Advertisement

Annals of Dyslexia

, Volume 69, Issue 1, pp 80–98 | Cite as

Discovering the impact of reading coursework and discipline-specific mentorship on first-year teachers’ self-efficacy: a latent class analysis

  • Luxi FengEmail author
  • Tracey S. Hodges
  • Hersh C. Waxman
  • R. Malatesha Joshi
Article

Abstract

Teacher self-efficacy is critical because it predicts teachers’ future behavior and impacts teacher turnover. Most teachers begin their career with moderate to high self-efficacy for teaching, but often experience a sharp decline during the first year of teaching. After the first year, their self-efficacy begins to increase but rarely rises to the level it was prior to beginning teaching. Therefore, examining first-year teachers’ self-efficacy is extremely important. Previous research generally depicts teachers as a homogeneous group, relying on variable-centered approaches and including self-efficacy as a scaling score, which may not be applicable at the individual level. Simply extending findings from the variable-centered analyses is insufficient. Therefore, the purpose of the present study is to examine the heterogeneous profiles of first-year teachers’ self-efficacy from the 2011–2012 Schools and Staffing Survey and to investigate how self-efficacy profiles are related to teacher training at the individual level. Using latent class analyses, we found three statistically distinctive classes within self-efficacy: high, moderate, and low. Regardless of teaching assignments, teachers who completed reading content courses during preparation programs and received discipline-specific mentoring during their first year dominated a higher level of self-efficacy. We conclude that these two factors are essential to preparing and retaining high-quality teachers.

Keywords

Content knowledge Latent class analysis Mentorship Teacher education Teacher self-efficacy 

