Adaptation of Teacher Immunity Scale to Turkish: Validity and Reliability Study

Abstract

The literature on teacher identity has yet to fully succeed to address the relationship between personal and contextual factors of teacher identity. Therefore, researchers are attempting to come up with constructs that better account for teacher identity. Accordingly, teacher immunity is a new concept that is a construct teachers develop either productively or maladaptively to protect themselves from the ever-increasing stress and challenges in instructional environments. This study aims to adapt the Language Teacher Immunity Questionnaire (Hiver, 2017) to Turkish culture. Research data were collected from a sample of teachers from various branches working in public and private schools (n=357). The scale adaptation process consists of 20 consecutive steps offered by the researchers based on a comprehensive literature review. When linguistic equivalency was ensured, confirmatory factor analysis was performed for construct validity, and internal consistency was tested through McDonald’s Omega coefficients. After some modifications, the fit indices were above acceptable levels. Also, convergent and divergent validity were examined. According to the results, the Teacher Immunity Scale (TIS) in a 6-point Likert-type format consisting of 32 items gathered under seven factors preserved the original factor structure. This study offers a valid and reliable Turkish adapted form of TIS that can be used with teachers from all branches. Teacher immunity is an emerging concept in teacher identity research, and this adapted instrument allows researchers to research the construct in Turkish.

Keywords

• Teacher immunity
• teacher identity
• resilience
• coping
• burnout.

References

1. Ahmadi, M., Amiryousefi, M., & Hesabi, A. (2020). Role of individual difference variables in EFL teachers’ immunity development. Journal of English Language Teaching and Learning, 12(26), 361–376.
2. Atefi Boroujeni, S., Tahririan, M. H., & Afzali, K. (2021). Exploring the factors triggering Iranian EFL t teachers’ immunity: A mixed-method inquiry. Journal of Applied Linguistics and Applied Literature: Dynamics and Advances, 9(2), 9–33.
3. Beauchamp, C., & Thomas, L. (2009). Understanding teacher identity: An overview of issues in the literature and implications for teacher education. Cambridge Journal of Education, 39(2), 175–189.
4. Beijaard, D., Meijer, P., & Verloop, N. (2004). Reconsidering research on teachers‟ professional identity. Teaching and Teacher Education, 20, 107–128.
5. Beyranvand, S., & Mohamadi Zenouzagh, Z. (2021). Teacher immunity, technological pedagogical content knowledge, and teacher engagement: contributing factors and relations. SN Social Sciences, 1(9), 1–23. https://doi.org/10.1007/S43545-021-00250-2
6. Bollen, K.A. (1989) Structural equations with latent variables. John Wiley and Sons. https://doi.org/10.1002/9781118619179
7. Bracken, B. A., & Barona, A. (1991). State of the art procedures for translating, validating and using psychoeducational tests in cross-cultural assessment. School Psychology International, 12(1-2), 119–132. https://doi.org/10.1177/0143034391121010
8. Brunetti, G. J. (2006). Resilience under fire: Perspectives on the work of experienced, inner city high school teachers in the United States. Teaching and Teacher Education, 22(7), 812–825.

