Innovative Behavior: Components, Causal Factors, and Developmental Guidelines for Secondary School Teachers
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Abstract
The objectives of this study were: 1) to develop the components of innovative behavior among secondary school teachers, 2) to construct a causal model of innovative behavior among secondary school teachers, and 3) to identify guidelines for enhancing innovative behavior among secondary school teachers. The research was conducted in three phases. In Phase 1, the components of innovative behavior were developed using qualitative methods. Seven key informants were purposively selected, and data were collected through interviews and analyzed using content analysis. In Phase 2, a causal model of innovative behavior was developed. The sample consisted of 569 secondary school teachers. Data were collected using a five-point rating scale questionnaire and analyzed through Structural Equation Modeling (SEM). In Phase 3, guidelines for enhancing innovative behavior were explored through semi-structured interviews with five experts in educational innovation. The data were analyzed using content analysis and analytic induction.
The findings indicated that innovative behavior comprised four components: Opportunity Seeking, Creative Thinking, Thought Leadership, and Innovative Application. The structural model of innovative behavior demonstrated a good fit with the empirical data ((849) = 1054.56, CFI = 0.994, TLI = 0.994, RMSEA = 0.021, SRMR = 0.046). The proposed guidelines for enhancing teachers’ innovative behavior included staying informed about educational trends and innovations, designing new instructional activities or learning materials, serving as role models in implementing new ideas within schools, and experimenting with new teaching tools and instructional methods in authentic classroom contexts.
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References
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Creswell, J. W., & Poth, C. N. (2016). Qualitative inquiry and research design: Choosing among five approaches. Los Angeles: Sage publications.
De Ayala, R. J. (2013). The theory and practice of item response theory. Washington, D.C: Guilford Publications.
De Jong, J. P. J., & Den Hartog, D. N. (2010). Measuring innovative work behaviour. Creativity and Innovation Management, 19(1), pp. 23-36.
Fullan, M. (2016). The new meaning of educational change. New York: Teachers college press.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). New York: Cengage Learning.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), pp. 1-55.
Kaufman, J. C., Beghetto, R. A., & Roberts, A. M. (2022). Creativity in the schools: Creativity models and new directions. In Handbook of positive psychology in schools (pp. 335-345). New York: Routledge.
Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). New York: Guilford Press.
Leithwood, K., & Jantzi, D. (2005). A review of transformational school leadership research 1996–2005. Leadership and Policy in Schools, 4(3), pp. 177-199.
Lemmetty, S., & Collin, K. (2020). Self-directed learning as a practice of workplace learning: Interpretative repertoires of self-directed learning in ICT work. Vocations and Learning, 13(1), pp. 47-70.
Liu, S., & Szabo, Z. (2009). Teachers’ attitudes toward technology integration in schools: A four-year study. Computers in the Schools, 26(4), pp. 241-262.
Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47(2), pp. 149-174.
Morris, T. H., & König, P. D. (2020). Self-directed experiential learning to meet ever-changing entrepreneurship demands. Education+ Training, 63(1), pp. 23-49.
OECD. (2022). Teaching in Focus: Fostering Innovation in Schools. Paris: OECD Publishing.
Önhon, Ö. (2019). The relationship between organizational climate for innovation and employees’ innovative work behavior: ICT sector Turkey. Vezetéstudomány-Budapest Management Review, 50(11), pp. 53-64.
Parker S.K., Williams H.M., & Turner N. (2006). Modeling the antecedents of proactive behavior at work. Journal of Applied Psychology, 91(3), pp. 636-652.
Shanker, R., Bhanugopan, R., Van der Heijden, B. I., & Farrell, M. (2017). Organizational climate for innovation and organizational performance: The mediating effect of innovative work behavior. Journal of Vocational Behavior, 100, pp. 67-77.
Soper, D. S. (2024). A-priori sample size calculator for structural equation models [Computer Software]. https://www.danielsoper.com/statcalc
Thurlings, M., Evers, A. T., & Vermeulen, M. (2015). Toward a model of explaining teachers’ innovative behavior: A literature review. Review of Educational Research, 85(3), pp. 430-471.
Tsegaye, W. K., Su, Q., & Malik, M. (2020). The quest for a comprehensive model of employee innovative behavior: The creativity and innovation theory perspective. The Journal of Developing Areas, 54(2), pp. 105-121.
Tura, B., & Akbaşlı, S. (2022). Factors affecting innovative work behaviors of teachers from the perspective of organizational Intelligence. Eğitimde Nitel Araştırmalar Dergisi, 29(2), pp. 203-234.
UNESCO. (2023). Reimagining Our Futures Together: A New Social Contract for Education. Paris: UNESCO Publishing.
Zhong, Z., Hu, D., Zheng, F., Ding, S., & Luo, A. (2018). Relationship between information-seeking behavior and innovative behavior in Chinese nursing students. Nurse Education Today, 63, pp. 1-5.
