Extending Technology Acceptance Model with Scientific Epistemological and Science Teaching Efficacy Beliefs: A Study with Preservice Teachers
Year 2022,
, 1 - 16, 31.01.2022
Tezcan Kartal
İbrahim Serdar Kızıltepe
Büşra Kartal
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.
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Year 2022,
, 1 - 16, 31.01.2022
Tezcan Kartal
İbrahim Serdar Kızıltepe
Büşra Kartal
References
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- 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
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- 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
- Huang, F., & Teo, T. (2021). Examining the role of technology‐related policy and constructivist teaching belief on English teachers’ technology acceptance: A study in Chinese universities. British Journal of Educational Technology, 52(1), 441-460. https://doi.org/10.1111/bjet.13027
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