Turkish Adaptation of Mathematics Achievement Emotions Questionnaire (AEQ-M): Reliability and Validity Study

Year 2019, Volume: 9 Issue: 53, 523 - 545, 25.06.2019

Başak Çalık Yeşim Çapa Aydın

Abstract

This study aimed to adapt Mathematics Achievement Emotions Questionnaire (AEQ-M) to Turkish language and provide evidence for the psychometric characteristics of the instrument. The scale was first translated to the Turkish and back translated to the English. Before finalizing the instrument, cognitive interviews were done with three middle school students and expert opinions were obtained from two experts in the field. Participants were sixth, seventh, and eighth grade middle school students in Ankara, Turkey. The scale was administered first to 746 and then to 2250 students, in Study 1 and 2 respectively. Confirmatory factor analysis suggested the seven-factor emotion model consistent with the original model. Besides, the relationships between each emotion and test anxiety were examined in Study 1 as further validity evidence. Positive and significant relationship appeared with negative emotions (i.e., anxiety, anger, shame, hopelessness, and boredom) of the AEQ-M. Cronbach alpha coefficients were high and ranged from .82 to .93. Overall, the Turkish adaptation of AEQ-M yielded valid and reliable scores to assess different mathematics achievement emotions of middle school students.

Keywords

Achievement emotions, control-value theory, mathematics education, middle school, validity, reliability, confirmatory factor analysis

