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

Yıl 2022, Cilt: 8 Sayı: 1, 1 - 16, 31.01.2022

Tezcan KARTAL İbrahim Serdar KIZILTEPE Büşra KARTAL

https://doi.org/10.21891/jeseh.1055590

Öz

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.

Anahtar Kelimeler

Technology acceptance model, Science teaching efficacy beliefs, Epistemological beliefs, Preservice teachers

Kaynakça

• Ajzen, I. (2006). Constructing a theory of planned behavior questionnaire. University of Massachusetts Amherst, 1-7. Retrieved from http://people.umass.edu/aizen/pdf/tpb.measurement.pdf on 1 October 2021.
• Akar, S. G. M. (2019). Does it matter being innovative: Teachers’ technology acceptance. Education and Information Technologies, 24(6), 3415-3432. https://doi.org/10.1007/s10639-019-09933-z
• 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.
• Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavior change. Psychological Review, 84(2), 191-215.
• 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
• Blonder, R., Jonatan, M., Bar-Dov, Z., Benny, N., Rap, S., & Sakhnini, S. (2013). Can you tube it? Providing chemistry teachers with technological tools and enhancing their self-efficacy beliefs. Chemistry Education Research and Practice, 14(3), 269-285. https://doi.org/10.1039/C3RP00001J
• 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
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd Ed.). Hillsdale, NJ: Erlbaum.
• 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.
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
• 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
• 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
• Huang, S. Y., Kuo, Y. H., & Chen, H. C. (2020). Applying digital escape rooms infused with science teaching in elementary school: Learning performance, learning motivation, and problem-solving ability. Thinking Skills and Creativity, 37, 100681. https://doi.org/10.1016/j.tsc.2020.100681
• Joo, Y. J., Park, S., & Lim, E. (2018). Factors influencing preservice teachers’ intention to use technology: TPACK, teacher self-efficacy, and technology acceptance model. Journal of Educational Technology & Society, 21(3), 48-59. https://www.jstor.org/stable/26458506
• Kapucu, S., & Bahçivan, E. (2015). High school students’ scientific epistemological beliefs, self-efficacy in learning physics and attitudes toward physics: A structural equation model. Research in Science & Technological Education, 33(2), 252-267. https://doi.org/10.1080/02635143.2015.1039976
• Kartal, B., & Çınar, C. (2018). Examining pre-service mathematics teachers’ beliefs of TPACK during a method course and field experience. Malaysian Online Journal of Educational Technology (MOJET) 6(3), 11-37. http://dx.doi.org/10.17220/mojet.2018.03.002
• Kartal, B. (2019). Examining pre-service teachers’ attitudes beliefs, and intentions related to using educational technologies. YYÜ Journal of Education Faculty, 16(1), 436-463. http://dx.doi.org/10.23891/efdyyu.2019.132
• Kartal, B. (2020). Pre-service science and mathematics teachers' teaching efficacy beliefs and attitudes toward teaching: A partial correlation research. Australian Journal of Teacher Education (Online), 45(9), 42-61. http://dx.doi.org/10.14221/ajte.2020v45n9.3
• Kartal, T., & Dilek, I. (2021). Developing pre-service elementary science teachers’ science teaching efficacy beliefs through microteaching by promoting efficacy sources. International Journal on Social and Education Sciences, 3(4), 710-731. https://doi.org/10.46328/ijonses.124
• Kızıltepe, İ. S., & Kartal, T. (2021). Examination of pre-service teachers’ epistemological beliefs in terms of multiple variables. Journal of Kırşehir Education Faculty, 22(3), 2036-2069. https://doi.org/10.29299/kefad.990289
• Kline, R. B. (2011). Convergence of structural equation modeling and multilevel modeling. In M. Williams (Ed.), The SAGE Handbook of Methodological Innovation. Thousand Oaks, CA: Sage.
• Lee, J., Cerreto, F. A., & Lee, J. (2010). Theory of planned behavior and teachers’ decisions regarding use of educational technology. Journal of Educational Technology & Society, 13(1), 152-164. https://www.jstor.org/stable/10.2307/jeductechsoci.13.1.152
• Lee, S. W. Y., Luan, H., Lee, M. H., Chang, H. Y., Liang, J. C., Lee, Y. H., ... & Tsai, C. C. (2021). Measuring epistemologies in science learning and teaching: A systematic review of the literature. Science Education, 105, 880-907. https://doi.org/10.1002/sce.21663
