Development and Validation of the Technology Integration Confidence Scale (TIC-S) Version 3 Instrument for Technology Use and Integration
DOI:
https://doi.org/10.46328/ijte.7166Keywords:
Technology integration, Technology Integration Confidence Scale, Self-efficacy, ISTE Standards for Educators, Item analysis, Instrument validation, Reliability, ValidityAbstract
This instrument development and validation study examined urban K-12 teachers’ self-efficacy in performing technology integration tasks, framed through the lens of Bandura’s (1997) concept of self-efficacy, which is the belief in one’s capability to execute specific actions. The Technology Integration Confidence Scale (TIC-S) version 3 was developed and refined through a pretest, pilot study, and final quantitative investigation to evaluate its psychometric properties. Following pretesting, the instrument’s subscale structure was realigned based on both theoretical foundations and statistical insights. Grounded in the 2017 ISTE Standards for Educators and adapted from Browne’s (2007) TIC-S version 2, the revised survey was administered online to 327 urban Catholic school teachers in Southern California. Participants self-reported their confidence in performing key technology-integrated pedagogical tasks. Statistical procedures, including Cronbach’s alpha and exploratory factor analysis (EFA) using principal component analysis (PCA) with oblique rotation, confirmed the instrument’s reliability and validity. The TIC-S version 3 is both a psychometrically sound research instrument and a practical diagnostic tool for assessing teachers’ readiness to integrate technology into instruction. For practice, results highlight its utility in guiding targeted professional development and supporting teachers in adapting to emerging technologies, including AI-enhanced learning environments. For research, the study supports further validation across diverse contexts, and recommends longitudinal and mixed-methods investigations to examine changes in teacher self-efficacy and its relationship to classroom practice. Overall, TIC-S version 3 provides a meaningful framework for advancing effective technology integration in K–12 education and is affirmed as a tool for future research related to techno-pedagogical applications in education.
References
Amemasor, S. K., Oppong, S. O., Ghansah, B., Benuwa, B.-B., & Essel, D. D. (2025). A systematic review on the impact of teacher professional development on digital instructional integration and teaching practices. Frontiers in Education, 10, 1541031. https://doi.org/10.3389/feduc.2025.1541031
An, Y., & Reigeluth, C. (2012). Creating technology-enhanced, learner-centered classrooms: K–12 teachers’ beliefs, perceptions, barriers, and support needs. Journal of Digital Learning in Teacher Education, 28(2), 54-62. https://doi.org/10.1080/21532974.2012.10784683
Artino, A. R., Jr. (2012). Academic self-efficacy: From educational theory to instructional practice. Perspectives on Medical Education, 1(2), 76-85. https://doi.org/10.1007/s40037-012-0012-5
Bakar, N. S. A., Maat, S. M., & Rosli, R. (2018). A systematic review of teacher’s self-efficacy and technology integration. International Journal of Academic Research in Business and Social Sciences, 8(8), 540–557. https://doi.org/10.6007/ijarbss/v8-i8/4611
Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: Worth Publishers.
Brown, S. A. (2012). Seeing Web 2.0 in context: A study of academic perceptions. Internet and Higher Education, 15(1), 50-57.
Browne, J. M. (2007). Evidence supporting the validity of inferences required by the intended uses of the Technology Integration Confidence Scale (Doctoral dissertation). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/etd/989/
Cardullo, V., Wang, C., Burton, M., & Dong, J. (2021). K-12 teachers’ remote teaching self-efficacy during the pandemic. Research in Innovative Teaching and Learning, 14(1), 32–45. https://doi.org/10.1108/RITL-10-2020-0065
Chiu, T. K. F., Ahmad, Z., & Çoban, M. (2025). Development and validation of teacher artificial intelligence (AI) competence self-efficacy (TAICS) scale. Education and Information Technologies, 30, 6667–6685. https://doi.org/10.1007/s10639-024-13094-z
Choi, S., Jang, Y., & Kim, H. (2023). Influence of pedagogical beliefs and perceived trust on teachers’ acceptance of educational artificial intelligence tools. International Journal of Human–Computer Interaction, 39(4), 910–922. https://doi.org/10.1080/10447318.2022.2075203
Clark, R. C., & Mayer, R. E. (2016). E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning (4th ed.). Hoboken, NJ: Wiley.