9. Chou, C. P., Bentler, P. M., & Pentz, M. A. (2000). A two-stage approach to multilevel structural equation models: Application to longitudinal data. In T. D. Little, K. U. Schnabel, & J. Baumert (Eds.), Modeling longitudinal and multilevel data, practical issues, applied approaches, and specific examples (pp. 3349). Lawrence Erlbaum Associates.
10. Churchward, P., & Willis, J. (2019). he pursuit of teacher quality: identifying some of the multiple discourses of quality that impact the work of teacher educators. Asia-Pacific Journal of Teacher Education, 47(3), 251–264.
11. Comrey, A. L., & Lee, H. B. (1992). A first course in factor analysis. Erlbaum.
12. Darling-Hammond, L. (1997). The quality of teaching matters most. Journal of Staff Development, 18(1), 38–41.
13. Dörnyei, Z., & Ushioda, E. (2009). Motivation, language identity and the L2 self. Multilingual Matters. https://doi.org/10.21832/9781847691293
14. Ellerton, P. (2022). On critical thinking and content knowledge: A critique of the assumptions of cognitive load theory. Thinking Skills and Creativity, 43, https://doi.org/10.1016/J.TSC.2021.100975
15. Erdem, C. (2020a). Exploring the relationships between possible selves and early teacher identity of Turkish pre-service teachers. Fire: Forum for International Research in Education, 6(3), 94–115.
16. Erdem, C. (2020b). Öğretmen kimliği araştırmalarında yeni bir kavram: Öğretmen etkenliği. Adıyaman University Journal of Educational Sciences, 10(1), 32–55.
17. Ergünay, O., & Adıgüzel, O. C. (2020). Öğretmen Vizyonlarında Değişimler: Üç Aday Öğretmene Yönelik Çoklu Durum Çalışması. Hacettepe University Journal of Education. https://doi.org/10.16986/HUJE.2020064993
18. Field, A. (2013). Discovering statistics using SPSS (4th Edition). SAGE.
19. Friedman, I. A., & Kass, E. (2002). Teacher self-efficacy: a classroom-organization conceptualization. Teaching and Teacher Education, 18(6), 675–686. https://doi.org/10.1016/S0742-051X(02)00027-6
20. Gooran, M., Soleimani, H., Alavi, M., & Jafarigohar, M. (2022). EFL teachers’ immunity: a case of online language teaching. Journal of Multilingual and Multicultural Development. https://doi.org/10.1080/01434632.2022.2044341
21. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis. Pearson University Press
22. Hambleton, R. K., & Kanjee, A. (1995). Increasing the validity of cross-cultural assessments: Use of improved methods for test adaptations. European Journal of Psychological Assessment, 11, 147-157. http://dx.doi.org/10.1027/1015-5759.11.3.147
23. Hamman, D., Wang, E., & Burley, H. (2013). What I expect and fear next year: measuring new teachers’ possible selves. Journal of Education for Teaching, 39(2), 222–234.
24. Harris, D. N., & Sass, T. R. (2011). Teacher training, teacher quality and student achievement. Journal of Public Economics, 95(7–8), 798–812. https://doi.org/10.1016/J.JPUBECO.2010.11.009
25. Hiver, P. (2017). Tracing the Signature Dynamics of Language Teacher Immunity: A Retrodictive Qualitative Modeling Study. The Modern Language Journal, 101(4), 669–690. https://doi.org/10.1111/modl.12433
26. Hiver, P., & Dörnyei, Z. (2017). Language teacher immunity: A double-edged sword. Applied Linguistics, 38, 405–423.
27. Hoe, S. L. (2008). Issues and procedures in adopting structural equation modeling technique. Journal of Applied Quantitative Methods, 3, 76-83.
28. Howard, S., & Johnson, B. (2000). What makes the difference? Children and teachers talk about resilient outcomes for children ‘at risk.’ Educational Studies, 26(3), 321–337.
29. Hubley A.M. (2014) Discriminant validity. In Michalos A.C. (eds) Encyclopedia of quality of life and well-being research. Springer, https://doi.org/10.1007/978-94-007-0753-5_751
30. Jafari, F. M., & Ameri, A. (2020). Teacher immunity in professional identity: Refelction on male IELTS teachers' homosocial fabrics in 2 Iranian ethnographic institutions. Rev. Tempos Espaços Educ, 13(32), 1–15. https://doi.org/10.20952/revtee.v13i32.14857
31. Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika,39(1), 31-36. https://doi.org/10.1007/BF02291575
32. Kirk, R. E. (2008). Statistics an introduction (5th Edition). Thomson Higher Education
33. Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford.
34. Krzanowski, W. J. (2007). Statistical principles and techniques in scientific and social investigations. Oxford University Press.
35. Li, S. (2021). Psychological Well-being, Mindfulness, and Immunity of Teachers in Second or Foreign Language Education: A Theoretical Review. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.720340