• Li, Y., Garza, V., Keicher, A., & Popov, V. (2019). Predicting high school teacher use of technology: Pedagogical beliefs, technological beliefs and attitudes, and teacher training. Technology, Knowledge and Learning, 24(3), 501-518. https://doi.org/10.1007/s10758-018-9355-2
• Min, M., Akerson, V., & Aydeniz, F. (2020). Exploring preservice teachers’ beliefs about effective science teaching through their collaborative oral reflections. Journal of Science Teacher Education, 31(3), 245-263. https://doi.org/10.1080/1046560X.2019.1690818
• Parkman, S., Litz, D., & Gromik, N. (2018). Examining pre-service teachers’ acceptance of technology-rich learning environments: A UAE case study. Education and Information Technologies, 23(3), 1253-1275. https://doi.org/10.1007/s10639-017-9665-3
• Sang, G., Valcke, M., Van Braak, J., & Tondeur, J. (2010). Student teachers’ thinking processes and ICT integration: Predictors of prospective teaching behaviors with educational technology. Computers & Education, 54(1), 103-112. https://doi.org/10.1016/j.compedu.2009.07.010
• Scherer, R., & Teo, T. (2019). Unpacking teachers’ intentions to integrate technology: A meta-analysis. Educational Research Review, 27, 90-109. https://doi.org/10.1016/j.edurev.2019.03.001
• Scherer, R., Siddiq, F., & Tondeur, J. (2020). All the same or different? Revisiting measures of teachers’ technology acceptance. Computers & Education, 143, 103656. https://doi.org/10.1016/j.compedu.2019.103656
• Schommer-Aikins, M. (2004). Explaining the epistemological belief system: Introducing the embedded systemic model and coordinated research approach. Educational psychologist, 39(1), 19-29. https://doi.org/10.1207/s15326985ep3901_3
• Siyam, N. (2019). Factors impacting special education teachers’ acceptance and actual use of technology. Education and Information Technologies, 24(3), 2035-2057. https://doi.org/10.1007/s10639-018-09859-y
• Tekkaya, C., Cakiroglu, J., & Ozkan, O. (2004). Turkish pre-service science teachers’ understanding of science and their confidence in teaching it. Journal of Education for Teaching, 30(1), 57-68. https://doi.org/10.1080/0260747032000162316
• Teo, T. (2008). Pre-service teachers’ attitudes towards computer use: A Singapore survey. Australasian Journal of Educational Technology, 24(4). https://doi.org/10.14742/ajet.1201
• Teo, T. (2009). Modelling technology acceptance in education: A study of pre-service teachers. Computers & Education, 52(2), 302-312. https://doi.org/10.1016/j.compedu.2008.08.006
• Teo, T. (2010). A path analysis of pre-service teachers’ attitudes to computer use: applying and extending the technology acceptance model in an educational context. Interactive Learning Environments, 18(1), 65-79. https://doi.org/10.1080/10494820802231327
• Teo, T., & Zhou, M. (2017). The influence of teachers’ conceptions of teaching and learning on their technology acceptance. Interactive Learning Environments, 25(4), 513-527. https://doi.org/10.1080/10494820.2016.1143844
• Teo, T., Chai, C. S., Hung, D., & Lee, C. B. (2008). Beliefs about teaching and uses of technology among pre‐service teachers. Asia‐Pacific Journal of Teacher Education, 36(2), 163-174. https://doi.org/10.1080/13598660801971641
• Teo, T., Fan, X., & Du, J. (2015). Technology acceptance among pre-service teachers: Does gender matter?. Australasian Journal of Educational Technology, 31(3). https://doi.org/10.14742/ajet.1672
• Teo, T., Ursavaş, Ö. F., & Bahçekapili, E. (2012). An assessment of pre-service teachers’ technology acceptance in Turkey: A structural equation modeling approach. Asia-Pacific Education Researcher, 21(1), 191-202. http://researchrepository.murdoch.edu.au/id/eprint/48415
• Tschannen-Moran, M., & Woolfolk Hoy, A. (2001). Teacher efficacy: Capturing an elusive construct. Teaching and Teacher Education, 17(7), 783-805. https://doi.org/10.1016/S0742-051X(01)00036-1
• Ursavaş, Ö., Şahin, S., & McIlroy, D. (2014). Technology acceptance measure for teachers: T-TAM. Journal of Theory and Practice in Education, 10(4), 885-917. Retrieved from https://dergipark.org.tr/tr/pub/eku/issue/5462/74152
• Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information systems research, 11(4), 342-365. https://doi.org/10.1287/isre.11.4.342.11872
• Wong, K. T., Teo, T., & Russo, S. (2012). Influence of gender and computer teaching efficacy on computer acceptance among Malaysian student teachers: An extended technology acceptance model. Australasian Journal of Educational Technology, 28(7). https://doi.org/10.14742/ajet.796