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Latent profile analysis of students’ perception of German classroom climate: outcomes and covariates

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Abstract

Classroom climate has been considered as an important factor influencing students’ learning motivation, achievement and psychological and behavioural health in schools. With the data from German National Educational Panel Study and the latent profile approach, we explored students’ perception of German classroom climate including learning and social environment (N = 4643). We also explored the outcome differences among these profiles and possible covariates related to them. The four following latent profiles differing in perceptions of German classroom climate were identified: negative, moderately negative, moderately positive and positive profiles; migration background predicted the probability of belonging to a specific profile; generally, students with a more positive perception had also higher interest, performance motivation, and achievement in reading as well as satisfaction with school life; the profiles of students in academic and vocational tracks were quite similar, but gender did not predict the profile membership probability for students in the vocational track and there was no self-concept disparity among profiles for them. These results supported individual differences in classroom perception as well as the associations of the perceptions with different outcome and background variables, which have implications for understanding students’ subjective perceptions of classroom climate and early detection of, or intervention for, the groups at risk.

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Data availability

This paper uses data from the National Educational Panel Study (NEPS): Starting Cohort Grade 5, http://dx.doi.org/10.5157/NEPS:SC3:10.0.0. The data that supports the findings of this study is available from the Leibniz Institute for Educational Trajectories (https://www.neps-data.de/Data-Center/Data-Access). Restrictions apply to the availability of this data, which is the reason why it cannot be provided by the authors of the study. Survey questionnaires are available on the NEPS study website (https://www.neps-data.de/Data-Center/Data-and-Documentation).

References

  • Aditomo, A., & Köhler, C. (2020). Do student ratings provide reliable and valid information about teaching quality at the school level? Evaluating measures of science teaching in PISA 2015. Educational Assessment, Evaluation and Accountability, 32(3), 275–310.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Asparouhov, T., & Muthén, B. O. (2010). Resampling methods in Mplus for complex survey data. Muthén & Muthén.

    Google Scholar 

  • Baumert, J., Kunter, M., Blum, W., Brunner, M., Voss, T., Jordan, A., & Tsai, Y. M. (2010). Teachers’ mathematical knowledge, cognitive activation in the classroom, and student progress. American Educational Research Journal, 47(1), 133–180.

    Article  Google Scholar 

  • Benita, M., Roth, G., & Deci, E. L. (2014). When are mastery goals more adaptive? It depends on experiences of autonomy support and autonomy. Journal of Educational Psychology, 106(1), 258.

    Article  Google Scholar 

  • Blossfeld, H.-P., Roßbach, H.-G., & von Maurice, J. (2011). Education as a lifelong process: The German National Educational Panel Study (NEPS). Zeitschrift für Erziehungswissenschaft, Special Issue 14. Wiesbaden, Germany: VS Verlag für Sozialwissenschaften.

  • Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modelling., 9, 233–255.

    Article  Google Scholar 

  • Ciani, K. D., Middleton, M. J., Summers, J. J., & Sheldon, K. M. (2010). Buffering against performance classroom goal structures: The importance of autonomy support and classroom community. Contemporary Educational Psychology, 35(1), 88–99.

    Article  Google Scholar 

  • Deci, E. L., & Ryan, R. M. (1985). The general causality orientations scale: Self-determination in personality. Journal of Research in Personality, 19(2), 109–134.

    Article  Google Scholar 

  • Diener, E. (2009). Subjective well-being. In E. Diener (Ed.), The science of well-being: The collected works of Ed Diener (pp. 11–58).

  • Ditton, H. (2000). Qualitätskontrolle und Qualitätssicherung in Schule und Unterricht. Ein Überblick zum Stand der empirischen Forschung. [Quality control in schools and teaching: A summary of empirical studies.] In Qualität und Qualitätssicherung im Bildungsbereich; Schule, Sozialpädagogik, Hochschule. (pp. 73–92).