Notes

References

  1. Akaike, H. (1987). Factor analysis and AIC. Psychometrika, 52, 317–332.  https://doi.org/10.1007/BF02294359.CrossRefGoogle Scholar
  2. Ashton, P. T., & Webb, R. B. (1986). Making a difference: Teachers’ sense of efficacy and student achievement. New York: Longman.Google Scholar
  3. Asparouhov, T., & Muthén, B. (2014). Auxiliary variables in mixture modeling: Three-step approaches using M plus. Structural Equation Modeling: A Multidisciplinary Journal, 21, 329–341.  https://doi.org/10.1080/10705511.2014.915181.CrossRefGoogle Scholar
  4. Asparouhov, T., & Muthén, B. (2015). Auxiliary variables in mixture modeling: Using the BCH method in Mplus to estimate a distal outcome model and an arbitrary secondary model. Mplus Web Notes. Retrieved from https://www.statmodel.com/examples/webnotes/webnote21.pdf
  5. Bandura, A. (1977). Social learning theory. Englewood Cliffs: Prentice Hall.Google Scholar
  6. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs: Prentice-Hall.Google Scholar
  7. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.Google Scholar
  8. Bangert-Drowns, R. L., Hurley, M. M., & Wilkinson, B. (2004). The effects of school-based writing-to-learn interventions on academic achievement: A meta-analysis. Review of Educational Research, 74(1), 29–58.CrossRefGoogle Scholar
  9. Banilower, E., Cohen, K., Pasley, J., & Weiss, I. (2008). Effective science instruction: What does research tell us? Portsmouth: RMC Corporation, Center on Instruction.Google Scholar
  10. Bauml, M. (2014). Collaborative lesson planning as professional development for beginning primary teachers. The New Educator, 10, 182–200.  https://doi.org/10.1080/1547688X.2014.925741.CrossRefGoogle Scholar
  11. Berlin, K. S., Williams, N. A., & Parra, G. R. (2014). An introduction to latent variable mixture modeling (part 1): Overview and cross-sectional latent class and latent profile analyses. Journal of Pediatric Psychology, 39, 174–187.  https://doi.org/10.1093/jpepsy/jst084.CrossRefGoogle Scholar
  12. Bolck, A., Croon, M., & Hagenaars, J. (2004). Estimating latent structure models with categorical variables: One-step versus three-step estimators. Political Analysis, 12, 3–27.  https://doi.org/10.1093/pan/mph001.CrossRefGoogle Scholar
  13. Caprara, G. V., Barbaranelli, C., Steca, P., & Malone, P. S. (2006). Teachers’ self-efficacy beliefs as determinants of job satisfaction and students’ academic achievement: A study at the school level. Journal of School Psychology, 44, 473–490.  https://doi.org/10.1016/j.jsp.2006.09.001.CrossRefGoogle Scholar
  14. Castro, A. J., Kelly, J., & Shih, M. (2010). Resilience strategies for new teachers in high-needs areas. Teaching and Teacher Education, 26, 622–629.  https://doi.org/10.1016/j.tate.2009.09.010.CrossRefGoogle Scholar
  15. Celeux, G., & Soromenho, G. (1996). An entropy criterion for assessing the number of clusters in a mixture model. Journal of Classification, 13, 195–212.CrossRefGoogle Scholar
  16. Chacon, C. T. (2005). Teachers’ perceived efficacy among English as a foreign language teachers in middle schools in Venezuela. Teaching and Teacher Education, 21, 257–272.  https://doi.org/10.1016/j.tate.2005.01.001.CrossRefGoogle Scholar
  17. Ciampa, K., & Gallagher, T. L. (2018). A comparative examination of Canadian and American pre-service teachers’ self-efficacy beliefs for literacy instruction. Reading and Writing: An Interdisciplinary Journal, 31(2), 457–481.CrossRefGoogle Scholar
  18. Collins, L. M., Fidler, P. L., Wugalter, S. E., & Long, J. D. (1993). Goodness-of-fit testing for latent class models. Multivariate Behavioral Research, 28, 375–389.  https://doi.org/10.1207/s15327906mbr2803_4.CrossRefGoogle Scholar
  19. Darling-Hammond, L., & Youngs, P. (2002). Defining “highly qualified teachers”. What does “scientifically-based research” actually tell us? Educational Researcher, 37(1), 13–25.CrossRefGoogle Scholar
  20. de la Torre Cruz, M. J., & Casanova Arias, P. F. (2007). Comparative analysis of expectancies of efficacy in in-service and prospective teachers. Teaching and Teacher Education, 23, 641–652.  https://doi.org/10.1016/j.tate.2007.02.005.CrossRefGoogle Scholar
  21. Dellinger, A. B., Bobbett, J. J., Olivier, D. F., & Ellett, C. D. (2008). Measuring teachers’ self-efficacy beliefs: Development and use of TEBS-self. Teaching and Teacher Education, 24, 751–766.  https://doi.org/10.1016/j.tate.2007.02.010.CrossRefGoogle Scholar
  22. Driscoll, K. C., & Pianta, R. C. (2010). Banking time in head start: Early efficacy of an intervention designed to promote supportive teacher–child relationships. Early Education and Development, 2(1), 38–64.  https://doi.org/10.1080/10409280802657449.CrossRefGoogle Scholar
