Abstract

During the COVID-19, university teachers’ informatization instructional leadership (TIIL) was adopted in many countries. This attracted widespread attention. This research derived six factors from the unified theory of acceptance and use of technology (UTAUT) including performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC) and behavioral intention (BI), added two new internal elements related to the individual teacher which are computer self-efficacy (CSE) and blended teaching competence (BTC). Before using the Partial Least Squares Structural Equation Modeling (PLS-SEM) to explore the contributing factors to TIIL by assessing interrelation between constructs within extended UTAUT model in this study. This pilot study aimed to examine the reliability and validity of modified scales incorporating Use Expectancy (UE) Scale including (PE Scale and EE Scale) used to measure use expectancy, SI Scale to measure social influence, FC Scale to measure facilitating conditions, CSE Scale to measure computer self-efficacy, BTC Scale to measure blended teaching competence, BI Scale to measure behavioral intention to adopt TIIL, and the TIIL Scale to measure teachers’ informatization instructional leadership. A total of 60 teachers from the large multi-disciplinary private undergraduate universities in Xi’an city of Shaanxi province in China participated in this research. The data was collected in November-December 2022 during the middle stages of COVID-19 pandemic. The PLS-SEM approach was used to evaluate the reliability and validity of the adapted scales. The internal consistency reliability was determined by composite reliability (CR) and Cronbach’s alpha. Convergent validity was assessed by outer loading and average variance extracted (AVE). Assessment of discriminant validity was measured by Fornell-Larcker criterion, Cross-loadings and Heterotrait-Monotrait Ratio (HTMT). Results showed after deleting nine items with lower than .40, Cronbach’s alpha values were all higher than .70. CR values were at a satisfactory level. All item values fulfilled the criteria of AVE, Fornell-Larcker criterion, cross-loadings, and HTMT. Research results revealed all adapted scales were valid and reliable to be used in future research. This study explored the influencing factors of TIIL in Chinese context, enriched the theory of TIIL, and provided practical support for the future development of TIIL.

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References

• [1] Agudo-Peregrina, Á. F., Hernández-García, Á., & Pascual-Miguel, F. J. (2014). Behavioral intention, use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning. COMPUTERS IN HUMAN BEHAVIOR, 34, 301-314. http://doi.org/10.1016/j.chb.2013.10.035

  [2] Alyoussef, I.Y. (2021). Factors Influencing Students’ Acceptance of M-Learning in Higher Education: An Application and Extension of the UTAUT Model. Electronics https://doi.org/10.3390/electronics10243171.

  [3] Ajzen, I. (1991). The Theory of Planned Behaviour. Orgnizational Behavior and Human Decision Processes, 50, 179–211.

  [4] Attuquayefio, S. N., & Addo, H. (2014). Using the UTAUT model to analyze students' ICT adoption. International journal of education and development using information and communication technology, 10 (3), 75.

  [5] Bervell, B., & Arkorful, V. (2020). LMS-enabled blended learning utilization in distance tertiary education: establishing the relationships among facilitating conditions, voluntariness of use and use behaviour. International Journal of Educational Technology in Higher Education, 17 (1) http://doi.org/10.1186/s41239-020-0183-9

  [6] Bian Q., Tian Zh.q., & Meng G. h. (2016). Research on the Influencing Factors of Network Learning of Normal School Students Taught in Mongolian in Perspective of Technology Acceptance Model. Research on Ethnic Education, 27(6), 60-64.

  [7] Bruggeman, B., Tondeur, J., Struyven, K., Pynoo, B., Garone, A., & Vanslambrouck, S.(2021). Experts speaking: Crucial teacher attributes for implementing blended learning in higher education. The Internet and higher education, 48. http://doi.org/10.1016/j.iheduc.2020.100772.

  [8] Buabeng-Andoh, C., & Baah, C. (2020). Pre-service teachers’ intention to use learning management system: an integration of UTAUT and TAM. Interactive Technology and Smart Education, 17(4), 455-474. http://doi.org/10.1108/ITSE-02-2020-0028.

  [9] Çakiroglu, J., Çakiroglu, E., & Boone, W. J. (2005). Pre-service teacher self-efficacy beliefs regarding science teaching: A comparison of pre-service teachers in Turkey and the USA. Science Educator, 14(1), 31–40.