Cukurova, M., Miao, X., & Brooker, R. (2023). Adoption of artificial intelligence in schools: Unveiling factors influencing teachers’ engagement [Preprint]. arXiv. https://arxiv.org/abs/2304.00903
Denzine, G. M., Cooney, J. B., & MacKenzie, R. (2005, December). Confirmatory factor analysis of the Teacher Efficacy Scale for prospective teachers. British Journal of Educational Psychology, 75(4), 689-708. doi: 10.1348/000709905X37253
Deye, S. (2015). Harnessing the power of technology in the classroom. Connected Learning: A Primer for State Policymakers (First of four reports). Denver, CO: NCSL. Retrieved from http://www.ncsl.org/Portals/1/Documents/educ/technology_final.pdf
Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255-284. doi: http://dx.doi.org/10.1080/15391523.2010.10782551
Ertmer, P. A., Ottenbreit-Leftwich, A. T., Sadik, O., Sendurur, E., & Sendurur, P. (2012). Teacher beliefs and technology integration practices: A critical relationship. Computers & Education, 59(2), 423-435. doi: 10.1016/j.compedu.2012.02.001
García-Martín, J., Rico, R., & García-Martín, S. (2023). The perceived self-efficacy of teachers in the use of digital tools during the COVID-19 pandemic: A comparative study between Spain and the United States. Behavioral Sciences, 13(3), 213. https://doi.org/10.3390/bs13030213
Gecker, J. (2025, June 25). How ChatGPT and other AI tools are changing the teaching profession. AP News. Retrieved from https://apnews.com/article/ai-chatgpt-teacher-chatbot-b1630bc549e9044d1e3bbcc060fb422c
Gilakjani, A. P. (2013). Factors contributing to teachers’ use of computer technology in the classroom. Universal Journal of Educational Research, 1, 262–267. doi: 10.13189/ujer.2013.010317
Gomez, F. C., Jr., Trespalacios, J., Hsu, Y.-C., & Yang, D. (2022). Exploring teachers’ technology integration self-efficacy through the 2017 ISTE standards. TechTrends, 66, 159–171. https://doi.org/10.1007/s11528-021-00639-z
Guo, S., Shi, L., & Zhai, X. (2024). Validating an instrument for teachers’ acceptance of artificial intelligence in education [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2406.10506
Guo, S., Zheng, Y., & Zhai, X. (2024). Artificial intelligence in education research during 2013–2023: A review based on bibliometric analysis. Education and Information Technologies, 29, 16387–16409. https://doi.org/10.1007/s10639-024-12491-8
Harris, J. (2019). Indicators of teacher development with digital technologies. Journal of Digital Learning in Teacher Education, 35(2), 85-98. https://doi.org/10.1080/21532974.2018.1562326
Harris, J., Grandgenett, N., & Hofer, M. (2010). Testing a TPACK-based technology integration assessment rubric. In C. D. Maddux, D. Gibson, & B. Dodge (Eds.), Research highlights in technology and teacher education 2010 (pp. 323–331). Chesapeake, VA: Society for Information Technology & Teacher Education.
Harris, M. (2019). Am I a tech-savvy teacher (Blog)? The International EdTech Blog with Matt Harris, ED.D. Retrieved from https://mattharrisedd.com/2019/12/04/tech-savvy-teacher-2/?utm_source=ReviveOldPost&utm_medium=social&utm_campaign=ReviveOldPost
Hatcher, L. (2013). Advanced statistics in research: Reading, understanding, and writing up data analysis results. Saginaw, MI: Shadow Finch Media.
Houghton Mifflin Harcourt (HMH). (2018). 4th Annual Educator Confidence Report (2018-2019). Boston, MA: Houghton Mifflin Harcourt. Retrieved from https://www.hmhco.com/forms/educator-confidence-report
Howard, S. K. (2013). Risk-aversion: Understanding teachers’ resistance to technology integration. Technology, Pedagogy and Education, 22(3), 357-372. https://doi.org/10.1080/1475939X.2013.802995
Hughes, J. E. (2005). The role of teacher knowledge and learning experiences in forming technology integrated pedagogy. Journal of Technology and Teacher Education, 13(2), 377–402.
International Society for Technology in Education. (2017). ISTE Standards for Educators. Retrieved from https://www.iste.org/standards/for-educators
International Society for Technology in Education. (2024, February 23). Artificial intelligence in education. Retrieved from https://www.iste.org/ai
Israel, G. D. (2003). Determining sample size (Fact Sheet PEOD-6). University of Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, EDIS.
