classroom Continued use Computer self-efficacy Perceived organizational support Perceived usefulness Perceived ease of use TPACK Higher education 

Notes

Funding

This study was funded by the Ministry of Education of the People’s Republic of China (Grant Number 14JZD044).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

References

  1. Admiraal, W., Lockhorst, D., Smit, B., & Weijers, S. (2013). The integrative model of behavior prediction to explain technology use in post-graduate teacher education programs in the Netherlands. International Journal of Higher Education, 2(4), 172–178.  https://doi.org/10.5430/ijhe.v2n4p172.CrossRefGoogle Scholar
  2. Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665–694. https://www.jstor.org/stable/3250951.CrossRefGoogle Scholar
  3. 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.  https://doi.org/10.1037/0033-2909.103.3.411.CrossRefGoogle Scholar
  4. Archambault, L., & Crippen, K. (2009). Examining TPACK among K-12 online distance educators in the United States. Contemporary Issues in Technology and Teacher Education, 9(1), 71–88. https://www.learntechlib.org/p/29332/.
  5. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
  6. Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52(1), 1–26.  https://doi.org/10.1146/annurev.psych.52.1.1.CrossRefGoogle Scholar
  7. Barclay, D., Thompson, R., & Higgins, C. (1995). The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use an illustration. Technology Studies, 2(2), 285–309.Google Scholar
  8. Bergmann, J., & Sams, A. (2012). Flip your classroom: Reach every student in every class every day. Arlington, VA: International Society for Technology. in Education.Google Scholar
  9. Berrett, D. (2012). How ‘flipping’ the classroom can improve the traditional lecture. The Chronicle of Higher Education, 58(25), 1–6.Google Scholar
  10. Bishop, J. L., & Verleger, M. A. (2013). The flipped classroom: A survey of the research. In Paper presented at 2013 ASEE annual conference & exposition, Atlanta, Georgia. https://peer.asee.org/22585.
  11. Bøe, T., Gulbrandsen, B., & Sørebø, Ø. (2015). How to stimulate the continued use of ICT in higher education: Integrating information systems continuance theory and agency theory. Computers in Human Behavior, 50, 375–384.  https://doi.org/10.1016/j.chb.2015.03.084.CrossRefGoogle Scholar
  12. Butts, A. (2014). Student views on the use of a flipped classroom approach: Evidence from Australia. Business Education & Accreditation, 6(1), 33–43.Google Scholar
  13. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336.Google Scholar
  14. Clark, R. E., & Salomon, G. (1986). Media in teaching. In M. Wittrock (Ed.), Handbook of research on teaching (3rd ed.). New York, NY: Macmillan.Google Scholar
  15. Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211. https://www.jstor.org/stable/249688.CrossRefGoogle Scholar
  16. Critz, C., & Wright, D. (2013). Using the flipped classroom in graduate nursing education. Nurse Educator, 38(5), 210–213.  https://doi.org/10.1097/NNE.0b013e3182a0e56a.CrossRefGoogle Scholar
  17. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://www.jstor.org/stable/249008.CrossRefGoogle Scholar
  18. Deslauriers, L., Schelew, E., & Wieman, C. (2011). Improved learning in a large-enrollment physics class. Science, 332(6031), 862–864.  https://doi.org/10.1126/science.1201783.CrossRefGoogle Scholar
  19. Dian, S., & Rhea, K. (2016, October). Teaching with technology: 55 percent of faculty are flipping the classroom. Retrieved from: https://campustechnology.com/articles/2016/10/12/55-percent-of-faculty-are-flipping-the-classroom.aspx?admgarea=News.
  20. Eisenberger, R., Huntington, R., Hutchison, S., & Sowa, D. (1986). Perceived organizational support. Journal of Applied Psychology, 71, 500–507.CrossRefGoogle Scholar
  21. Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://www.jstor.org/stable/3150980.CrossRefGoogle Scholar
  22. Gefen, D., Straub, D. W., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(1), 1–77. https://aisel.aisnet.org/cais/vol4/iss1/7.