  [10] Caprara, G. V., Barbaranelli, C., Steca, P., & Malone, P. S. (2006). Teachers’ self-efficacy beliefs as determinants of job satisfaction and students’ academic achievement: A study at the school level. Journal of School Psychology, 44(6), 473–490. http://doi.org/10.1016/j.jsp.2006.09.001.

  [11] Compeau, D. R., Higgins, C. A., & Huff, S.(1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23, 145.

  [12] Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. United States of America: Addison-Wesley Publishing Company. Retrieved from http://people.umass.edu/aizen/f &a1975. html

  [13] Goddard, R. D., Hoy, W. K., & Hoy, A. W. (2000). Collective teacher efficacy: Its meaning, measure, and impact on student achievement. American Educational Research Journal, 37(2), 479–507.

  [14] Graham, C. R. (2006). Blended learning systems: Definition, current trends, and future directions. In C. J. Bonk & C. R. Graham (Eds.), Handbook of blended learning Global perspectives local designs (pp. 3–21). San Francisco: John Wiley and Sons. doi:10.2307/4022859.

  [15] Graham, C. R., Borup, J., Pulham, E., & Larsen, R. (2019). K-12 Blended Teaching Readiness: Model and Instrument Development. Journal of research on technology in education, 51(3), 239-258. http://doi.org/10.1080/15391523.2019.1586601.

  [16] Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modelling (PLS-SEM) (2nd ed.). United States of America: SAGE Publication.

  [17] Ibrahim, R., Leng, N. S., Yusoff, R. C. M., Samy, G. N., Masrom, S., & Rizman, Z. I. (2018a) E-learning acceptance based on technology acceptance model (TAM). Journal of Fundamental and Applied Sciences, 9(4S), 871-889. http://doi.org/10.4314/jfas.v9i4S.50.

  [18] Kurt, H., Güngör, F., & Ekici, G. (2014). The relationship among teacher efficacy, efficacy regarding teaching, and responsibility for student achievement. Procedia - Social and Behavioral Sciences, 116, 802–807. http://doi.org/10.1016/j.sbspro.2014.01.301.

  [19] Lei Ch. z. (2018). Educational informatization: From 1.0 to 2.0-- The trend and thinking of the development of educational informatization in China in the new era Journal OF East China Normal University No.1 98-103. DOI:10. 16382/j. CNKI. 1000-5560. 2018.01.012.

  [20] Li Y. f. (2020). Research on Influencing Factors and Forming Path of Informatization Leadership Behavior of Primary School Teachers. Education Technology Research. DOI:10.13811/j.cnki.eer.2020.04.015

  [21] Li Y f.(2020b). Construction and application of information leadership model for primary school teachers. China Electronic Education (02), 94-101.

  [22] Li, Y., & Zhao, M. (2021). A Study on the Influencing Factors of Continued Intention to Use MOOCs: UTAUT Model and CCC Moderating Effect. Frontiers in Psychology, 12 http://doi.org/10.3389/fpsyg.2021.528259

  [23] Liaw, S. S., Chang, W. C., Hung, W. H., & Huang, H. M. (2006). Attitudes toward search engines as a learning assisted tool: approach of Liaw and Huang’s research model. Computers in Human Behavior, 22, 177–190.

  [24] Malczyk, B. R.(2018). Multimodal Instruction, the New Hybrid: A Student-Centered Approach to Blended Learning. Journal of Nonprofit Education and Leadership, 8(1), 16-31. http://doi.org/10.18666/JNEL-2018-V8-I1-8347.

  [25] Mohamadi, F. S., & Asadzadeh, H. (2012).Testing the mediating role of teachers’ self-efficacy beliefs in the relationship between sources of efficacy information and students achievement. Asia Pacific Education Review, 13(3), 427–433. http://doi.org/10.1007/s12564-011-9203-8.

  [26] Mojavezi, A., & Tamiz, M. P. (2012).The impact of teacher self-efficacy on the students’ motivation and achievement. Theory and Practice in Language Studies, 2(3), 483–491. http://doi.org/10.4304/tpls.2.3.483-491.

  [27] Mukred, M., Yusof, Z. M., Alotaibi, F. M., Mokhtar, U. A., & Fauzi, F. (2019). The Key Factors in Adopting an Electronic Records Management System (ERMS) in the Educational Sector: A UTAUT-Based Framework. IEEE Access, 7, 35963-35980. http://doi.org/10.1109/ACCESS.2019.2904617.