36. Maghsoudi, M. (2021). Productive or Maladaptive Immunity? Which one is more Dominant among Iranian EFL Prospective Teachers? Applied Research on English Language, 10(1), 51–80.
37. Morris, D. B., Usher, E. L., & Chen, J. A. (2017). Reconceptualizing the Sources of Teaching Self-Efficacy: A Critical Review of Emerging Literature. Educational Psych, 29, 795–833. https://doi.org/10.1007/s10648-016-9378-y
38. Noughabi, M. A., Amirian, S. M. R., Adel, S. M. R., & Zareian, G. (2020). The Association of Experienced in-service EFL teachers’ immunity with engagement, emotions, and autonomy. Current Psychology. https://doi.org/10.1007/s12144-020-01066-8
39. Ordem, E. (2017). A Language Teacher’s Reflection on Maladaptive Immunity, Possible Selves and Motivation. International Education Studies, 10(9), 1–8.
40. Oswald, M., Johnson, B., & Howard, S. (2003). Quantifying and evaluating resilience-promoting factors: Teachers’ beliefs and perceived roles. Research in Education, 70, 50–64.
41. Pallant, J. (2016). SPSS survival manual: A step by step guide to data analysis using spss program (6th ed.). McGraw-Hill Education.
42. Parsons, S. A., Vaughn, M., Malloy, J. A., & Pierczynski, M. (2017). The development of teachers’ visions from preservice into their first years teaching: A longitudinal study. Teaching and Teacher Education, 64, 12–25.
43. Priestley, M., Biesta, G. J. J., & Robinson, S. (2015). Teacher agency: An ecological approach. Bloomsbury.
44. Rahimpour, H., Amirian, S. M. R., Adel, S. M. R., & Zareian, G. R. (2020). A model of the factors predicting English language teacher immunity: A path analysis. Indonesian Journal of Applied Linguistics, 10(1), 73–83.
45. Sampson, R. J. (2022). From darkness to light: Teacher immunity and the emergence of relatedness with students. In Y. Kimura (Ed.), Language teacher motivation, autonomy and development in East Asia. Springer.
46. Sarıçoban, A., & Kırmızı, O. (2021). Language teacher immunity: insights from Turkey. International Online Journal of Education and Teaching, 8(2), 1172–1189.
47. Saydam, D. (2019). English language teacher immunity: The METU case. Middle East Technical University.
48. Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of Educational Research, 99(6), 323-338.
49. Shen, B., Mccaughtry, N., Martin, J., Garn, A., Kulik, N., & Fahlman, M. (2015). The relationship between teacher burnout and student motivation. British Journal of Educational Psychology, 85, 519–532. https://doi.org/10.1111/bjep.12089 Tabachnick, B., & Fidell, L. (2013). Using multivariate statistics. Pearson.
50. Taber, K.S. The use of cronbach's alpha when developing and reporting research instruments in science education. Res Sci Educ 48, 1273–1296 (2018). https://doi.org/10.1007/s11165-016-9602-2
51. Tal, C., & Yinon, Y. (2002). Teachers’ conservatism, openness to change, transcendence and self-enhancement in daily life and in school situations. Social Psychology of Education, 5, 271–293.
52. Tatlı Dalioğlu, S., & Adıgüzel, O. C. (2017). The relationship between teacher candidates’ possible selves, self-efficacy beliefs and attitudes towards teaching. Mersin University Journal of the Faculty of Education, 13(2), 487–496.
53. Tinsley, H. E., & Tinsley, D. J. (1987). Uses of factor analysis in counseling psychology research. Journal of Counseling Psychology, 34, 414-424. https://doi.org/10.1037/0022-0167.34.4.414
54. Zijlmans, E.A.O., Tijmstra, J., van der Ark, L.A., & Sijtsma, K. (2019). Item-Score reliability as a selection tool in test construction. Front. Psychol. 9, 2298. https://10.3389/fpsyg.2018.02298
55. Hebebci, M. T., & Shelley, M. (2018). Analysis of the relationship between university students’ problematic internet use and loneliness. International Journal of Assessment Tools in Education, 5(2), 223-234. https://doi.org/10.21449/ijate.402690
56. Ömür, S., & Erkuş, A. (2013). Dereceli puanlama anahtarıyla, genel izlenimle ve ikili karşılaştırmalar yöntemiyle yapılan değerlendirmelerin karşılaştırılması [Comparison of the evaluations which were done with rubric, overall impression and paired comparisons]. Hacettepe University Journal of Education, 28(2), 308 320. https://dergipark.org.tr/tr/pub/hunefd/issue/7790/101884
57. R Core Team. (2014). R: A language and environment for statistical computing [Computer software manual]. http://www.R-project.org/
58. Tatsuoka, K. K. (1984). Analysis of errors in fraction addition and subtraction problems (Report No. NIE-G-81-0002). Computer-based Education Research Laboratory, University of Illinois.
59. Terzi, R. (2017). New Q-matrix validation procedures [Doctoral dissertation, Rutgers University]. Rutgers University Libraries. https://doi.org/10.7282/T3571G5G