  • Dorman, J. P. (2001). Associations between classroom environment and academic efficacy. Learning Environments Research, 4(3), 243–257.

    Article  Google Scholar 

  • Eccles, J. S., & Blumenfeld, P. (1985). Classroom experiences and student gender: Are there differences and do they matter? In L. C. Wilkinson, & C. B. Marrett (Eds.), Gender influences in classroom interaction (pp. 79–114). Orlando, FL: Academic Press. https://doi.org/10.1016/B978-0-12-752075-9.50010-6

  • Fauth, B., Decristan, J., Rieser, S., Klieme, E., & Büttner, G. (2014). Student ratings of teaching quality in primary school: Dimensions and prediction of student outcomes. Learning and Instruction, 29, 1–9.

    Article  Google Scholar 

  • Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7(2), 117–140.

    Article  Google Scholar 

  • Ferguson, S. L., Moore, E. W. G., & Hull, D. M. (2020). Finding latent groups in observed data: A primer on latent profile analysis in Mplus for applied researchers. International Journal of Behavioral Development, 44(5), 458–468.

    Article  Google Scholar 

  • Fraser, B. J. (1994). Research on classroom and school climate. In D. Gabel (Ed.), Handbook of research on science teaching and learning (pp. 493–541). Macmillan.

    Google Scholar 

  • Fujita, F., & Diener, E. (1997). Social comparisons and subjective well-being. Health, coping and well-being: Perspectives from Social Comparison Theory, 329–357.

  • Goldstein, S. E., Boxer, P., & Rudolph, E. (2015). Middle school transition stress: Links with academic performance, motivation, and school experiences. Contemporary School Psychology, 19(1), 21–29.

    Article  Google Scholar 

  • Hajovsky, D. B., Mason, B. A., & McCune, L. A. (2017). Teacher-student relationship quality and academic achievement in elementary school: A longitudinal examination of gender differences. Journal of School Psychology, 63, 119–133.

    Article  Google Scholar 

  • Hamre, B. K., & Pianta, R. C. (2010). Classroom environments as developmental processes: Conceptualization and measurement. In J. L. Meece & J. S. Eccles (Eds.), Handbook of research on schools, schooling and human development (pp. 25–41). Routledge.

    Google Scholar 

  • Hardre, P. L., & Reeve, J. (2003). A motivational model of rural students’ intentions to persist in, versus drop out of, high school. Journal of Educational Psychology, 95(2), 347.

    Article  Google Scholar 

  • Helmke, A., & Weinert, F. E. (1997). Bedingungsfaktoren schulischer Leistungen. [Influencing factors on school performance.] In Weinert, F. E. (Ed.), Enzyklopädie der Psychologie. Bd.3. Psychologie des Unterrichts und der Schule (pp. 71e176). Göttingen: Hogrefe.

  • Hochweber, J., & Vieluf, S. (2018). Gender differences in reading achievement and enjoyment of reading: The role of perceived teaching quality. The Journal of Educational Research, 111(3), 268–283.

    Article  Google Scholar 

  • Joe, H. K., Hiver, P., & Al-Hoorie, A. H. (2017). Classroom social climate, self-determined motivation, willingness to communicate, and achievement: A study of structural relationships in instructed second language settings. Learning and Individual Differences, 53, 133–144.

    Article  Google Scholar 

  • Jung, T., & Wickrama, K. A. S. (2008). An introduction to latent class growth analysis and growth mixture modeling. Social and Personality Psychology Compass, 2(1), 302–317.

    Article  Google Scholar 

  • Kim, Y., Jeon, S., Chang, C., & Chung, H. (2022). glca: An R package for multiple-group latent class analysis. Applied Psychological Measurement, 46(5), 439–441. https://doi.org/10.1177/01466216221084197

    Article  Google Scholar 

  • Klein, K. J., Bliese, P. D., Kozlowski, S. W. J., Dansereau, F., Gavin, M. B., Griffin, M. A., & Bligh, M. C. (2000). Multilevel analytical techniques: Commonalities, differences, and continuing questions. In K. J. Klein & S. W. J. Kozlowski (Eds.), Multilevel theory, research, and methods in organizations, and methods in organizations: Foundations, extensions, and new directions (pp. 512–553). Jossey-Bass.

