Skip to main content

Advertisement

SpringerLink
Log in

Factors impacting special education teachers’ acceptance and actual use of technology

  • Published:
Education and Information Technologies Aims and scope Submit manuscript

Abstract

This study uses the Technology Acceptance Model (TAM) to explore the factors that impact special education teachers’ acceptance and actual use of technology. TAM is used as the foundation for generating the hypothesis and developing the conceptual framework for the study. Twenty-four (n=24) special education teachers in a private school in the United Arab Emirates (UAE) participated in this study by answering an electronic questionnaire that included items related to Perceived Usefulness, Perceived Ease of Use, Attitudes Towards Usage, Behavioural Intention to Use, Access to Technology, Job Relevance, Self-Efficacy, Time, and Actual Usage. Preliminary findings indicate that special education teachers have positive attitudes towards the use of technology. Self-efficacy, time and access to technology were found to significantly impact actual use of technology. The research results provide initial insights on special education teachers attitudes towards using technology in their practice as well as the factors that may facilitate or hinder their actual use. Implications for practice and future research are discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Alharbi, S., & Drew, S. (2014). Using the technology acceptance model in understanding academics’ behavioural intention to use learning management systems. International Journal of Advanced Computer Science and Applications, 5(1), 143–155.

    Google Scholar 

  • Almeida, C. M., Jameson, J. M., Riesen, T., & McDonnell, J. (2016). Urban and rural preservice special education teachers' computer use and perceptions of self-efficacy. Rural Special Education Quarterly, 35(3), 12–19.

    Google Scholar 

  • Alshammari, S. H., Ali, M. B., & Rosli, M. S. (2016). The Influences of Technical Support, Self-Efficacy and Instructional Design on the Usage and Acceptance of LMS: A Comprehensive Review. Turkish Online Journal of Educational Technology-TOJET, 15(2), 116–125.

    Google Scholar 

  • Baglama, B., Yikmis, A., & Demirok, M. S. (2017). Special education teachers’ views on using technology in teaching mathematics. European Journal of Special Education Research.

  • Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the association for information systems, 8(4), 3.

    Google Scholar 

  • Bahr, D. L., Shaha, S. H., Farnsworth, B. J., Lewis, V. K., & Benson, L. F. (2004). Preparing Tomorrow's Teachers to Use Technology: Attitudinal Impacts of Technology-supported Field Experience On Pre-service Teacher Candidates. Journal of Instructional Psychology, 31(2).

  • Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological review, 84(2), 191.

    Google Scholar 

  • Baturay, M. H., Gökçearslan, Ş., & Ke, F. (2017). The relationship among pre-service teachers' computer competence, attitude towards computer-assisted education, and intention of technology acceptance. International Journal of Technology Enhanced Learning, 9(1), 1–13.

    Google Scholar 

  • Benbasat, I., & Barki, H. (2007). Quo vadis TAM? Journal of the Association for Information Systems, 8(4), 7.

    Google Scholar 

  • Birkollu, S. S., Yucesoy, Y., Baglama, B., & Kanbul, S. (2017). Investigating the Attitudes of Preservice Teachers Towards Technology Based on Various Variables. TEM Journal, 6(3), 578–583.

    Google Scholar 

  • Bruhn, A. L., Woods-Groves, S., Fernando, J., Choi, T., & Troughton, L. (2017). Evaluating technology-based self-monitoring as a tier 2 intervention across middle school settings. Behavioral Disorders, 42(3), 119–131.

    Google Scholar 

  • Buabeng-Andoh, C. (2012). Factors influencing teachers' adoption and integration of information and communication technology into teaching: A review of the literature. International Journal of Education and Development using Information and Communication Technology, 8(1), 136.

    Google Scholar 

  • Cafiero, J. M. (2012). Technology supports for individuals with autism spectrum disorders. Journal of Special Education Technology, 27(1), 64–76.

    Google Scholar 

  • Chang, J. L., Lieu, P. T., Liang, J. H., Liu, H. T., & Wong, S. L. (2011). Factors influencing technology acceptance decisions. African Journal of Business Management, 5(7), 2901–2909.

    Google Scholar 

  • Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & Education, 59(3), 1054–1064.

