Research Article
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Year 2023, , 22 - 32, 30.04.2023
https://doi.org/10.54535/rep.1210912

Abstract

References

  • Al-Abdullatif, A. M., Al-Dokhny, A. A., & Drwish, A. M. (2022). Critical factors influencing pre-service teachers’ use of the Internet of Things (IoT) in classrooms. International Journal of Interactive Mobile Technologies, 16 (4), 85-102
  • Atman Uslu, N. & Yildiz Durak, H. (2022). Understanding self-regulation, achievement emotions, and mindset of undergraduates in emergency remote teaching: a latent profile analysis. Interactive Learning Environments, 1-20.
  • Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user Information systems: Theory and results. Massachusetts Institute of Technology.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
  • Gökçearslan, Ş, & Saritepeci, M. (2021). Educational dimension of the internet of things. In H. Çakır & Ç. Uluyol (Eds.), Internet of Things from theory to practice (pp. 351–366). Nobel Publishing.
  • Gökçearslan, Ş., Yildiz Durak, H., & Atman Uslu, N. (2022). Acceptance of educational use of the Internet of Things (IoT) in the context of individual innovativeness and ICT competency of pre-service teachers. Interactive Learning Environments, 1-15.
  • Ionescu-Feleaga, L., Ionescu, BȘ, & Bunea, M. (2021). The IoT technologies acceptance in education by the students from the economic studies in Romania. The Amfiteatru Economic Journal, 23(57), 342–342.
  • Kassab, M., DeFranco, J., & Laplante, P. (2020). A systematic literature review on Internet of things in education: Benefits and challenges. Journal of Computer Assisted Learning, 36(2), 115-127.
  • Özdemir, A., Nursaçan, M. N. N., & Nursaçan, İ. (2014). 2014-2018 yılları arasında nesnelerin interneti (IoT) üzerine bir literatür taraması [A review of literature on internet of things (IoT) between 2014-2018]. Bandırma Onyedi Eylül Üniversitesi Sosyal Bilimler Araştırmaları Dergisi, 1(2), 1-22.
  • Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational psychology review, 18(4), 315-341.
  • Ray, S., Jin, Y., & Raychowdhury, A. (2016). The changing computing paradigm with Internet of Things: a tutorial introduction. IEEE Des Test, 33(2), 76–96.
  • Saadé, R. G., & Kira, D. (2006). The emotional state of technology acceptance. Issues in Informing Science & Information Technology, 3, 529-539.
  • Saritepeci, M., Yıldız Durak, H., & Durak, A. (2021). Hayat Boyu öğrenme bağlamında endüstri 4.0. In H. Yildiz Durak & M. Saritepeci (Eds.) Dijital Çağda Hayat Boyu Öğrenme (p. 221 -231). Pegem Pub.
  • Stojanović, D., Bogdanović, Z., Petrović, L., Mitrović, S., & Labus, A. (2020). Empowering learning process in secondary education using pervasive technologies. Interactive Learning Environments, 1-14. https://doi.org/10.1080/10494820.2020.1806886
  • Sula, A., Spaho, E., Matsuo, K., Barolli, L., Miho, R., & Xhafa, F. (2013). An IoT-based system for supporting children with autism spectrum disorder. In 2013 Eighth International Conference on Broadband and Wireless Computing, Communication and Applications, pp. 282–289.
  • Şahin, F. (2021). Öğretmen adaylarının bilişim teknolojileri kullanım niyetlerinde duyguların ve temel psikolojik ihtiyaçların rolü: Teknolojinin kabulüne motivasyonel bir yaklaşım [The Role of Emotions and Basic Psychological Needs in Preservice Teachers’ Intention to Use Information Technologies: A Motivational Approach to the Acceptance of Technology]. Unpublished PhD Thesis. Anadolu University, Turkey.
  • Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics (Vol. 5, pp. 481-498). Boston, MA: Pearson.
  • Tondeur, J., Aesaert, K., Prestridge, S., & Consuegra, E. (2018). A multilevel analysis of what matters in the training of pre-service teacher's ICT competencies. Computers & Education, 122, 32-42.
  • Triandis, H. C. (1980). Values, attitudes and interpersonal behavior. Nebraska symposium on motivation, 1979: Beliefs, attitudes, and values. University of Nebraska Press, Lincoln, NE, 195-259.
  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
  • Yildiz Durak, H. (2019). Examining the acceptance and use of online social networks by preservice teachers within the context of unified theory of acceptance and use of technology model. Journal of Computing in Higher Education, 31(1), 173-209.
  • Yildiz Durak, H. (2021a). Modeling of relations between K-12 teachers’ TPACK levels and their technology integration self-efficacy, technology literacy levels, attitudes toward technology and usage objectives of social networks. Interactive Learning Environments, 29(7), 1136–1162.
  • Yildiz Durak, H. (2021b). Preparing pre-service teachers to integrate teaching technologies into their classrooms: Examining the effects of teaching environments based on open-ended, hands-on and authentic tasks. Education and Information Technologies, 26(5), 5365–5387.
  • Zaerov, E., Letskovska, S., Seymenliyski, K., & Simionov, R. (2020, October). PV system monitoring by loT in smart university. In Proceedings of the 9th International Conference on Telecommunications and Remote Sensing (pp. 44–49).