  [28] Pulham, E., & Graham, C. R. (2018). Comparing K-12 online and blended teaching competencies: a literature review. Distance Education, 39(3), 411-432. http://doi.org/10.1080/01587919.2018.1476840.

  [29] Raman, A., & Don, Y. (2013). Preservice Teachers’ Acceptance of Learning Management Software: An Application of the UTAUT2 Model. International education studies, 6 (7) http://doi.org/10.5539/ies.v6n7p157.

  [29] Raman, A., & Thannimalai, R.(2021). Factors Impacting the Behavioural Intention to Use E- learning at Higher Education amid the Covid-19 Pandemic: UTAUT2 Model. Psihologičeskaâ nauka i obrazovanie, 26 (3), 82-93. http://doi.org/10.17759/pse.2021260305.

  [30] Raman, A., Thannimalai, R., & Ismail, S. N. (2019). Principals’ Technology Leadership and its Effect on Teachers’ Technology Integration in 21st Century Classrooms. International Journal of Instruction, 12(4), 423-442. https://doi.org/10.29333/iji.2019.12428a

  [31] Ritimoni B, Prasenjit D, and Kandarpa D. (2021) Perception towards online/blended learning at the time of Covid-19 pandemic: an academic analytics in the Indian context. Asian Association of Open Universities Journal Vol. 16 No. 1, 2021 pp. 41-60. https://DOI 10.1108/AAOUJ-09-2020-0079.

  [32] Haarala-Muhonen A, Myyry L, Pyörälä E, Kallunki V, Anttila H, Katajavuori N, Kinnunen P and Tuononen T (2023) The impact of pedagogical and ICT training in teachers’ approaches to online teaching and use of digital tools. Front. Educ.8:1223665. doi: 10.3389/feduc.2023.1223665

  [33] Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modelling (PLS-SEM) (2nd Edition). United States of America: SAGE Publication.

  [34] 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. http://doi.org/10.1007/s11747-014-0403-8

  [35] Li Y and Zhao M (2021). A Study on the Influencing Factors of Continued Intention to Use MOOCs: UTAUT Model and CCC Moderating Effect. Front. Psychol. 12:528259. doi: 10.3389/fpsyg.2021.528259.

  [36] Senler, B., & Sungur, S. (2010). Pre-service science teacher’s teaching self-efficacy: A case from Turkey. Procedia - Social and Behavioral Sciences, 9, 771–775. http://doi.org/10.1016/j.sbspro.2010.12.232.

  [37] Sun Zh x, Liu X c. (2015). Teacher information-based teaching leadership: concept connotation and survey analysis. Modern Distance Education (04), 28-36.

  [38] Tschannen-Moran, M., Woolfolk-Hoy, A., & Hoy, W. K. (1998).Teacher efficacy: Its meaning and measure. Review of Educational Research, 68(2), 202–248. http://doi.org/10.3102/00346543068002202.

  [39] 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. http://doi.org/10.2307/30036540.

  [40] Wang X.p (2018). Research on Model Construction and Empirical Study of College Teacher’s Blended Learning Acceptance, 108-110 (Master dissertation). Yunnan Normal University. https://kns.cnki.net/kcms/detail/detail.aspx?FileName=1018796769.nh&DbName=CMFD2019.

  [41] Wong. K. K. (2013). Partial least squares structural equation modelling (PLS-SEM) techniques using SmartPLS, Marketing Bulletin, 24 (1), 1-32.

  [42] Yeop, M. A., Yaakob, M. F. M., Wong, K. T., Don, Y., Zain, F. M. (2019). Universiti Utara Malaysia, M., Universiti Pendidikan Sultan Idris, M., & Universiti Utara Malaysia, M. M. F. U. Implementation of ICT Policy (Blended Learning Approach): Investigating factors of Behavioural Intention and Use Behaviour. International journal of instruction, 12 (1), 767-782. http://doi.org/10.29333/iji.2019.12149a.

  [43] Yu T. zh. & Zhang X. f. (2020). Impact of Teacher Information Technology Leadership on Teaching Efficacy: An Empirical Analysis Using Structural Equation Model in Chinese Full Text. Teacher Education Research. DOI:10.13445/j.cnki.t.e.r.

  [44] Zhao L. l, and Zhang R.f (2019). Teachers’ Informationization Teaching Leadership: Connotation, Influencing Factors and Improving Path. Chongqing Higher Education Research, 7(3):86－97. DOI:10．15998/j．cnki．issn1673－8012．2019．03．007

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