    Google Scholar 

  • Conti, D., Commodari, E., & Buono, S. (2017). Personality factors and acceptability of socially assistive robotics in teachers with and without specialized training for children with disability. Life Span and Disability, 20(2), 251–272.

    Google Scholar 

  • Creswell, J. W. (2014). Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research. Pearson publications.

  • Crutchfield, S. A., Mason, R. A., Chambers, A., Wills, H. P., & Mason, B. A. (2015). Use of a self-monitoring application to reduce stereotypic behavior in adolescents with autism: A preliminary investigation of I-Connect. Journal of Autism and Developmental Disorders, 45(5), 1146–1155.

    Google Scholar 

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319–339.

    Google Scholar 

  • El Alfy, S., Gómez, J. M., & Ivanov, D. (2017). Exploring instructors’ technology readiness, attitudes and behavioral intentions towards e-learning technologies in Egypt and United Arab Emirates. Education and Information Technologies, 22(5), 2605–2627.

    Google Scholar 

  • Elkaseh, A. M., Wong, K. W., & Fung, C. C. (2016). Perceived ease of use and perceived usefulness of social media for e-learning in Libyan higher education: a structural equation modeling analysis. International Journal of Information and Education Technology, 6(3), 192.

    Google Scholar 

  • Fullan, M. (2001). The new meaning of educational change (3rd ed.). New York: Teachers College Press.

    Google Scholar 

  • Gorsuch, R. L. (1988). Exploratory factor analysis. In Handbook of multivariate experimental psychology (pp. 231–258). Boston: Springer.

    Google Scholar 

  • Guieford, J. P. (1965). Fundamental Statistics in Psychology and Education. New York: McGram-Hill.

    Google Scholar 

  • Holden, H., & Rada, R. (2011). Understanding the influence of perceived usability and technology self-efficacy on teachers’ technology acceptance. Journal of Research on Technology in Education, 43(4), 343–367.

    Google Scholar 

  • Ismail, S. A. A., Almekhlafi, A. G., & Al-Mekhlafy, M. H. (2010). Teachers’ perceptions of the use of technology in teaching languages in United Arab Emirates’ schools. International Journal for Research in Education, 27(1), 37–56.

    Google Scholar 

  • Juhary, J. (2014). Perceived usefulness and ease of use of the learning management system as a learning tool. International Education Studies, 7(8), 23.

    Google Scholar 

  • Ke, F., & Moon, J. (2018). Virtual collaborative gaming as social skills training for high-functioning autistic children. British Journal of Educational Technology, 49(4), 728–741.

    Google Scholar 

  • Kopcha, T. J. (2012). Teachers' perceptions of the barriers to technology integration and practices with technology under situated professional development. Computers & Education, 59(4), 1109–1121.

    Google Scholar 

  • Koutromanos, G., Styliaras, G., & Christodoulou, S. (2015). Student and in-service teachers’ acceptance of spatial hypermedia in their teaching: The case of HyperSea. Education and Information Technologies, 20(3), 559–578.

    Google Scholar 

  • Leong, L. W., Ibrahim, O., Dalvi-Esfahani, M., Shahbazi, H., & Nilashi, M. (2018). The moderating effect of experience on the intention to adopt mobile social network sites for pedagogical purposes: An extension of the technology acceptance model. Education and Information Technologies, 23(6), 2477–2498.

    Google Scholar 

  • Litz, D., & Scott, S. (2017). Transformational leadership in the educational system of the United Arab Emirates. Educational Management Administration & Leadership, 45(4), 566–587.

    Google Scholar 

  • Liu, S. H. (2012). A multivariate model of factors influencing technology use by preservice teachers during practice teaching. Journal of Educational Technology & Society, 15(4), 137.

    Google Scholar 

  • Masrom, M. (2007). Technology acceptance model and e-learning. Technology, 21(24), 81.

    Google Scholar 

  • Mathieson, K., Peacock, E., & Chin, W. W. (2001). Extending the technology acceptance model: the influence of perceived user resources. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 32(3), 86–112.

    Google Scholar 

  • Narkon, D. E., Wells, J. C., & Segal, L. S. (2011). E-word wall: An interactive vocabulary instruction tool for students with learning disabilities and autism spectrum disorders. Teaching Exceptional Children, 43(4), 38–45.

