Research Article
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Extending Technology Acceptance Model with Scientific Epistemological and Science Teaching Efficacy Beliefs: A Study with Preservice Teachers

Year 2022, , 1 - 16, 31.01.2022
https://doi.org/10.21891/jeseh.1055590

Abstract

The technology acceptance model (TAM) is a widely used framework to investigate factors influencing technology use in education. TAM refers to a person’s technology-related attitudes and beliefs influencing intention to use and actual use of technology and seeks predictors of behaviors whether to accept or reject using technology. There are various external variables extended to TAM to increase the predictivity of the model and the generalizability of findings. However, what is not yet clear is the impact of teacher-related variables such as teaching efficacy and epistemological beliefs on teachers’ technology acceptance and behavioral intention. This study examined 710 preservice teachers’  technology acceptance using an extended-TAM with scientific epistemological and science teaching efficacy beliefs. Data were collected through a self-reported measurement tool. Structural equation modeling was used to analyze data. Results revealed that the research model explained 59% of the variance in behavioral intention, and perceived usefulness is the most prominent determinant of behavioral intention. The subdimension of scientific epistemological beliefs, justification, is the strongest determinant in influencing TAM constructs among the external variables (epistemological and science teaching efficacy beliefs). Science teaching efficacy beliefs had small effects on technology acceptance
constructs. Recommendations were made based on the findings.

References

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Year 2022, , 1 - 16, 31.01.2022
https://doi.org/10.21891/jeseh.1055590

