Document Type : Research Paper


Department of English Language and Literature, University of Isfahan, Isfahan, Iran


Adaptive teaching addresses students’ diversity and their immediate learning needs. Particularly, in the high-interactive context of English teaching, fostering adaptive teaching in teacher professional development programs not only stimulates teacher change at the micro level, but also facilitates implementing the organizational and curricular innovations imposed by authorities at the macro level. The current English teaching literature lacks a measure for evaluating and fostering adaptive teaching within higher education. Hence, within the present study, the Interconnected Model of Teacher Professional Growth (IMTPG) was adapted and validated as a measure for evaluating and fostering teacher adaptability for 183 international English teachers in higher education. Structural Equation Modelling (SEM) was employed for validating two different enactment and reflection links in the original IMTPG, and the final adapted IMTPG for adaptive teaching (At-IMTPG) was proposed. The AT-IMTPG can be applied for evaluating how adaptive English teachers are, seeking to resolve the problem of implementing educational innovations by English teachers in higher education. It can also be used to design teacher professional growth programs for fostering adaptive teaching within English teaching higher education. Such a change in the classroom level is hoped to be translated into an educational change in English teaching higher education.


Main Subjects

Anderson, L. W. (1979). Adaptive education, Educational Leadership, 37 (2)140-143.
Anderson, J. C., & Gerbing, D. W. (1984). The Effect of Sampling Error on Convergence, Improper Solutions, and Goodness-of-Fit Indices for Maximum Likelihood Confirmatory Factor Analysis. Psychometrika, 49, 155-173.
Bentler, P. M., & Chou, C. P. (1987). Practical Issues in Structural Modeling. Sociological Methods & Research, 16, 78-117.
Boomsma, A., & Hoogland, J. J. (2001). The Robustness of LISREL Modeling Revisited. In R. Cudeck, S. du Toit, & D. Sörbom (Eds.), Structural Equation Models: Present and Future. A Festschrift in Honor of Karl Jöreskog (pp. 139-168). Scientific Software International.
Boomsma, A. (1985). Nonconvergence, Improper Solutions, and Starting Values in LISREL Maximum Likelihood Estimation. Psychometrika, 50, 229-242.
Borich, G. D. (2011). Effective teaching methods. Pearson Education, Inc.
Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How people learn: Brain, mind, experience, and school. National Academies Press.
Chou, C. P. & Bentler, P. M. (1995). Estimates and tests in structural equation modeling. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 37-55). SAGE Publications.
Clarke, D., & Hollingsworth, H. (2002). Elaborating a model of teacher professional growth. Teaching and Teacher Education, 18(8), 947-967.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Association.
Collie, R. J. and Martin, A. J. (2017). Teachers' sense of adaptability: Examining links with perceived autonomy support, teachers' psychological functioning, and students' numeracy achievement. Learning and Individual Differences, 55 (2017) 29–39.
Collie, R. J., Holliman, A. J., & Martin, A. J. (2016). Adaptability, engagement and academic achievement at university. Educational Psychology, 37(5).
Darling-Hammond, L., & Bransford, J. (Eds.). (2005). Preparing teachers for a changing world: What teachers should learn and be able to do. JosseyBass.
David, C. (2013). Innovation in Language Teaching and Learning. In C. A. Chapelle (Ed.), The Encyclopedia of Applied Linguistics, Wiley-Blackwell.
Dewey, J. (1910). How we think: A restatement of the relation of reflective thinking to the educative process. D. C. Heath.
Ding, L., Velicer, W. F., & Harlow, L. L. (1995). Effects of Estimation Methods, Number of Indicators per Factor, and Improper Solutions on Structural Equation Modeling Fit Indices. Structural Equation Modeling: A Multidisciplinary Journal, 2, 119-143.
Duffy, G. G., Miller, S. D., Parsons, S. A., & Meloth, M. (2009). Teachers as metacognitive professionals. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Handbook of metacognition in education (pp. 240–256). Erlbaum.