    Google Scholar 

  • Kunter, M., Baumert, J., & Köller, O. (2007). Effective classroom management and the development of subject-related interest. Learning and Instruction, 17(5), 494–509.

    Article  Google Scholar 

  • Kunter, M., Schümer, G., Artelt, C., Baumert, J., Klieme, E., Neubrand, M., Prenzel, M., Schiefele, U., Schneider, W., Stanat, P., Tillmann, K.-J., & Weiß, M. (2003). PISA 2000 - Dokumentation der Erhebungsinstrumente. MPI für Bildungsforschung.

    Google Scholar 

  • Kunter, M., & Voss, T. (2011). Das Modell der Unterrichtsqualität in COACTIV: Eine multikriteriale Analyse.[Teaching quality model in COACTIV: A multi-criteria analysis]. Professionelle Kompetenz von Lehrkräften. Ergebnisse des Forschungsprogramms COACTIV, 85–113.

  • LeClair, C., Doll, B., Osborn, A., & Jones, K. (2009). English language learners’ and non–English language learners’ perceptions of the classroom environment. Psychology in the Schools, 46(6), 568–577.

    Article  Google Scholar 

  • Logan, S., & Johnston, R. (2010). Investigating gender differences in reading. Educational Review, 62(2), 175–187.

    Article  Google Scholar 

  • Lubke, G. H., & Muthén, B. (2005). Investigating population heterogeneity with factor mixture models. Psychological Methods, 10(1), 21–39.

    Article  Google Scholar 

  • Maaz, K., Trautwein, U., Lüdtke, O., & Baumert, J. (2008). Educational transitions and differential learning environments: How explicit between-school tracking contributes to social inequality in educational outcomes. Child Development Perspectives, 2(2), 99–106.

    Article  Google Scholar 

  • Marsh, H. W., Lüdtke, O., Trautwein, U., & Morin, A. J. S. (2009). Classical latent profile analysis of academic self-concept dimensions: Synergy of person- and variable-centered approaches to theoretical models of self-concept. Structural Equation Modeling: A Multidisciplinary Journal, 16(2), 191–225.

    Article  Google Scholar 

  • Martin, A. J., & Dowson, M. (2009). Interpersonal relationships, motivation, engagement, and achievement: Yields for theory, current issues, and educational practice. Review of Educational Research, 79(1), 327–365.

    Article  Google Scholar 

  • Midgley, C., Anderman, E., & Hicks, L. (1995). Differences between elementary and middle school teachers and students: A goal theory approach. The Journal of Early Adolescence, 15(1), 90–113.

    Article  Google Scholar 

  • Miller, A. D., & Murdock, T. B. (2007). Modeling latent true scores to determine the utility of aggregate student perceptions as classroom indicators in HLM: The case of classroom goal structures. Contemporary Educational Psychology, 32, 83–104. https://doi.org/10.1016/j.cedpsych.2006.10.006

    Article  Google Scholar 

  • Morin, A. J. S., & Marsh, H. W. (2015). Disentangling shape from level effects in person-centered analyses: An illustration based on university teachers’ multidimensional profiles of effectiveness. Structural Equation Modeling: A Multidisciplinary Journal, 22(1), 39–59.

    Article  Google Scholar 

  • Murayama, K., & Elliot, A. J. (2009). The joint influence of personal achievement goals and classroom goal structures on achievement-relevant outcomes. Journal of Educational Psychology, 101(2), 432–447.

    Article  Google Scholar 

  • Möller, J., & Bonerad, E. M. (2007). Fragebogen zur habituellen Lesemotivation. [Questionnaire of habitual reading motivation]. Psychologie in Erziehung Und Unterricht, 54(1), 259–267.