References

• Arbuckle, J. L. (2011). Amos 20 [Computer software]. Chicago: SPSS.
• Baloğlu, M. & Koçak, R. (2006). A multivariate investigation of the differences in mathematics anxiety. Personality and Individual Differences, 40, 1325-1335.
• Bandalos, D. L. (2002). The effects of item parceling on goodness-of-fit and parameter estimate bias in structural equation modeling. Structural Equation Modeling, 9, 78–102.
• Bandalos, D. L., & Finney, S. J. (2001). Item parceling issues in structural equation modeling. In G. A. Marcoulides & R. E. Schumacker (Eds.), New developments and techniques in structural equation modeling (pp. 269–296). Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
• Birgin, O. , Baloğlu, M. , Çatlıoğlu, H. & Gürbüz, H. (2010). An investigation of mathematics anxiety among sixth through eighth grade students in Turkey. Learning and Individual Differences, 20, 654-658.
• Boekaerts, M. (2007). Understanding students’ affective processes in the classroom.In P.A. Schutz & R. Pekrun (Eds.), Emotions in education (pp. 37–56). San Diego:Academic Press.
• Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.
• Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136-162). Thousand Oaks, CA: Sage.
• Chiang, W. & Liu, C. (2014). Scale of academic emotion in science education: Development and validation. International Journal of Science Education, 36 (6), 908-928.
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd eds). Lawrence Erlbaum Associates, Publishers.
• Dede, Y. & Dursun, Ş. (2008). İlköğretim II. kademe öğrencilerinin matematik kaygı düzeylerinin incelenmesi [The investigation of math anxiety levels of middle school students]. Journal of Uludag University Faculty of Education, 21(2), 295-312.
• Frenzel, A. C., Goetz, T. , Lüdtke, O. , Pekrun, R. & Sutton, R. E. (2009). Emotional transmission in the classroom: Exploring the relationship between teacher and student enjoyment. Journal of Educational Psychology, 101(3), 705-716.
• Frenzel, A. C., Thrash, T. M., Pekrun, R., & Goetz, T. (2007a). Achievement emotions in Germany and China: A cross-cultural validation of the Academic Emotions Questionnaire-Mathematics (AEQ-M). Journal of Cross-Cultural Psychology, 38, 302– 309.
• Frenzel, A. C., Pekrun, R., & Goetz, T. (2007b). Girls and mathematics – a “hopeless” issue? A control- value approach to gender differences in emotions towards mathematics. European Journal of Psychology of Education, 22, 497–514.
• Frenzel, A. C., Pekrun, R., & Goetz, T. (2007c). Perceived learning environment and students’ emotional experiences: A multilevel analysis of math classrooms. Learning and Instruction, 27(5), 472-493.
• Goetz, T., Bieg, M., Lüdtke, O., Pekrun, R., & Hall, N. (2013). Do girls really experience more anxiety in mathematics? Psychological Science, 20, 1-9.
• Goetz, T. Cronjaeger, H. , Frenzel, A. C., Lüdtke, O. & Hall, N. C. (2010). Academic self concept and emotion relations: Domain specificity and age effects. Contemporary Educational Psychology, 35, 44-58.
• Goetz, T. ,Frenzel, A. C. , Hall, N. & Pekrun, N. (2008). Antecedents of academic emotions: Testing the internal / external frame of reference model for academic enjoyment. Contemporary Educational Psychology, 33, 9-33.
• Goetz, T. , Frenzel, A. C. Pekrun, N. , Hall, N. & Lüdtke, O. (2007). Between and within domain relations of students’ academic emotions. Journal of Educational Psychology, 99 (4), 715- 733.
• Goetz, T. , Pekrun, R. , Hall, N. & Haag, L. (2006). Academic emotions from a social-cognitive perspective: Antecedents and domain specificity of students’ affect in the context of Latin instruction. British Journal of Educational Psychology, 76, 289-308.
• Hair, J. F. , Anderson, R. E., Tatham, R. L. & Black, W. C. (2010). Multivariate Data Analysis (7th ed.). Prentice Hall, Inc.
• Holt, J. K. (2004, October). Item parceling in structural equation models for optimum solutions. Paper presented at the 2004 Annual Meeting of the Mid-Western Research Association, Columbus, OH.
• Hu, L. H. & Bentler, P. M. (1999). Cut off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6 (1), 1-15.
• Keshavarzi, A. & Ahmadi, S. (2013). Ahmadi, S. (2013). A comparison of mathematics anxiety among students by gender. Procedia- Social and Behavioural Sciences, 83, 542-546.
• King, R. B. & Areepathamannil, S. (2014). What students feel in school influences the strategies tjhey use for learning: Academic emotions and cognitive / metacognitive strategies. Journal of Pacific Rim Psychology, 8, 18-27.
• Kleine, M., Goetz, M., Pekrun, R. & Hall, N. (2005). The structure of students’ emotions experienced during a mathematical achievement test. The International Journal on Mathematics Education, 37(3), 221-225.
• Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling (3rd ed.). The Guilford Press.
• Knapp, T.R., & Mueller, R.O. (2010). Reliability and validity of instruments. In Hancock, G.R. & Mueller, R.O. (Eds.), The Reviewer's Guide to Quantitative Methods in the Social Sciences (337–342). London: Routledge.
• Lihtenfeld, S. , Pekrun, R. , Stupnisky, R. H. , Reiss, K. & Murayama, K. (2012). Measuring students’ emotions in the early years. The achievement emotions questionnaireelementary school (AEQ-ES). Learning and Individual Differences, 22, 190-201.
• Ma, X. (1999). A meta-analysis of the relationship between anxiety toward mathematics and achievement in mathematics. Journal for Research in Mathematics Education, 30 (5), 520-540.
• 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.
• Matsunaga, M. (2008). Item parceling in structural equation modeling: A primer. Communication Methods and Measures, 2(4), 260-293.
• Mega, C. , Ronconi, L. & De Beni, R. (2012). What makes a good students? How emotions, selfregulated learning, and motivation contribute to academic achievement. Journal of Educational Psychology, 106 (1), 121-131.
• Op ’t Eynde, P. (2004). A socio-constructivist perspective on the study of affect in mathematics education. Proceedings of the 28th Conference of the International Group for the Psychology of Mathematics Education 1, 118–122.
• Peixoto, F., Mata, L., Monteiro, V., Sanches, C. & Pekrun, R. (2015). The achievement emotions questionnaire: Validation for pre-adolescent students. European Journal of Developmental Psychology, 12(4), 472-481.
• Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18, 315–341.
• Pekrun, R., Elliot, A. J., & Maier, M. A. (2009). Achievement goals and achievement emotions: Testing a model of their joint relations with academic performance. Journal of Educational Psychology,101, 115– 597.
• Pekrun, R., Frenzel, A., Goetz, T., & Perry, R. P. (2007). The control-value theory of achievement emotions: An integrative approach to emotions in education. In P.A. Schutz & R. Pekrun (Eds.), Emotions in education (pp. 13–36). San Diego: Academic Press.
• Pekrun, R. , Goetz, T. & Frenzel, A. C. (2005). Achievement emotions questionnaire- mathematics (AEQM). User’s manual. Department of Psychology, University of Munich.
• Pekrun, R.,Goetz, T., Frenzel, A. C., Barchfeld, P., & Perry, R. P. (2011). Measuring emotions in students’ learning and performance: The Achievement Emotions Questionnaire (AEQ). Contemporary Educational Psychology, 36, 36–48.
• Pekrun , R , Goetz, T . , Titz, W . , & Perry, R P . (2002). Academic emotions in students' selfregulated learning and achievement: A program of quantitative and qualitative research. Educational Psychologist, 37, 91-106.
• Pekrun, R., Hall, N. C., Goetz, T.,& Perry, R. P. (2014). Boredom and academic achievement: Testing a model of reciprocal causation. Journal of Educational Psychology, 106, 696–710.
• Rogers, W. M., & Schmitt, N. (2004). Parameter recovery and model fit using multidimensional composites: A comparison of four empirical parcelling algorithms. Multivariate Behavioral Research, 39, 379−412.
• Schutz, P. A. & De Cuir, J. T. (2002). Inquiry on emotions in education. Educational Psychologist, 37(2), 125-134.
• Spangler, G., Pekrun, R., Kramer, K., & Hofmann, H. (2002). Students’ emotions, physiological reactions, and coping in academic exams. Anxiety, Stress and Coping, 15, 383–400.
• Sungur, S. (2004). The implementation of problem-based learning in secondary school biology courses. Unpublished Dissertation, Middle East Technical University, Ankara, Turkey.
• Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. Needham Heights, MA: Allyn and Bacon.
• Valiente, C. Swanson, J. & Eisenberg, N. (2012). Linking students’ emotions and academic achievement: when and why emotions matter. Child Development Perspectives, 6(2), 129- 135.
• Villavicencio, F. T., & Bernardo, A. B. I. (2013a). Negative emotions moderate the relationship between self-efficacy and achievement of Filipino students. Psychological Studies, 58(3), 225–232.
• Villavicencio, F. T., & Bernardo, A. B. I. (2013b). Positive academic emotions moderate the relationship between self-regulation and academic achievement. British Journal of Educational Psychology, 83, 329–340.
• Villavicencio, F. T., & Bernardo, A. B. I. (2016). Beyond math anxiety: Positive emotions predict mathematics achievement, self-regulation, and self-efficacy. The Asia-Pasific Education Research, 25(3), 415-422.
• Wigfield, A., & Meece, J. L. (1988). Math anxiety in elementary and secondary school students. Journal of Educational Psychology, 80, 210 –216.
• Yüksel-Şahin, F. (2008). Mathematics anxiety among 4th and 5th grade Turkish elementary school students. International Electronic Journal of Mathematics Education, 3(3), 179-192.
• Zeidner, M. (2007). Test anxiety in educational contexts: Concepts, findings, and future directions. In P.A. Schutz & R. Pekrun (Eds.), Emotion in education (pp. 165–184). San Diego, CA: Academic Press.