Measuring ICT orientation: Scale development & validation
- 63 Downloads
This paper attempts to measure ICT orientation of higher education teachers in Indian context. The study has identified 4 factors of ICT orientation and examined their impact on Job performance. To generate the items, their purification and validation this study has adopted well accepted and renowned scale development procedures by Churchill (Journal of Marketing Research, 16(1), 64–73, 1979) and Hinkin (Organizational Research Methods, 1(1), 104–121, 1995). A one way ANOVA test is applied to test the relationship between 4 factors of ICT orientation and the demographics of respondents. The findings of this study present a 15 item 4 factor scale measuring ICT orientation of teachers among which “advantage” emerged out to be a significant factor. The study further highlighted that ICT orientation has a direct and positive relationship with job performance. This study is the foremost study, which has developed a valid and reliable scale for measuring the ICT orientation of teachers in Indian context.
KeywordsICT orientation SEM ICT skills Scale validation Job performance
This research work required a lot of effort. It required high concentration and the whole hearted support of people from industry and academics without which it would not have been possible to accomplish. We therefore express our sincere thanks and gratitude to all the people who have been associated with the research paper
- Ahmad, A. R. (2012). High job performance through Information and communication technology: skill, knowledge, attitude and readiness among academicians in public and private higher learning institutions in Malaysia. International Journal of Computer Science Issue, 9(2), 130–136.Google Scholar
- Aslan, A., & Zhu, C. (2016). Investigating variables predicting Turkish pre- service teachers’ integration of ICT into teaching practices. British Journal of Educational Technology. https://doi.org/10.1111/bjet.12437/full.
- Bhat, S. A., & Beri, A. (2016a). ICT immersion in different domains of teaching profession-a literature review. International Journal of Indian Psychology, 3(3), 156–166.Google Scholar
- Bhat, S. A., & Beri, A. (2016b). ICT orientation: development and validation of ICTOR scale for teachers. Man in India, 96(9), 3123–3134.Google Scholar
- Blau, I., & Antonovsky, A. (2009). Teachers' openness to changes in professional and personal life. Unpublished work, Department of Education and Psychology, Open University of Israel. Ra'anana, Israel.Google Scholar
- Blau, I., & Peled, Y. (2012). Teachers’ openness to change and attitudes towards ICT: comparison of laptop per teacher and laptop per student programs. Interdisciplinary Journal of e-Learning and Learning Objects, 8(1), 73–82.Google Scholar
- Christensen, R. W., & Knezek, G. A. (2009). Construct validity for the teachers’ attitudes toward computers questionnaire. Journal of Computing in Teacher Education, 25(4), 143–155.Google Scholar
- Costello, A. B., & Osborne, J. W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical assessment, research & evaluation, 10(7), 1–9Google Scholar
- Fluck A. & Dowden T. (2009). Can new teachers be ICT change-agents. Paper presented at Australian Association for Research in Education International Conference, Canberra. Available at: https://eprints.usq.edu.au/23955/1/Fluck_Dowden_AARE2009_PV.pdf. Accessed 28 Oct 2016.
- Gulbahar, Y., & Guven, I. (2008). A survey on ICT usage and the perceptions of social studies teachers in Turkey. Journal of Educational Technology & Society, 11(3), 37–51.Google Scholar
- Hair, J. F., Anderson, R. E., Tatham, R. L. & Black, W. C. (1998). Multivariate data analysis, 5th ed., Prentice-Hall, Englewood Cliffs.Google Scholar
- Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis – A global perspective (7th ed.). Upper Saddle River: Pearson Prentice Hall.Google Scholar
- Joreskog, K. G., & Sorbom, D. (2004). LISREL 8.7. Chicago: Scientific Software International Inc..Google Scholar
- Kaluyu, V., Wambugu, H., & Oduor, C. (2015). Impact of proficiency in information communication technology skills on job performance: a case of university quality assurance officers in Kenya. International Journal of Economics, Commerce and Management, 3(2), 1–12.Google Scholar
- Keith, T. Z. (2005). Multiple regression and beyond. Boston: Pearson.Google Scholar
- Kumar, P. G., & Ratnakar, R. (2011). A scale to measure farmers’ attitude towards ICT-based extension services. Indian Research Journal of Extension, 11(1), 109–112.Google Scholar
- Lee, S., Chang, S., Hou, J. & Lin, C. (2008). Night market experience and image of temporary residents and foreign visitors. International Journal of Culture, Tourism and Hospitality Research,2(3), 217–233.Google Scholar
- Leng, N. W. (2011). Reliability and validity of an information and communications technology attitude scale for teachers. Asia-Pacific Education Researcher (De La Salle University Manila), 20(1), 162–170.Google Scholar
- MacKeogh, K. (2003). Student perceptions of the use of ICTs in European education: Report of a survey’, available at: http://doras.dcu.ie/569/1/mackeogh_icts_european_education.pdf. Accessed 20 Oct 2016.
- Mehra, V., & Far, Z. N. (2013). A scale to measure university teachers’ attitude towards ICT. International Journal of Teacher Educational Research, 2(7), 10–25.Google Scholar
- Ministry of Education. (2006). Education development blueprint 2006–2010. Kuala Lumpur: Ministry of Education.Google Scholar
- Nunnally, J. C. (1978). Psychometric theory. New York: McGraw-Hill.Google Scholar
- Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.Google Scholar
- Oye, N. D., Iahad, N. A., & Rabin, Z. A. (2011). A model of ICT acceptance and use for teachers in higher education institutions. International Journal of Computer Science & Communication Networks, 1(1), 22–40.Google Scholar
- Papaioannou, P., & Charalambous, K. (2011). Principals’ attitudes towards ICT and their perceptions about the factors that facilitate or inhibit ICT integration in primary schools of Cyprus. Journal of Information Technology Education: Research, 10(1), 349–369.Google Scholar
- Parsuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12–40.Google Scholar
- Pathak, R. P., & Chaudhary, J. (2012). Eduction technology. India: Pearson Publishers.Google Scholar
- Sarkar, S. (2012). The role of information and communication technology (ICT) in higher education for the 21st century. Science, 1(1), 30–41.Google Scholar
- Smalley, N., Graff, M., & Saunders, D. (2001). A revised computer attitude scale for secondary school students. Education and Psychology, 18(3), 47–57.Google Scholar
- Sonnentag, S., Volmer, J., & Spychala, A. (2008). Job performance. In The sage handbook of organizational behavior, 1, pp. 427–447.Google Scholar
- Tabachnick, B. G., & Fidell, L. S. (1996). Using multivariate statistics (3rd ed.). New York: Harper Collins College.Google Scholar
- Tinio, V. L. (2003). ICT in education. Available at: E-primers for information economy, society and policy. http://www.E-primers.org/ICT/page2.asp . Accessed 2 Nov 2016.
- Tondeur, J., Aesaert, K., Pynoo, B., Braak, J., Fraeyman, N., & Erstad, O. (2015). Developing a validated instrument to measure preservice teachers’ ICT competencies: Meeting the demands of the 21st century. British Journal of Educational Technology. https://doi.org/10.1111/bjet.12380/abstract.
- Usluel, Y. K., Askar, P., & Bas, T. (2008). A structural equation model for ICT usage in higher education. Journal of Educational Technology & Society, 11(2), 262–273.Google Scholar
- Vigneshwaran, & Dange, J. K. (2013). Development of a scale to measure self-confidence in ict integration of secondary school teachers. International Multidisciplinary e-Journal, 2(1), 103–108.Google Scholar