El Masry, T., & Alzaanin, E. I. (2021). Uncovering New Paths to Adaptation: A Case Study of Malaysian English as a Second Language Pre-service Teachers. Arab World English Journal, 12 (1) 421-442.
Fan, X., Thompson, B. & Wang L. (1999). Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes. Structural Equation Modeling, 6(1), 56–83.
Farrell, T. S. (2006). Reflective practice in action: A case study of a writing teacher’s reflections on practice. TESL Canada Journal, 23(2).
Gallagher, M. A., Parsons, S. A., & M. Vaughn (2020). Adaptive teaching in mathematics: a review of the literature, Educational Review, 74(2)
Goei, S. L., & Verhoef, N. (2015). Lesson study as a tool for teacher learning: the context of combinatorial reasoning problems. Paper presented at 16th Biennial Conference of the European Association for Research in Learning and Instruction (EARLI) 2015, Limassol, Cyprus.
Gun, B. (2014). Making Sense of Experienced Teachers’ Interactive Decisions: Implications for Expertise in Teaching, International Journal of Instruction, 7(1), 75-90.
Gungor, M. N. (2016). Turkish Pre-service Teachers’ Reflective Practices in Teaching English to Young Learners. Australian Journal of Teacher Education, 41(2), 136-151.
Haghi, S., Aliakbari, M., & Yasini, A. (2023). EFL Teachers’ Individual Development Planning Model: A Data-Driven Approach. Journal of Teaching English as a Second Language Quarterly, 42 (1), 1-28.
Hammond, J. (2016). Dialogic space: intersections between dialogic teaching and systemic functional linguistics, Research Papers in Education, 31(1), 5-22,
Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge.
Heckhausen, J., Wrosch, C., & Schulz, R. (2010). A motivational theory of life-span development. Psychological Review, 117, 32–60.
Hoffman, J. V., & Duffy, G. G. (2016). Does thoughtfully adaptive teaching actually exist? A challenge to teacher educators. Theory Into Practice, 55, 172–179.
Holliman, A. J., Martin A. J. & Collie R. J. (2018): Adaptability, engagement, and degree completion: a longitudinal investigation of university students, Educational Psychology, 38(6),
Hu, L. T. and Bentler P. M. (1995). Evaluating model fit. In: R. H. Hoyle (Ed.). Structural equation modeling: Concepts, issues, and applications. Sage, 76–99.
Jackson, D. L. (2001). Sample Size and Number of Parameter Estimates in Maximum Likelihood Confirmatory Factor Analysis: A Monte Carlo Investigation. Structural Equation Modeling, 8, 205-223.
Jacobs, V. R., Lamb, L. C., & Philipp, R. A. (2010). Professional noticing of children’s mathematical thinking. Journal for Research in Mathematics Education, 41(2), 169–202.
Janssen, O. (2003). Innovative behavior and job involvement at the price of conflict and less satisfactory relations with co-workers. Journal of Occupational and Organizational Psychology, 76, 347–364.
Jeannin, L. & P. Hallinger (2018). Exploring the need to contextualize professional development programs for university lecturers: A case study in Thailand. The Independent Journal of Teaching and Learning, 13 (2), 98-112.
Johnson, N. (1996). School leadership and the management of change. IARTV Seminar Series, No. 55, July.
Justi, R., & Van Driel, J. (2006). The use of the interconnected model of teacher professional growth for understanding the development of science teachers' knowledge on models and modelling. Teaching and Teacher Education, 22(4), 437-450.
Kara, N. and Sevim, N. (2013). Adaptive Learning Systems: Beyond Teaching Machines, Contemporary Educational Technology, 4(2), 108-120.
Kolb, D. (1984). Experiential learning: Experience as the source of learning and development. New Jersey.
Kyriazos, T. A. (2018). Applied Psychometrics: Sample Size and Sample Power Considerations in Factor Analysis (EFA, CFA) and SEM in General. Psychology, 9, 2207-2230.
Lin, X., Schwartz, D. L., & Hatano, G. (2005). Toward teachers’ adaptive metacognition. Educational Psychologist, 40, 245–255.