  23. Grandgenett, N. F. (2008). Perhaps a matter of imagination: Technological pedagogical content knowledge in mathematics education. In M. C. Herring, P. Koehler, & M. J. Mishra (Eds.), The Handbook of technological pedagogical content knowledge (TPCK) for educators (pp. 145–166). New York, NY: Routledge.Google Scholar
  24. Guillemin, F., Bombardier, C., & Beaton, D. (1993). Cross-cultural adaptation of health-related quality of life measures: Literature review and proposed guidelines. Journal of Clinical Epidemiology, 46(12), 1417–1432.  https://doi.org/10.1016/0895-4356(93)90142-N.CrossRefGoogle Scholar
  25. Hamdan, N., McKnight, P. E., McKnight, K., & Arfstrom, K. M. (2013). A white paper based on the literature review: A review of flipped learning. Retrieved from http://flippedlearning.org/wp-content/uploads/2016/07/WhitePaper_FlippedLearning.pdf.
  26. Hao, Y., & Lee, K. S. (2016). Teaching in flipped classrooms: Exploring pre-service teachers’ concerns. Computers in Human Behavior, 57, 250–260.  https://doi.org/10.1016/j.chb.2015.12.022.CrossRefGoogle Scholar
  27. Harkness, J. A., & Schoua-Glusberg, A. (1998). Questionnaires in translation. In J.A. Harkness (Ed.), Cross-cultural survey equivalence (pp. 87–126) Mannheim, Germany: Open Access Repository. https://nbn-resolving.de/urn:nbn:de:0168-ssoar-49733-1.
  28. Hill, P. (2010). Examination systems: Asia-Pacific secondary education system review series No.1. Bangkok: UNESCO.Google Scholar
  29. Hoffmann, S. (2014). Beyond the flipped classroom: Redesigning a research methods course for e3 instruction. Contemporary Issues in Education Research, 7(1), 51–62.CrossRefGoogle Scholar
  30. Hung, H.-T. (2015). Flipping the classroom for English language learners to foster active learning. Computer Assisted Language Learning, 28(1), 81–96.  https://doi.org/10.1080/09588221.2014.967701.CrossRefGoogle Scholar
  31. Jovanović, J., Gašević, D., Dawson, S., Pardo, A., & Mirriahi, N. (2017). Learning analytics to unveil learning strategies in a flipped classroom. Internet and Higher Education, 33, 74–85.  https://doi.org/10.1016/j.iheduc.2017.02.001.CrossRefGoogle Scholar
  32. Keengwe, J., Kidd, T., & Kyei-Blankson, L. (2009). Faculty and technology: implications for faculty training and technology leadership. Journal of Science Education and Technology, 18(1), 23–28.  https://doi.org/10.1007/s10956-008-9126-2.CrossRefGoogle Scholar
  33. Koh, J. H. L., & Chai, C. S. (2016). Seven design frames that teachers use when considering technological pedagogical content knowledge (TPACK). Computers & Education, 102, 244–257.  https://doi.org/10.1016/j.compedu.2016.09.003.CrossRefGoogle Scholar
  34. Kurup, V., & Hersey, D. (2013). The changing landscape of anaesthesia education: Is flipped classroom the answer? Current Opinion in Anaesthesiology, 26(6), 726–731.  https://doi.org/10.1097/ACO.0000000000000004.CrossRefGoogle Scholar
  35. Lam, S. F., Cheng, R. W. Y., & Choy, H. C. (2010). School support and teacher motivation to implement project-based learning. Learning and Instruction, 20(6), 487–497.  https://doi.org/10.1016/j.learninstruc.2009.07.003.CrossRefGoogle Scholar
  36. Lu, H. P., & Hsiao, K. L. (2007). Understanding intention to continuously share information on weblogs. Internet Research, 17(4), 345–361.  https://doi.org/10.1108/10662240710828030.CrossRefGoogle Scholar
  37. MacLeod, J., Yang, H. H., & Xiang, Z. (2017a). Understanding college students’ intrinsic motivation and social interdependence in intercultural computer-supported collaborative learning between USA and China. Asia-Pacific Education Researcher, 26(3-4), 205–217.  https://doi.org/10.1007/s40299-017-0341-6 CrossRefGoogle Scholar
  38. MacLeod, J., Yang, H. H., Zhu, S., & Shi, Y. (2017b). Technological factors and student-to-student connected classroom climate in cloud classrooms. Journal of Educational Computing Research, 56(6), 826–847.  https://doi.org/10.1177/0735633117733999 CrossRefGoogle Scholar
  39. Ministry of Education of the People’s Republic of China. (2014). Educational Statistical Yearbook. Retrieved from: http://www.moe.edu.cn/s78/A03/moe_560/jytjsj_2014/2014_qg/201509/t20150909_206904.html.