  23. Duffin, L. C., French, B. F., & Patrick, H. (2012). The teachers’ sense of efficacy scale: Confirming the factor structure with beginning pre-service teachers. Teaching and Teacher Education, 28, 827–834.  https://doi.org/10.1016/j.tate.2012.03.004.CrossRefGoogle Scholar
  24. Elliott, E. M., Isaacs, M. L., & Chugani, C. D. (2010). Promoting self-efficacy in early career teachers: A principal’s guide for differentiated mentoring and supervision. Florida Journal of Educational Administration & Policy, 4, 131–146.Google Scholar
  25. Ernest, J. M., Heckaman, K. A., Thompson, S. E., Hull, K. M., & Carter, S. W. (2011). Increasing the teaching efficacy of a beginning special education teacher using differentiated instruction: A case study. International Journal of Special Education, 26, 191–201.Google Scholar
  26. Fenty, N. S., & Brydon, M. (2017). Integrating literacy and the content curriculum to support diverse learners. Learning Disabilities: A Contemporary Journal, 15(2), 225–328.Google Scholar
  27. Flores, M. A. (2006). Being a novice teacher in two different settings: Struggles, continuities, and discontinuities. Teachers College Record, 108, 2021–2052.Google Scholar
  28. Fox, A. G., & Peters, M. L. (2013). First year teachers: Certification program and assigned subject on their self-efficacy. Current Issues in Education, 16, 1–15.Google Scholar
  29. Gaston, A., Martinez, J., & Martin, E. P. (2016). Embedding literacy strategies in social studies for eighth-grade students. Journal of Social Studies Education Research, 7(1), 73–95.CrossRefGoogle Scholar
  30. Gavish, B., & Friedman, I. A. (2010). Novice teachers’ experience of teaching: A dynamic aspect of burnout. Social Psychology of Education, 13, 141–167.  https://doi.org/10.1007/s11218-009-9108-0.CrossRefGoogle Scholar
  31. Ghaith, G., & Yaghi, H. (1997). Relationships among experience, teacher efficacy, and attitudes toward the implementation of instructional innovation. Teaching and Teacher Education, 13, 451–458.  https://doi.org/10.1016/S0742-051X(96)00045-5.CrossRefGoogle Scholar
  32. Gibson, S., & Dembo, M. (1984). Teacher efficacy: A construct validation. Journal of Educational Psychology, 76, 569–582.CrossRefGoogle Scholar
  33. Graham, S., Bruch, J., Fitzgerald, J., Friedrich, L., Furgeson, J., Greene, K., et al. (2016). Teaching secondary students to write effectively (NCEE 2017-4002). Washington, DC: National Center for Education Evaluation and Regional Assistance (NCEE), Institute of Education Sciences, U.S. Department of Education.Google Scholar
  34. Graham, S., Harris, K. R., & Chambers, A. B. (2017). Evidence-based practice and writing instruction: A review of reviews. In C. A. MacArthur, S. Graham, & J. Fitzgerald (Eds.), The handbook of writing research (2nd ed., pp. 211–226). New York: Guilford Press.Google Scholar
  35. Graham, S., & Perin, D. (2007). What we know, what we still need to know: Teaching adolescents to write. Scientific Studies of Reading, 11, 313–335.  https://doi.org/10.1080/10888430701530664.CrossRefGoogle Scholar
  36. Gray, L., & Taie, S. (2015). Public school teacher attrition and mobility in the first five years: Results from the first through fifth waves of the 2007–08 beginning teacher longitudinal study. First look. Washington, DC: National Center for Education Statistics Retrieved from https://files.eric.ed.gov/fulltext/ED556348.pdf.Google Scholar
  37. Hagenaars, J. A., & McCutcheon, A. L. (Eds.). (2002). Applied latent class analysis. New York, NY: Cambridge University Press.Google Scholar
  38. Hall, D. M., Hughes, M. A., & Thelk, A. D. (2017). Developing mentorship skills in clinical faculty: A best practices approach to supporting beginning teachers. Teacher Educators’ Journal, 1077–1098.Google Scholar
  39. Hargreaves, A., & Fullan, M. (2012). Professional capital: Transforming teaching in every school. New York: Teachers College Press.Google Scholar
  40. Helms-Lorenz, M., Slof, B., Vermue, C. E., & Canrinus, E. T. (2011). Beginning teachers’ self-efficacy and stress and the supposed effects of induction arrangements. Educational Studies, 38, 189–207.  https://doi.org/10.1080/03055698.2011.598679.CrossRefGoogle Scholar
  41. Hill, H. C., Rowan, B., & Ball, D. L. (2005). Effects of teachers’ mathematical knowledge for teaching on student achievement. American Educational Research Journal, 42, 371–406.  https://doi.org/10.3102/00028312042002371.CrossRefGoogle Scholar