Loan, N. T. T. (2019). Reflective Teaching in an EFL Writing Instruction Course for Thai Pre-service Teachers, The Journal of Asia TEFL, 16(2), 561-575.
Lomas, L. (2018). Proposed Structural Refinements to the Interconnected Model of Teacher Professional Growth. In Hunter, J., Perger, P., & Darragh, L. (Eds.). Making waves, opening spaces (Proceedings of the 41st annual conference of the Mathematics Education Research Group of Australasia) pp. 495-502. MERGA.
Ma, J., & Ren, S. (2011). Reflective Teaching and Professional Development of Young College English Teachers—From the Perspective of Constructivism, Theory and Practice in Language Studies, 1(2), 153-156,
MacCallum, R. C., Browne, M. W., & Sugawara, H., M. (1996), Power Analysis and Determination of Sample Size for Covariance Structure Modeling, Psychological Methods, 1 (2), 130-49.
Madin, C. V. & Swanto, S. (2019). An Inquiry Approach to Facilitate Reflection in Action Research for ESL Pre-Service Teachers. TEFLIN Journal, 30(1),
Marsh, H. W., & Hau, K. T. (1999). Confirmatory Factor Analysis: Strategies for Small Sample Sizes. Statistical Strategies for Small Sample Research, 1, 251-284.
Marsh, H. W., Hau, K. T., Balla, J. R., & Grayson, D. (1998). Is More Ever too Much? The Number of Indicators per Factor in Confirmatory Factor Analysis. Multivariate Behavioral Research, 33, 181-220.
Martin, A. J., Nejad, H., Colmar, S., & Liem, G. A. D. (2012). Adaptability: Conceptual and empirical perspectives on responses to change, novelty and uncertainty. Journal of Psychologists and Counsellors in Schools, 22(01), 58–81.
Martin, A. J., Nejad, H. G., Colmar, S. H. & Liem, G. A. D. (2013). Adaptability: How students’ responses to uncertainty and novelty predict their academic and non-academic outcomes. Journal of Educational Psychology. 105(3), 728-746.
Martin, A. J., Nejad, H., Colmar, S., Liem, G. A. D. & Collie, R. J. (2015). The role of adaptability in promoting control and reducing failure dynamics: A mediation model. Learning and Individual Differences. 38, 36-43.
Matei, A. and Gogu, M. C. (2018). Adaptive Education – A Systemic View, Proceedings of EDULEARN17 Conference 3rd-5th July 2017, Barcelona, Spain
Munalim, L. O., & Gonong, G. O. (2019). Stances in Student-Teachers’ Spoken Reflection: An Exploratory Linguistic Study to Enhance a Reflection Inventory. Iranian Journal of Language Teaching Research, 7(1), 119-139.
Oo, T. Z. & Habók, A. (2020). The Development of a Reflective Teaching Model for Reading Comprehension in English Language Teaching, International Electronic Journal of Elementary Education, 13(1), 127-138.
Parsons, S. A., & Vaughn, M. (2016). Toward adaptability: Where to from here? Theory Into Practice, 55, 267–274.
Parsons, S. A., Vaughn, M., Scales, R. Q., Gallagher, M. A., Parsons, A. W., Davis, S. D., & Allen, M. (2018). Teachers’ instructional adaptations: A research synthesis. Review of Educational Research, 88(2), 205–242.
Ratminingsih, N. M., Artini, L. P., & Padmadewi, N. N. (2018). Incorporating self and peer assessment in reflective teaching practices. International Journal of Instruction, 10(4), 165–184.
Richards, J. C., & Lockhart, C. (1996). Reflective Teaching in Second Language Classrooms. Cambridge University Press.
Salih, A. A. & Omar, L. I. (2022). Reflective Teaching in EFL Online Classrooms: Teachers’ Perspective. Journal of Language Teaching and Research, 13(2), 261-270,
Schatzman, L. (1991). Dimensional analysis: Notes on an alternative approach to the grounding of theory in qualitative research. In: Maines D. R. (Ed.): Social Organization and Social Process: Essays in Honor of Anslem Stauss. Aldin de Gruyter, 303–314.