  40. Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.CrossRefGoogle Scholar
  41. Missildine, K., Fountain, R., Summers, L., & Gosselin, K. (2013). Flipping the classroom to improve student performance and satisfaction. Journal of Nursing Education, 52(10), 597–599.CrossRefGoogle Scholar
  42. O’Flaherty, J., & Phillips, C. (2015). The use of flipped classrooms in higher education: a scoping review. Internet and Higher Education, 25, 85–95.  https://doi.org/10.1016/j.iheduc.2015.02.002.CrossRefGoogle Scholar
  43. Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78.  https://doi.org/10.1037/0003-066X.55.1.68.CrossRefGoogle Scholar
  44. Segars, A. H. (1997). Assessing the unidimensionality of measurement: A paradigm and illustration within the context of information systems research. Omega International Journal of Management Science, 25(1), 107–121.  https://doi.org/10.1016/S0305-0483(96)00051-5.CrossRefGoogle Scholar
  45. Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14.  https://doi.org/10.3102/0013189X015002004.CrossRefGoogle Scholar
  46. Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124–143. https://www.jstor.org/stable/249443.CrossRefGoogle Scholar
  47. Van Laar, E., Van Deursen, A. J. A. M., Van Dijk, J. A. G. M., & de Haan, J. (2017). The relation between 21st-century skills and digital skills or literacy: A systematic literature review. Computers in Human Behavior, 72, 577–588.  https://doi.org/10.1016/j.chb.2017.03.010.CrossRefGoogle Scholar
  48. 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. https://www.jstor.org/stable/30036540.CrossRefGoogle Scholar
  49. Wells, J. D., Campbell, D. E., Valacich, J. S., & Featherman, M. (2010). The effect of perceived novelty on the adoption of information technology innovations: A risk/reward perspective. Decision Sciences, 41(4), 813–843.  https://doi.org/10.1111/j.1540-5915.2010.00292.x.CrossRefGoogle Scholar
  50. Wright, N. (2015). A case for adapting and applying continuance theory to education: understanding the role of student feedback in motivating teachers to persist with including digital technologies in learning. Teachers and Teaching, 21(4), 459–471.  https://doi.org/10.1080/13540602.2014.969105.CrossRefGoogle Scholar
  51. Yang, H. H., Feng, L., & MacLeod, J. (2018a). Understanding students’ acceptance of cloud classrooms: Integrating UTAUT and connected classroom climate. Journal of Educational Computing Research.  https://doi.org/10.1177/0735633117746084 CrossRefGoogle Scholar
  52. Yang, H. H., Zhu, S., & MacLeod, J. (2018b). Promoting education equity in rural and underdeveloped areas: Cases of computer-supported collaborative teaching in China. Eurasia Journal of Mathematics, Science and Technology Education, 14(6), 2393–2405.  https://doi.org/10.29333/ejmste/89841 CrossRefGoogle Scholar
  53. Zainuddin, Z., & Halili, S. H. (2016). Flipped classroom research and trends from different fields of study. The International Review of Research in Open and Distributed Learning17(3), 313–340.  https://doi.org/10.19173/irrodl.v17i3.2274.
  54. Zhang, Y., Fang, Y., Wei, K.-K., & Wang, Z. (2012). Promoting the intention of students to continue their participation in e-learning systems: The role of the communication environment. Information Technology & People, 25(4), 356–375.  https://doi.org/10.1108/09593841211278776.CrossRefGoogle Scholar
  55. Zhao, Y. (2009). Catching up or leading the way: American education in the age of globalization. Alexandria, VA: ASCD.Google Scholar
  56. Zhu, S., Yang, H. H., MacLeod, J., Shi, Y., & Wu, D. (2018). Parents’ and students’ attitudes toward tablet integration in schools. International Review of Research in Open and Distributed Learning, 19(4), 222–240.  https://doi.org/10.19173/irrodl.v19i4.2970 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Central China Normal UniversityWuhanChina
  2. 2.Hubei University of EducationWuhanChina
  3. 3.State University of New York at OswegoNew YorkUSA
  4. 4.Wuhan Huada National E-learning Technologies Co. Ltd.WuhanChina

Personalised recommendations