The Role of Personal Variables and Emotions Related to Preservice Teachers’ Intention to Use Information Technologies in Acceptance of Educational Use of the Internet of Things (IoT)

Year 2023, , 22 - 32, 30.04.2023
https://doi.org/10.54535/rep.1210912

Abstract

The purpose of this study is to examine the relationship between pre-service teachers’ internet of things acceptance behaviors (intention, usefulness, ease of use, facilitating conditions) and personal variables and information technology (IT) emotions. The research participants consisted of 171 pre-service teachers studying at the education faculty of a state university in Turkey. A personal information form and two different scales (IoT technologies acceptance scale and IT Emotion Scale) were used to collect data. Multiple Linear Regression Analysis was used in the analysis of the data. As a result of the research, competency in using digital technologies was an important predictor of the scores related to usability, and the increase in competency in using digital technologies positively affected the scores related to usability. The experience of using digital technologies and fun are important predictors in explaining the scores related to intention. The experience of using digital technologies and the increase in fun positively affect the scores related to intention. The experience of using digital technologies is an important predictor of the scores related to ease of use, and the increase in the experience of using digital technologies positively affects the scores related to ease of use. Finally, the scores related to the facilitating conditions of the competency in using digital technologies are an important predictor, and the increase in the competency of using digital technologies positively affects the scores of the facilitating conditions.