Snow-Gerono, J. L. (2008). Locating supervision- a reflective framework for negotiating tensions within conceptual and procedural foci for teacher development. Teaching and Teacher Education, 24(6), 1502–1515.
Soodmand Afshar, H., & Ghasemi, Sh. (2018). Developing and validating a model for exploring Iranian EFL teachers' perception of professional development. Journal of Teaching English as a Second Language Quarterly, 37(3), 169-210.
Soper, D. S. (2020). A-Priori Sample Size Calculator for Structural Equation Models [Software]. http://wwwdanielsopercom/statcalc.
Sprinthall, N. A., Reiman, A. J., & Thies-Sprinthall, L. (1996). Teacher professional development. In J. Sikula, T. J. Buttery, & E. Guyton (Eds.), Handbook of research on teacher education. Macmillan.
Stevens, J. P. (2009). Applied multivariate statistics for the social sciences (5th ed.). Routledge Academic.
Tabachnick, B. G., & Fidell, L. S. (2007). Experimental Design Using ANOVA. Duxbury.
Tanaka, J. S. (1987). How Big Is Big Enough? Sample Size and Goodness of Fit in Structural Equation Models with Latent Variables. Child Development, 58, 134-146.
Tomasik, M., Silbereisen, R., & Heckhausen, J. (2010). Is it adaptive to disengage from demands of social change? Adjustment to developmental barriers in opportunity-deprived regions. Motivation and Emotion, 34, 384–398.
Thurlings, M., Evers, A. T., & Vermeulen, M. (2015). Toward a model of explaining teachers’ innovative behavior: A literature review. Review of Educational Research, 85, 430–471.
Vagle, M. (2016). Making pedagogical adaptability less obvious. Theory Into Practice, 55, 207–216.
van Driel, J. H., Meirink, J. A., van Veen, K. & Zwart, R. C. (2012). Current trends and missing links in studies on teacher professional development in science education: a review of design features and quality of research, Studies in Science Education, 48(2), 129-160,
Voon, X. P., Wong, L. H., & Looi, C. K. (2018). Analyzing the mediating processes of teacher’s growth: A case study in a seamless inquiry science learning environment. In Jong, M. S. Y., Shih, J. L., Looi, C. K., Huang, M. X., Xie, Y. R., Zhang, Y., Sun, D., Kuo, R., Tan, S. C., Lau, W., Xie, H., Jiang, B., Wang, M., Tu, S., Jiang, M., Geng, J., & Zheng, Y. X. (Eds.), Proceedings of the 22nd Global Chinese Conference on Computers in Education (GCCCE 2018) (pp. 773-780). Guangzhou: South China Normal University.
West, L., & Staub, F. C. (2003). Content-focused coaching. Transforming mathematics lessons. Heinemann.
Westfall, P. and Henning, K. S. S. (2013) Understanding Advanced Statistical Methods. CRC Press.
Winne, P. H., & Hadwin, A. F. (2008). The weave of motivation and self-regulated learning. In D. H. Schunk, & B. J. Zimmerman (Eds.), Motivation and self-regulated learning: Theory, research, and application (pp. 297–314). Routledge.
Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013). Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety. Educational and Psychological Measurement, 73, 913-934.
Yasaei, H., Alemi, M. & Tajeddin, Z. (2022). English Language Teachers' Autonomy for Professional Development: A Narrative Account of Self-Direction, Capacity, and Freedom. Journal of Teaching English as a Second Language Quarterly, 41(1), 175-212.
Zimmerman, B. J. (2002). Achieving self-regulation: The trial and triumph of adolescence. In F. Pajares & T. Urdan (Eds.), Academic motivation of adolescents. Information Age Publishing.
Zwart, R. C., Wubbels, T., Bolhuis, S. & Bergen, T. C. M. (2008). Teacher learning through reciprocal peer-coaching: an analysis of activity sequence. Teaching and Teacher Education 24, 982-1002.