    Google Scholar 

  • Nie, Y., & Lau, S. (2009). Complementary roles of care and behavioral control in classroom management: The self-determination theory perspective. Contemporary Educational Psychology, 34(3), 185–194.

    Article  Google Scholar 

  • Nylund-Gibson, K., & Choi, A. Y. (2018). Ten frequently asked questions about latent class analysis. Translational Issues in Psychological Science, 4(4), 440–461.

    Article  Google Scholar 

  • OECD. (2019). The road to integration: Education and migration, OECD reviews of migrant education. OECD Publishing. https://doi.org/10.1787/d8ceec5d-en

    Book  Google Scholar 

  • Reeve, J. (2009). Why teachers adopt a controlling motivating style toward students and how they can become more autonomy supportive. Educational Psychologist, 44(3), 159–175.

    Article  Google Scholar 

  • Reeve, J., & Jang, H. (2006). What teachers say and do to support students’ autonomy during a learning activity. Journal of Educational Psychology, 98(1), 209–218.

    Article  Google Scholar 

  • Rohatgi, A., & Scherer, R. (2020). Identifying profiles of students’ school climate perceptions using PISA 2015 data. Large-Scale Assessments in Education, 8(1), 1–25.

    Article  Google Scholar 

  • Roseth, C. J., Johnson, D. W., & Johnson, R. T. (2008). Promoting early adolescents’ achievement and peer relationships: The effects of cooperative, competitive, and individualistic goal structures. Psychological Bulletin, 134(2), 223.

    Article  Google Scholar 

  • Ryan, A. M., & Patrick, H. (2001). The classroom social environment and changes in adolescents’ motivation and engagement during middle school. American Educational Research Journal, 38(2), 437–460.

    Article  Google Scholar 

  • Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67.

    Article  Google Scholar 

  • Sandilos, L. E., Rimm-Kaufman, S. E., & Cohen, J. J. (2017). Warmth and demand: The relation between students’ perceptions of the classroom environment and achievement growth. Child Development, 88(4), 1321–1337.

    Article  Google Scholar 

  • Schenke, K., Ruzek, E., Lam, A. C., Karabenick, S. A., & Eccles, J. S. (2017). Heterogeneity of student perceptions of the classroom climate: A latent profile approach. Learning Environments Research, 20(3), 289–306.

    Article  Google Scholar 

  • Schiefele, U., Moschner, B., & Husstegge, R. (2002). Skalenhandbuch SMILE-Projekt. [Scale handbook of SMILE-Project].

  • Schiepe-Tiska, A. (2019). School tracks as differential learning environments moderate the relationship between teaching quality and multidimensional learning goals in mathematics. Frontiers in Education, 4(4). https://doi.org/10.3389/feduc.2019.00004

  • Schweig, J. (2014). Cross-level measurement invariance in school and classroom environment surveys: Implications for policy and practice. Educational Evaluation and Policy Analysis, 36(3), 259–280. https://doi.org/10.3102/0162373713509880

    Article  Google Scholar 

  • Seidel, T., Rimmele, R., & Prenzel, M. (2005). Clarity and coherence of lesson goals as a scaffold for student learning. Learning and Instruction, 15(6), 539–556.

    Article  Google Scholar 

  • Shrout, P. E., & Fleiss, J. L. (1979). Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin, 86(2), 420–3428.

    Article  Google Scholar 

  • Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel analysis: An introduction to basic and advanced multilevel modeling (2nd ed.). Sage.

    Google Scholar 

  • Spearman, J., & Watt, H. M. (2013). Perception shapes experience: The influence of actual and perceived classroom environment dimensions on girls’ motivations for science. Learning Environments Research, 16(2), 217–238.