References

  • Al-Abdullatif, A. M., Al-Dokhny, A. A., & Drwish, A. M. (2022). Critical factors influencing pre-service teachers’ use of the Internet of Things (IoT) in classrooms. International Journal of Interactive Mobile Technologies, 16 (4), 85-102
  • Atman Uslu, N. & Yildiz Durak, H. (2022). Understanding self-regulation, achievement emotions, and mindset of undergraduates in emergency remote teaching: a latent profile analysis. Interactive Learning Environments, 1-20.
  • Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user Information systems: Theory and results. Massachusetts Institute of Technology.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
  • Gökçearslan, Ş, & Saritepeci, M. (2021). Educational dimension of the internet of things. In H. Çakır & Ç. Uluyol (Eds.), Internet of Things from theory to practice (pp. 351–366). Nobel Publishing.
  • Gökçearslan, Ş., Yildiz Durak, H., & Atman Uslu, N. (2022). Acceptance of educational use of the Internet of Things (IoT) in the context of individual innovativeness and ICT competency of pre-service teachers. Interactive Learning Environments, 1-15.
  • Ionescu-Feleaga, L., Ionescu, BȘ, & Bunea, M. (2021). The IoT technologies acceptance in education by the students from the economic studies in Romania. The Amfiteatru Economic Journal, 23(57), 342–342.
  • Kassab, M., DeFranco, J., & Laplante, P. (2020). A systematic literature review on Internet of things in education: Benefits and challenges. Journal of Computer Assisted Learning, 36(2), 115-127.
  • Özdemir, A., Nursaçan, M. N. N., & Nursaçan, İ. (2014). 2014-2018 yılları arasında nesnelerin interneti (IoT) üzerine bir literatür taraması [A review of literature on internet of things (IoT) between 2014-2018]. Bandırma Onyedi Eylül Üniversitesi Sosyal Bilimler Araştırmaları Dergisi, 1(2), 1-22.
  • Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational psychology review, 18(4), 315-341.
  • Ray, S., Jin, Y., & Raychowdhury, A. (2016). The changing computing paradigm with Internet of Things: a tutorial introduction. IEEE Des Test, 33(2), 76–96.
  • Saadé, R. G., & Kira, D. (2006). The emotional state of technology acceptance. Issues in Informing Science & Information Technology, 3, 529-539.
  • Saritepeci, M., Yıldız Durak, H., & Durak, A. (2021). Hayat Boyu öğrenme bağlamında endüstri 4.0. In H. Yildiz Durak & M. Saritepeci (Eds.) Dijital Çağda Hayat Boyu Öğrenme (p. 221 -231). Pegem Pub.
  • Stojanović, D., Bogdanović, Z., Petrović, L., Mitrović, S., & Labus, A. (2020). Empowering learning process in secondary education using pervasive technologies. Interactive Learning Environments, 1-14. https://doi.org/10.1080/10494820.2020.1806886
  • Sula, A., Spaho, E., Matsuo, K., Barolli, L., Miho, R., & Xhafa, F. (2013). An IoT-based system for supporting children with autism spectrum disorder. In 2013 Eighth International Conference on Broadband and Wireless Computing, Communication and Applications, pp. 282–289.
  • Şahin, F. (2021). Öğretmen adaylarının bilişim teknolojileri kullanım niyetlerinde duyguların ve temel psikolojik ihtiyaçların rolü: Teknolojinin kabulüne motivasyonel bir yaklaşım [The Role of Emotions and Basic Psychological Needs in Preservice Teachers’ Intention to Use Information Technologies: A Motivational Approach to the Acceptance of Technology]. Unpublished PhD Thesis. Anadolu University, Turkey.
  • Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics (Vol. 5, pp. 481-498). Boston, MA: Pearson.
  • Tondeur, J., Aesaert, K., Prestridge, S., & Consuegra, E. (2018). A multilevel analysis of what matters in the training of pre-service teacher's ICT competencies. Computers & Education, 122, 32-42.
  • Triandis, H. C. (1980). Values, attitudes and interpersonal behavior. Nebraska symposium on motivation, 1979: Beliefs, attitudes, and values. University of Nebraska Press, Lincoln, NE, 195-259.
  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
  • Yildiz Durak, H. (2019). Examining the acceptance and use of online social networks by preservice teachers within the context of unified theory of acceptance and use of technology model. Journal of Computing in Higher Education, 31(1), 173-209.
  • Yildiz Durak, H. (2021a). Modeling of relations between K-12 teachers’ TPACK levels and their technology integration self-efficacy, technology literacy levels, attitudes toward technology and usage objectives of social networks. Interactive Learning Environments, 29(7), 1136–1162.
  • Yildiz Durak, H. (2021b). Preparing pre-service teachers to integrate teaching technologies into their classrooms: Examining the effects of teaching environments based on open-ended, hands-on and authentic tasks. Education and Information Technologies, 26(5), 5365–5387.
  • Zaerov, E., Letskovska, S., Seymenliyski, K., & Simionov, R. (2020, October). PV system monitoring by loT in smart university. In Proceedings of the 9th International Conference on Telecommunications and Remote Sensing (pp. 44–49).
There are 24 citations in total.

Details

Primary Language English
Subjects Studies on Education
Journal Section Articles
Authors

Aykut Durak 0000-0001-7070-9048

Early Pub Date April 30, 2023
Publication Date April 30, 2023
Published in Issue Year 2023

Cite

APA Durak, A. (2023). The Role of Personal Variables and Emotions Related to Preservice Teachers’ Intention to Use Information Technologies in Acceptance of Educational Use of the Internet of Things (IoT). Research on Education and Psychology, 7(Special Issue), 22-32. https://doi.org/10.54535/rep.1210912

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