  42. Jamil, F. M., Downer, J. T., & Pianta, R. C. (2012). Association of pre-service teachers’ performance, personality, and beliefs with teacher self-efficacy at program completion. Teacher Education Quarterly, 39, 119–138.Google Scholar
  43. Kim, H., & Cho, Y. (2014). Pre-service teachers’ motivation, sense of teaching efficacy, and expectation of reality shock. Asia-Pacific Journal of Teacher Education, 42, 67–81.  https://doi.org/10.1080/1359866X.2013.85999.CrossRefGoogle Scholar
  44. Kirby, S. N., & Grissmer, D. W. (1993). Teacher attrition: Theory, evidence, and suggested policy options. Santa Monica: Rand Corporation.Google Scholar
  45. Lo, Y., Mendell, N., & Rubin, D. (2001). Testing the number of components in a normal mixture. Biometrika, 88, 767–778.  https://doi.org/10.1093/biomet/88.3.767.CrossRefGoogle Scholar
  46. Loeb, S., Darling-Hammond, L., & Luczak, J. (2005). How teaching conditions predict teacher turnover in California schools. Peabody Journal of Education, 80(3), 44–70.  https://doi.org/10.1207/s15327930pje8003_4.CrossRefGoogle Scholar
  47. McLachlan, G., & Peel, D. (2000). Finite mixture models. New York: Wiley.CrossRefGoogle Scholar
  48. Miller, D. M., Scott, C. E., & McTigue, E. M. (2016). Writing in the secondary-level disciplines: A systematic review of context, cognition, and content. Educational Psychology Review, 28, 1–38.  https://doi.org/10.1007/s10648-016-9393-z.CrossRefGoogle Scholar
  49. Moseley, C., Wandless, K., Bilica, A., & Gdovin, R. (2014). Exploring the relationship between teaching efficacy and cultural efficacy of novice science teachers in high-needs schools. School Science and Mathematics, 114, 315–325.  https://doi.org/10.1111/ssm.12087.
  50. Myers, J., Scales, R. Q., Grisham, D. L., Wolsey, T. D., Dismuke, S., Smetana, L., Yoder, K. K., Ikpeze, C., Ganske, K., & Martin, S. (2016). What about writing? A national exploratory study of writing instruction in teacher preparation programs. Literacy Research and Instruction, 55, 309–330.  https://doi.org/10.1080/19388071.2016.1198442.CrossRefGoogle Scholar
  51. National Assessment of Educational Progress. (2017). 2017 reading Grades 4 and 8 assessment report cards: Summary data tables for national and state average scores and achievement level results. Retrieved from https://www.nationsreportcard.gov/reading_2017/files/2017_Results_Appendix_Reading_State.pdf
  52. National Commission on Teaching and America’s Future. (2007). The cost of teacher turnover in five school districts: A pilot study. Washington, DC: Jamil.Google Scholar
  53. Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal, 14, 535–569.  https://doi.org/10.1080/10705510701575396.CrossRefGoogle Scholar
  54. Nylund-Gibson, K., & Masyn, K. E. (2016). Covariates and mixture modeling: Results of a simulation study exploring the impact of misspecified effects on class enumeration. Structural Equation Modeling: A Multidisciplinary Journal, 23, 782–797.  https://doi.org/10.1080/10705511.2016.1221313.CrossRefGoogle Scholar
  55. Ozder, H. (2011). Self-efficacy beliefs of novice teachers and their performance in the classroom. Australian Journal of Teacher Education, 36(5), 1–16.CrossRefGoogle Scholar
  56. Rosenman, R., Tennekoon, V., & Hill, L. G. (2011). Measuring bias in self-reported data. International Journal of Behavioural and Healthcare Research, 2, 320–332.  https://doi.org/10.1504/IJBHR.2011.043414.CrossRefGoogle Scholar
  57. Schlechty, P. C., & Vance, V. S. (1981). Do academically able teachers leave education? The North Carolina case. The Phi Delta Kappan, 63(2), 106–112.Google Scholar
  58. Schwartz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6, 461–464.CrossRefGoogle Scholar
  59. Sclove, L. (1987). Application of model-selection criteria to some problems in multivariate analysis. Psychometrika, 52, 333–343.  https://doi.org/10.1007/BF02294360.CrossRefGoogle Scholar
  60. Shanahan, T. (2017). Relationships between reading and writing development. In C. A. MacArthur, S. Graham, & J. Fitzgerald (Eds.), The handbook of writing research (2nd ed., pp. 194–207). New York: Guilford Press.Google Scholar
  61. Siwatu, K. O. (2011). Preservice teachers’ sense of preparedness and self-efficacy to teach in America’s urban and suburban schools: Does context matter? Teaching and Teacher Education, 27, 357–365.  https://doi.org/10.1016/j.tate.2010.09.004.CrossRefGoogle Scholar
  62. Skaalvik, E. M., & Skaalvik, S. (2007). Dimensions of teacher self-efficacy and relations with strain factors, perceived collective teacher efficacy, and teacher burnout. Journal of Educational Psychology, 99, 611–625.  https://doi.org/10.1037/0022-0663.99.3.611.CrossRefGoogle Scholar