Abstract

References

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  • Al-Azawei, A., & Alowayr, A. (2020). Predicting the intention to use and hedonic motivation for mobile learning: A comparative study in two Middle Eastern countries. Technology in Society, 62, 101325. https://doi.org/10.1016/j.techsoc.2020.101325
  • Anderson, S. E., Groulx, J. G., & Maninger, R. M. (2011). Relationships among preservice teachers’ technology-related abilities, beliefs, and intentions to use technology in their future classrooms. Journal of Educational Computing Research, 45(3), 321-338. https://doi.org/10.2190%2FEC.45.3.d
  • Avcı Yucel, U., & Gulbahar, Y. (2013). Technology acceptance model: A review of the prior predictors. Ankara University Journal of Faculty of Educational Sciences (JFES), 46(1), 89-109. https://doi.org/10.1501/Egifak_0000001275
  • Aypay, A., Celik, H. C., Aypay, A., & Sever, M. (2012). Technology acceptance in education: A study of pre-service teachers in Turkey. Turkish Online Journal of Educational Technology-TOJET, 11(4), 264-272.
  • Bahcivan, E. (2014). Examining relationships among Turkish pre-service science teachers’ conceptions of teaching and learning, scientific epistemological beliefs and science teaching efficacy beliefs. Journal of Baltic Science Education, 13(6), 870-882.
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  • Bano, M., Zowghi, D., Kearney, M., Schuck, S., & Aubusson, P. (2018). Mobile learning for science and mathematics school education: A systematic review of empirical evidence. Computers & Education, 121, 30-58. https://doi.org/10.1016/j.compedu.2018.02.006
  • Bardakcı, S., & Alkan, M. F. (2019). Investigation of Turkish preservice teachers’ intentions to use IWB in terms of technological and pedagogical aspects. Education and Information Technologies, 24(5), 2887-2907. https://doi.org/10.1007/s10639-019-09904-4
  • Baydas, O., & Goktas, Y. (2017). A model for preservice teachers’ intentions to use ICT in future lessons. Interactive Learning Environments, 25(7), 930-945. https://doi.org/10.1080/10494820.2016.1232277
  • Becker, S., Klein, P., Gößling, A., & Kuhn, J. (2020). Using mobile devices to enhance inquiry-based learning processes. Learning and Instruction, 69, 101350. https://doi.org/10.1016/j.learninstruc.2020.101350
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  • Bondy, E., Ross, D., Adams, A., Nowak, R., Brownell, M., Hoppey, D., ... & Stafford, L. (2007). Personal epistemologies and learning to teach. Teacher Education and Special Education, 30(2), 67-82. https://doi.org/10.1177%2F088840640703000202
  • Byrne, B. M. (2016). Structural equation modeling with Amos: Basic concepts, applications, and programming (3rd Ed.). Taylor & Francis Group: New York. http://www.routledge.com/9781138797031
  • Cheng, M. M., Chan, K. W., Tang, S. Y., & Cheng, A. Y. (2009). Pre-service teacher education students’ epistemological beliefs and their conceptions of teaching. Teaching and Teacher Education, 25(2), 319-327. https://doi.org/10.1016/j.tate.2008.09.018
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  • Conley, A. M., Pintrich, P. R., Vekiri, I., & Harrison, D. (2004). Changes in epistemological beliefs in elementary science students. Contemporary Educational Psychology, 29(2), 186-204. https://doi.org/10.1016/j.cedpsych.2004.01.004
  • Creswell, J. W. (2015). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (5th Ed.). Boston: Pearson Education.
  • Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results (PhD). Cambridge, MA: Massachusetts Institute of Technology. Retrieved from https://dspace.mit.edu/bitstream/handle/1721.1/15192/14927137-MIT.pdf?sequence=2.
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  • Demirbag, M., & Bahcivan, E. (2021). Comprehensive exploration of digital literacy: Embedded with self-regulation and epistemological beliefs. Journal of Science Education and Technology, 30(3), 448-459. https://doi.org/10.1007/s10956-020-09887-9
  • Deng, F., Chai, C. S., Tsai, C. C., & Lee, M. H. (2014). The relationships among Chinese practicing teachers’ epistemic beliefs, pedagogical beliefs and their beliefs about the use of ICT. Journal of Educational Technology & Society, 17(2), 245-256. https://www.jstor.org/stable/10.2307/jeductechsoci.17.2.245
  • Ekici, D. I. (2018). Development of pre-service teachers’ teaching self-efficacy beliefs through an online community of practice. Asia pacific education review, 19(1), 27-40. https://doi.org/10.1007/s12564-017-9511-8
  • Eksail, F. A. A., & Afari, E. (2020). Factors affecting trainee teachers’ intention to use technology: A structural equation modeling approach. Education and Information Technologies, 25(4), 2681-2697. https://doi.org/10.1007/s10639-019-10086-2
  • Enochs, L. G., & Riggs, I. M. (1990). Further development of an elementary science teaching efficacy belief instrument: A preservice elementary scale. School Science and Mathematics, 90(8), 694-706. https://doi.org/10.1111/j.1949-8594.1990.tb12048.x
  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA.; Don Mills, Ontario: Addison-Wesley.
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177%2F002224378101800104
  • Gagnier, K. M., Holochwost, S. J., & Fisher, K. R. (2021). Spatial thinking in science, technology, engineering, and mathematics: Elementary teachers’ beliefs, perceptions, and self‐efficacy. Journal of Research in Science Teaching. https://doi.org/10.1002/tea.21722
  • Gibson, S., & Dembo, M. H. (1984). Teacher efficacy: A construct validation. Journal of Educational Psychology, 76, 569-582. https://psycnet.apa.org/doi/10.1037/0022-0663.76.4.569
  • Granić, A., & Marangunić, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572-2593. https://doi.org/10.1111/bjet.12864
  • Güneş, E., & Bahçivan, E. (2018). A mixed research-based model for pre-service science teachers’ digital literacy: Responses to “which beliefs” and “how and why they interact” questions. Computers & Education, 118, 96-106. https://doi.org/10.1016/j.compedu.2017.11.012
  • Gurer, M. D., & Akkaya, R. (2021). The influence of pedagogical beliefs on technology acceptance: a structural equation modeling study of pre-service mathematics teachers. Journal of Mathematics Teacher Education, 1-17. https://doi.org/10.1007/s10857-021-09504-5
  • Gyamfi, S. A. (2016). Identifying Ghanaian pre-service teachersâ readiness for computer use: A Technology Acceptance Model approach. International Journal of Education and Development using ICT, 12(2), 105-122.
  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. (2019). Multivariate data analysis (8th Ed.). United Kingdom: Pearson Education, Inc.
  • Hofer, B. K., & Pintrich, P. R. (1997). The development of epistemological theories: beliefs about knowledge and knowing and their relation to learning. Review of Educational Research, 67, 88-140. https://doi.org/10.3102%2F00346543067001088
  • Hoy, A. W., & Spero, R. B. (2005). Changes in teacher efficacy during the early years of teaching: A comparison of four measures. Teaching and teacher education, 21(4), 343-356. https://doi.org/10.1016/j.tate.2005.01.007
  • Huang, F., & Teo, T. (2019). Influence of teacher-perceived organisational culture and school policy on Chinese teachers’ intention to use technology: An extension of technology acceptance model. Educational Technology Research and Development, 68, 1547-1567. https://doi.org/10.1007/s11423-019-09722-y
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There are 70 citations in total.

Details

Primary Language English
Subjects Special Education and Disabled Education
Journal Section Articles
Authors

Tezcan Kartal 0000-0001-7609-3555

İbrahim Serdar Kızıltepe 0000-0002-6210-5372

Büşra Kartal 0000-0003-2107-057X

Publication Date January 31, 2022
Published in Issue Year 2022

Cite

APA Kartal, T., Kızıltepe, İ. S., & Kartal, B. (2022). Extending Technology Acceptance Model with Scientific Epistemological and Science Teaching Efficacy Beliefs: A Study with Preservice Teachers. Journal of Education in Science Environment and Health, 8(1), 1-16. https://doi.org/10.21891/jeseh.1055590