Johnson, K. (2023, September 15). Teachers are going all in on generative AI. Wired. Retrieved from https://www.wired.com/story/teachers-are-going-all-in-on-generative-ai/
Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36. https://doi.org/10.1007/BF02291575
Kay, R. H. (2006). Evaluating strategies used to incorporate technology into preservice education: A review of the literature. Journal of Research on Technology in Education, 38(4), 383-408.
Kimmons, R. (2012). PICRAT Matrix: A matrix to help guide technology integration practices [Blog]. Royce Kimmons: Understanding Digital Participation Divides. Retrieved from http://roycekimmons.com/tools/picrat
Koehler, M. J., & Mishra, P. (2009). What is technological pedagogical content knowledge (TPACK)? Contemporary Issues in Technology and Teacher Education, 9(1), 60-70.
Koh, J. H. L., & Frick, T. W. (2009). Teachers' Sense of Efficacy for Technology Integration Scale. Journal of Educational Computing Research, 41(3), 247–271. doi 10.2190/EC.41.3.b.
Liu, F., Ritzhaupt, A. D., Dawson, K., & Barron, A. E. (2017). Explaining technology integration in K-12 classrooms: A multilevel path analysis model. Educational Technology, Research, and Development, 65(4), 795-813. doi: http://dx.doi.org/10.1007/s11423-016-9487-9
Lomax, R. G., & Hahs‐Vaughn, D. L. (2012). An introduction to statistical concepts (3rd ed.). New York, NY: Routledge.
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054.
Muir, M., Knezek, G., & Christensen, R. (2004). The power of one to one: Early findings from the Maine Learning Technology Initiative. Learning and Leading with Technology, 32(3), 6-11.
Nazaretsky, T., Ariely, M., Cukurova, M., & Alexandron, G. (2022). Teachers’ trust in AI-powered educational technology and a professional development program to improve it. British Journal of Educational Technology, 53(6), 1468–1483. https://doi.org/10.1111/bjet.13232
Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York, NY: McGraw-Hill.
Ofgang, E. (2025, August 11). How AI has changed your teaching. Tech & Learning. Retrieved from https://www.techlearning.com/news/how-ai-has-changed-your-teaching
Paus-Hasebrink, I., Wijnen, C. W., & Jadin, T. (2010). Opportunities of Web 2.0: Potentials of learning. International Journal of Media & Cultural Politics, 6(1), 45-62. doi:10.1386/macp.6.1.45/1
Puentedura, R. R. (2006). Transformation, technology, and education. Retrieved from http://hippasus.com/resources/tte/
Quiroz, J., Manzanero, O., Vairez, M. R., Jr., Gomez, F. C., Jr., & Elliott, R. A. D. (2024). Teachers’ self-efficacy, psychological well-being and apprehensions during the COVID-19 pandemic in Belize. Journal of Belizean Research, 2(1). https://jobr.ub.edu.bz/index.php/ubrj/article/view/32
Rabaglietti, E., Lattke, L. S., Tesauri, B., Settanni, M., & De Lorenzo, A. (2021). A balancing act during COVID-19: Teachers’ self-efficacy, perception of stress in the distance learning experience. Frontiers in Psychology, 12, 644108. https://doi.org/10.3389/fpsyg.2021.644108
Rajapakse, C., Ariyarathna, W., & Selvakan, S. (2024). A self-efficacy theory-based study on the teachers’ readiness to teach artificial intelligence in public schools in Sri Lanka [Preprint]. arXiv. https://arxiv.org/abs/2412.19425
Raosoft. (2004). Sample size calculator. Retrieved from http://www.raosoft.com/samplesize.html
Ruel, E., Wagner, W. E., III, & Gillespie, B. J. (2016). The practice of survey research: Theory and applications. Thousand Oaks, CA: Sage.