  63. Spitler, E. (2011). From resistance to advocacy for math literacy: One teacher's literacy identity transformation. Journal of Adolescent & Adult Literacy, 55, 306–315.  https://doi.org/10.1002/JAAL.00037.CrossRefGoogle Scholar
  64. Swan, B. G., Wolf, K. J., & Cano, J. (2011). Changes in teacher self-efficacy from the student teaching experience through the third year of teaching. Journal of Agricultural Education, 52, 128–139.  https://doi.org/10.5032/jae.2011.02128.CrossRefGoogle Scholar
  65. Tschannen-Moran, M., & Johnson, D. (2011). Exploring literacy teachers’ self-efficacy beliefs: Potential sources at play. Teaching and Teacher Education, 27, 751–761.  https://doi.org/10.1016/j.tate.2010.12.005.CrossRefGoogle Scholar
  66. Tschannen-Moran, M., & Tschannen-Moran, B. (2011). Taking a strengths-based focus improves school climate. Journal of School Leadership, 21, 422–448.CrossRefGoogle Scholar
  67. Tschannen-Moran, M., & Woolfolk Hoy, A. W. (2001). Teacher efficacy: Capturing an elusive construct. Teaching and Teacher Education, 17, 783–805.  https://doi.org/10.1016/S0742-051X(01)00036-1.CrossRefGoogle Scholar
  68. Tschannen-Moran, M., & Woolfolk Hoy, A. W. (2006). The differential antecedents of self-efficacy beliefs of novice and experienced teachers. Teaching and Teacher Education, 23, 944–945.  https://doi.org/10.1016/j.tate.2006.05.003.CrossRefGoogle Scholar
  69. Vermunt, J. K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18, 450–469.  https://doi.org/10.2307/25792024.CrossRefGoogle Scholar
  70. Vieluf, S., Kunter, M., & van de Vijver, F. J. R. (2013). Teacher self-efficacy in cross-national perspective. Teaching and Teacher Education, 35, 92–103.  https://doi.org/10.1016/j.tate.2013.05.006.CrossRefGoogle Scholar
  71. von Eye, A., & Wiedermann, W. (2015). Person-centered analysis. In R. A. Scott & S. M. Kosslyn (Eds.), Emerging trends in the social and behavioral sciences: An interdisciplinary, searchable, and linkable resource (pp. 1–18). Hoboken: Wiley.Google Scholar
  72. Vygotsky, L. (1978). Interaction between learning and development. Readings on the Development of Children, 23(3), 34–41.Google Scholar
  73. Walls, T. A., & Schafer, J. L. (2006). Models for intensive longitudinal data. Oxford: Oxford University Press.CrossRefGoogle Scholar
  74. Wang, H., Hall, N. C., & Rahimi, S. (2015). Self-efficacy and causal attributions in teachers: Effects on burnout, job satisfaction, illness, and quitting intentions. Teaching and Teacher Education, 47, 120–130.  https://doi.org/10.1016/j.tate.2014.12.005.CrossRefGoogle Scholar
  75. Watson, J. M. (2018). Job embeddedness may hold the key to retention of novice talent in schools. Educational Leadership and Administration: Teaching and Program Development, 29(1), 26–43.Google Scholar
  76. Weber, B. J., & Omotani, L. M. (1994). The power of believing. The Executive Educator, 16, 35–38.Google Scholar
  77. Weber, N. D., Hodges, T. S., & Waxman, H. C. (2013). The development of an instrument to measure factors that impact preservice teachers’ perceived field commitment in teacher preparation programs. The Texas Forum of Teacher Education, 3, 87–101.Google Scholar
  78. Woolfolk Hoy, A., & Spero, R. B. (2005). Changes in teacher efficacy during the early years of teaching: A comparison of four measures. Teaching and Teacher Education, 21, 343–356.  https://doi.org/10.1016/j.tate.2005.01.007.CrossRefGoogle Scholar
  79. Yang, C. (2006). Evaluating latent class analyses in qualitative phenotype identification. Computational Statistics & Data Analysis, 50, 1090–1104.  https://doi.org/10.1016/j.csda.2004.11.004.CrossRefGoogle Scholar
  80. Zakeri, A., Rahmany, R., & Labone, E. (2016). Teachers’ self- and collective efficacy: The case of novice English language teachers. Journal of Language Teaching and Research, 7(1), 158–167.  https://doi.org/10.17507/jltr.0701.18.CrossRefGoogle Scholar
  81. Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25, 82–91.  https://doi.org/10.1006/ceps.1999.1016.CrossRefGoogle Scholar

Copyright information

© The International Dyslexia Association 2019

Authors and Affiliations

  • Luxi Feng
    • 1
    Email author
  • Tracey S. Hodges
    • 2
  • Hersh C. Waxman
    • 3
  • R. Malatesha Joshi
    • 3
  1. 1.Department of Psychological SciencesUniversity of ConnecticutStorrsUSA
  2. 2.Department of Curriculum and InstructionUniversity of AlabamaTuscaloosaUSA
  3. 3.Department of Teaching, Learning, and CultureTexas A&M UniversityCollege StationUSA

Personalised recommendations