    Google Scholar 

  • O’Malley, P., Lewis, M. E. B., Donehower, C., & Stone, D. (2014). Effectiveness of using iPads to increase academic task completion by students with autism. Universal Journal of Educational Research, 2(1), 90–97.

    Google Scholar 

  • Okolo, C. M., & Diedrich, J. (2014). Twenty-five years later: How is technology used in the education of students with disabilities? Results of a statewide study. Journal of Special Education Technology, 29(1), 1–20.

    Google Scholar 

  • Oye, N. D., Iahad, N. A., & Rahim, N. A. (2014). The history of UTAUT model and its impact on ICT acceptance and usage by academicians. Education and Information Technologies, 19(1), 251–270.

    Google Scholar 

  • 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.

    Google Scholar 

  • Saddler, B., Newman, D., & Passa, K. (2006, March). The Benefits of Integrating Technology Into Inclusive Classrooms. In Society for Information Technology & Teacher Education International Conference (pp. 4225–4230). Association for the Advancement of Computing in Education (AACE).

  • Sahin, A., Top, N., & Delen, E. (2016). Teachers’ first-year experience with chromebook laptops and their attitudes towards technology integration. Technology, Knowledge and Learning, 21(3), 361–378.

    Google Scholar 

  • Schmidt, M. M. (2014). Designing for learning in a three-dimensional virtual learning environment: A design-based research approach. Journal of Special Education Technology, 29(4), 59–71.

    Google Scholar 

  • Siegel, J., Good, K., & Moore, J. (1996). Integrating technology into educating preservice special education teachers. Action in Teacher Education, 17(4), 53–63.

    Google Scholar 

  • Siyam N. (2018, in press). Special Education Teachers’ Perceptions on Using Technology for Communication Practices. Journal for Researching Education Practice and Theory (JREPT), 1(2), 1–16.

  • Stockless, A. (2018). Acceptance of learning management system: The case of secondary school teachers. Education and Information Technologies, 23(3), 1101–1121.

    Google Scholar 

  • Teo, T. (2008). Pre-service teachers' attitudes towards computer use: A Singapore survey. Australasian Journal of Educational Technology, 24(4).

  • Teo, T. (2009). Examining the Relationship between Student Teachers' Self-Efficacy Beliefs and Their Intended Uses of Technology for Teaching: A Structural Equation Modelling Approach. Turkish Online Journal of Educational Technology-TOJET, 8(4), 7–15.

    Google Scholar 

  • Teo, T. (2011a). Factors influencing teachers’ intention to use technology: Model development and test. Computers & Education, 57(4), 2432–2440.

    Google Scholar 

  • Teo, T. (Ed.). (2011b). Technology acceptance in education. Springer Science & Business Media.

  • Teo, T., Faruk Ursavaş, Ö., & Bahçekapili, E. (2011). Efficiency of the technology acceptance model to explain pre-service teachers' intention to use technology: A Turkish study. Campus-Wide Information Systems, 28(2), 93–101.

    Google Scholar 

  • Tyler-Wood, T. L., Putney, D., & Cass, M. A. (1997). Accessibility: the main factor influencing special education teachers’ perceived level of computer competence. Journal of Computing in Teacher Education, 13(4), 20–24.

    Google Scholar 

  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186–204.

    Google Scholar 

  • Wu, C., & Liu, C. F. (2015). Acceptance of ICT-mediated teaching/learning systems for elementary school teachers: Moderating effect of cognitive styles. Education and Information Technologies, 20(2), 381–401.

    Google Scholar 

  • Xin, Y. P., Tzur, R., Hord, C., Liu, J., Park, J. Y., & Si, L. (2017). An intelligent tutor-assisted mathematics intervention program for students with learning difficulties. Learning Disability Quarterly, 40(1), 4–16.

    Google Scholar 

  • Zhao, Y., Tan, S. H., & Mishra, P. (2001). Teaching and learning: Whose computer is it? Journal of Adolescent & Adult Literacy, 44(4), 348.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. The British University in Dubai, P.O. Box 345015, Dubai, United Arab Emirates

    Nur Siyam

Authors
  1. Nur Siyam
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nur Siyam.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Siyam, N. Factors impacting special education teachers’ acceptance and actual use of technology. Educ Inf Technol 24, 2035–2057 (2019). https://doi.org/10.1007/s10639-018-09859-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10639-018-09859-y

Keywords

Search

Navigation