Sadaf, A., Newby, T., & Ertmer, P. (2016). An investigation of the factors that influence preservice teachers’ intentions and integration of Web 2.0 tools. Educational Technology Research & Development, 64(1), 37-64. doi:10.1007/s11423-015-9410-9
Seifert, T. (2019). Customized consultation to enhance teacher educators’ techno-pedagogical skills. In A. Elçi, L. L. Beith, & A. Elçi (Eds.), Handbook of research on faculty development for digital teaching and learning (pp. 99-118). IGI Global. https://doi.org/10.4018/978-1-5225-8476-6.ch006
Sellami, A., Santhosh, M. E., Michaleczek, I., Alazaizeh, M., & Madad, J. (2024). Unveiling teachers’ instructional self-efficacy in science, mathematics, and technology: Personal and contextual influences. Canadian Journal of Science, Mathematics and Technology Education, 24, 418–438. https://doi.org/10.1007/s42330-025-00359-z
Sokoloff, N. (2025, May 4). ‘AI is already here’: Why some Connecticut school districts are embracing AI in the classroom. CT Insider. Retrieved from https://www.ctinsider.com/news/education/article/ai-education-ct-schools-east-hartford-lebanon-tech-20302119.php
Straub, E. T. (2009). Understanding technology adoption: Theory and future directions for informal learning. Review of Educational Research, 79(2), 625-649.
Tamim, R. M., Bernard, R. M., Borokhovski, E., Abrami, P. C., & Schmid, R. F. (2011). What forty years of research says about the impact of technology on learning: A second-order meta-analysis and validation study. Review of Educational Research, 81(1), 4-28.
Thakur, P. (2015). Preparing teachers for techno-pedagogical skills: A training module for professional development. International Journal of Multidisciplinary Approach & Studies, 2(6), 79-91.
Tomlinson, C. A. (2017). Let’s celebrate personalization: But not too fast. Educational Leadership, 74(6), 10-15. Retrieved from http://www.ascd.org/el/articles/lets-celebrate-personalization-but-not-too-fast
Tweed, S. R. (2013). Technology implementation: Teacher age, experience, self-efficacy, and professional development as related to classroom technology integration (Doctoral dissertation). East Tennessee State University, Johnson City, TN. Retrieved from https://dc.etsu.edu/cgi/viewcontent.cgi?article=2266&context=etd
Viberg, O., Cukurova, M., Feldman-Maggor, Y., Alexandron, G., Shirai, S., Kanemune, S., Wasson, B., Tømte, C., Spikol, D., Milrad, M., Coelho, R., & Kizilcec, R. F. (2023). What explains teachers’ trust in AI-EdTech across six countries? [Preprint]. International Journal of Artificial Intelligence in Education. Advance online publication. https://doi.org/10.1007/s40593-024-00433-x
Wang, J., Ertmer, P. A., & Newby, T. J. (2004). The Technology Integration Self-Efficacy Scale. Journal of Research on Technology in Education, 36(3), 219–229. doi 10.1080/15391523.2004.10782414
Williams, M. K., Christensen, R., McElroy, D., & Rutledge, D. (2023). Teacher self-efficacy in technology integration as a critical component in designing technology-infused teacher preparation programs. Contemporary Issues in Technology and Teacher Education, 23(1). https://citejournal.org/volume-23/issue-1-23/general/teacher-self-efficacy-in-technology-integration-as-a-critical-component-in-designing-technology-infused-teacher-preparation-programs
Windschitl, M., & Sahl, K. (2002). Tracing teachers’ use of technology in a laptop computer school: The interplay of teacher beliefs, social dynamics, and institutional culture. American Educational Research Journal, 39(1), 165-205. doi: https://doi.org/10.3102/00028312039001165
Wozney, L., Venkatesh, V., & Abrami, P. C. (2006). Implementing computer technologies: Teachers’ perceptions and practices. Journal of Technology and Teacher Education, 14(1), 173-207.
Yang, X., & Du, J. (2024). The effect of teacher self-efficacy, online pedagogical and content knowledge, and emotion regulation on teacher digital burnout: A mediation model. BMC Psychology, 12, Article 51. https://doi.org/10.1186/s40359-024-01540-z
Zeng, Q., Wang, X., & Li, W. (2022). The relationship between teachers’ information technology integration self-efficacy and TPACK: A meta-analysis. Frontiers in Psychology, 13, 1091017. https://doi.org/10.3389/fpsyg.2022.1091017
Zhou, X., Shu, L., Xu, Z., & Padrón, Y. (2023). The effect of professional development on in-service STEM teachers’ self-efficacy: A meta-analysis of experimental studies. International Journal of STEM Education, 10, Article 37. https://doi.org/10.1186/s40594-023-00422-x
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