    Article  Google Scholar 

  • Stapleton, L. M., Yang, J. S., & Hancock, G. R. (2016). Construct meaning in multilevel settings. Journal of Educational and Behavioral Statistics, 41(5), 481–520.

    Article  Google Scholar 

  • Tapola, A., & Niemivirta, M. (2008). The role of achievement goal orientations in students’ perceptions of and preferences for classroom environment. British Journal of Educational Psychology, 78(2), 291–312.

    Article  Google Scholar 

  • Thijs, J., Westhof, S., & Koomen, H. (2012). Ethnic incongruence and the student–teacher relationship: The perspective of ethnic majority teachers. Journal of School Psychology, 50(2), 257–273.

    Article  Google Scholar 

  • Urdan, T., & Schoenfelder, E. (2006). Classroom effects on student motivation: Goal structures, social relationships, and competence beliefs. Journal of School Psychology, 44(5), 331–349.

    Article  Google Scholar 

  • Van Eck, K., Johnson, S. R., Bettencourt, A., & Johnson, S. L. (2017). How school climate relates to chronic absence: A multi–level latent profile analysis. Journal of School Psychology, 61, 89–102.

    Article  Google Scholar 

  • Velayutham, S., & Aldridge, J. M. (2013). Influence of psychosocial classroom environment on students’ motivation and self-regulation in science learning: A structural equation modeling approach. Research in Science Education, 43(2), 507–527.

    Article  Google Scholar 

  • Wagner, W., Helmke, A., & Rösner, E. (2009). Deutsch Englisch Schülerleistungen International. Dokumentation der Erhebungsinstrumente für Schülerinnen und Schüler, Eltern und Lehrkräfte.[DESI documentation of instruments for students, parents and teachers.] Frankfurt, Main: GFPF; DIPF.

  • Wolters, C. A. (2004). Advancing achievement goal theory: Using goal structures and goal orientations to predict students’ motivation, cognition, and achievement. Journal of Educational Psychology, 96(2), 236.

    Article  Google Scholar 

  • Way, N., Reddy, R., & Rhodes, J. (2007). Students’ perceptions of school climate during the middle school years: Associations with trajectories of psychological and behavioral adjustment. American Journal of Community Psychology, 40(3), 194–213.

    Article  Google Scholar 

  • Webb, N. M., & Palincsar, A. S. (1996). Group processes in the classroom. Prentice Hall International.

    Google Scholar 

  • Wentzel, K. R. (1991). Relations between social competence and academic achievement in early adolescence. Child Development, 62(5), 1066–1078.

    Article  Google Scholar 

  • Williams, G. C., & Deci, E. L. (1996). Internalization of biopsychosocial values by medical students: A test of self-determination theory. Journal of Personality and Social Psychology, 70(4), 767.

    Article  Google Scholar 

  • Yi, H. S., & Lee, Y. (2017). A latent profile analysis and structural equation modeling of the instructional quality of mathematics classrooms based on the PISA 2012 results of Korea and Singapore. Asia Pacific Education Review, 18(1), 23–39.

    Article  Google Scholar 

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Acknowledgements

From 2008 to 2013 NEPS data was collected as part of the Framework Program for the Promotion of Empirical Education Research funded by the German Federal Ministry of Education and Research (BMBF). As of 2014, NEPS is carried out by the Leibniz Institute for Educational Trajectories (LIfBi) at the University of Bamberg in cooperation with a nationwide network.

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  1. Leibnitz Institute for Educational Trajectories, Wilhelmsplatz 3, 96047, Bamberg, Germany

    Ji Zhou & Anna Hawrot

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Appendix

Appendix

Tables 7, 8.

Table 7 Multi-group CFA results for the five dimensions of learning environment perception between two tracks
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Table 8 Correlations among five scales of perceived environment
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Zhou, J., Hawrot, A. Latent profile analysis of students’ perception of German classroom climate: outcomes and covariates. Learning Environ Res 27, 121–142 (2024). https://doi.org/10.1007/s10984-023-09471-z

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