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Educational Psychology
An International Journal of Experimental Educational Psychology
Volume 41, 2021 - Issue 6
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Articles

The association between cognitive activation and mathematics achievement: a multiple mediation model

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Pages 695-711 | Received 20 Jun 2020, Accepted 12 Apr 2021, Published online: 03 May 2021

References

  • Agger, C. A., & Koenka, A. C. (2020). Does attending a deeper learning school promote student motivation, engagement, perseverance, and achievement? Psychology in the Schools, 57(4), 627–645. https://doi.org/10.1002/pits.22347
  • Ainley, M., Hidi, S., & Berndorff, D. (2002). Interest, learning, and the psychological processes that mediate their relationship. Journal of Educational Psychology, 94(3), 545–561. https://doi.org/10.1037/0022-0663.94.3.545
  • Barnes, A. (2019). Perseverance in mathematical reasoning: The role of children’s conative focus in the productive interplay between cognition and affect. Research in Mathematics Education, 21(3), 271–294. https://doi.org/10.1080/14794802.2019.1590229
  • Bass, H., & Ball, D. L. (2015). Beyond “you can do it!”: Developing mathematical perseverance in elementary school. University of Michigan. https://www.semanticscholar.org/paper/Beyond-%22You-Can-Do-It!%22-Developing-Mathematical-in-Bass-Ball/234aa2071a16409b030bea03657cc539e4d900c4#citing-papers
  • Baumert, J., Kunter, M., Blum, W., Brunner, M., Voss, T., Jordan, A., Klusmann, U., Krauss, S., Neubrand, M., & Tsai, Y. M. (2010). Teachers’ mathematical knowledge, cognitive activation in the classroom, and student progress. American Educational Research Journal, 47(1), 133–180. https://doi.org/10.3102/0002831209345157
  • Baumert, J., Kunter, M., Blum, W., Klusmann, U., Krauss, S., & Neubrand, M. (2013). Professional competence of teachers, cognitively activating instruction, and the development of students’ mathematical literacy (COACTIV): A research program. In M. Kunter, J. Baumert, W. Blum, U. Klusmann, S. Krauss, & M. Neubrand (Eds.), Cognitive activation in the mathematics classroom and professional competence of teachers: Results from the COACTIV project (pp. 1–21). Springer.
  • Bazelais, P., Lemay, D. J., & Doleck, T. (2016). How does grit impact college students’ academic achievement in science? European Journal of Science and Mathematics Education, 4(1), 33–43. https://doi.org/10.30935/scimath/9451
  • Bollen, K. A. (1989). A new incremental fit index for general structural equation models. Sociological Methods & Research, 17(3), 303–316. https://doi.org/10.1177/0049124189017003004
  • 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. 445–455). SAGE.
  • Byrne, B. M. (2001). Structural equation modelling with AMOS: Basic concepts, applications, and programming. Lawrence Erlbaum Associates.
  • Collins, A. M., Greeno, J. G., & Resnick, L. B. (2001). Educational learning theory. In N. Smelser & P. B. Baltes (Eds.), International encyclopedia of the social and behavioral sciences (pp. 4276–4279). Elsevier.
  • Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01
  • Deci, E. L., & Ryan, R. M. (2012). Motivation, personality, and development within embedded social contexts: An overview of self-determination theory. In R. M. Ryan (Ed.), The Oxford handbook of human motivation (pp. 85–107). Oxford University Press.
  • Duckworth, A. L., Peterson, C., Matthews, M. D., & Kelly, D. R. (2007). Grit: Perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 92(6), 1087–1101. https://doi.org/10.1037/0022-3514.92.6.1087
  • Fan, L., Miao, Z., & Mok, A. C. I. (2015). How Chinese teachers teach mathematics and pursue professional development: Perspectives from contemporary international research. In L. Fan, N-Y. Wong, J. Cai, & S. Li (Eds.), How Chinese teach mathematics: Perspectives from insiders (pp. 43–70). World Scientific.
  • 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. https://doi.org/10.1016/j.learninstruc.2013.07.001
  • Fung, F., Tan, C. Y., & Chen, G. (2018). Student engagement and mathematics achievement: Unraveling main and interactive effects. Psychology in the Schools, 55(7), 815–831. https://doi.org/10.1002/pits.22139
  • Greeno, J. G., Collins, A. M., & Resnick, L. B. (1996). Cognition and learning. In D. C. Berliner & R. C. Calfee (Eds.), Handbook of educational psychology (pp. 15–46). Macmillan.
  • Gu, L., Huang, R., & Marton, F. (2004). Teaching with variation: A Chinese way of promoting effective mathematics learning. In L. Fan, N-Y. Wong, J. Cai & S. Li (Eds.), How Chinese learn mathematics: Perspectives from insiders (pp. 309–347). World Scientific.
  • Hau, K. T., & Ho, I. T. (2010). Chinese students’ motivation and achievement. In M. H. Bond (Ed.), The Oxford handbook of Chinese psychology (pp. 187–204). Oxford University Press.
  • Hidi, S. (2000). An interest researcher’s perspective: The effects of extrinsic and intrinsic factors on motivation. In C. Sansone & J. M. Harackiewicz (Eds.), Intrinsic and extrinsic motivation: The search for optimal motivation and performance (pp. 309–339). Academic Press.
  • Hiebert, J., & Grouws, D. A. (2007). The effects of classroom mathematics teaching on students’ learning. In F. K. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 371–404). Information Age.
  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
  • Klieme, E., Pauli, C., & Reusser, K. (2009). The Pythagoras study: Investigating effects of teaching and learning in Swiss and German mathematics classrooms. In T. Janik & T. Seidel (Eds.), The power of video studies in investigating teaching and learning in the classroom (pp. 137–160). Waxmann.
  • Klieme, E., Schümer, G., & Knoll, S. (2001). Mathematikunterricht in der Sekundarstufe I: “Aufgabenkultur” und Unterrichtsgestaltung [Mathematics instruction at lower secondary level: “Task culture” and quality of instruction]. In E. Klieme & J. Baumert (Eds), TIMSS – Impulse für Schule und Unterricht: Forschungsbefunde, Reforminitiativen, Praxisberichte und Video-Dokumente (pp 43–57). BMBF.
  • Krapp, A., & Prenzel, M. (2011). Research on interest in science: Theories, methods and findings. International Journal of Science Education, 33(1), 27–50. https://doi.org/10.1080/09500693.2010.518645
  • Kunter, M., & Baumert, J. (2006). Linking TIMSS to research on learning and instruction: A re-analysis of the German TIMSS and TIMSS video data. In S. J. Howie & T. Plomp (Eds.), Contexts of learning mathematics and science: Lessons learned from TIMSS (pp. 335–351). Routledge.
  • Kunter, M., Klusmann, U., Dubberke, T., Baumert, J., Blum, W., Brunner, M., Jordan, A., Krauss, S., Löwen, K., Neubrand, M., & Tsai, Y. M. (2007). Linking aspects of teacher competence to their instruction: Results from the COACTIV project. In M. Prenzel (Ed), Studies on the educational quality of schools: The final report of the DFG priority programme (pp 39–60). Waxmann.
  • Lazarides, R., & Buchholz, J. (2019). Student-perceived teaching quality: How is it related to different achievement emotions in mathematics classrooms? Learning and Instruction, 61, 45–59. https://doi.org/10.1016/j.learninstruc.2019.01.001
  • Leung, F. K. (2001). In search of an East Asian identity in mathematics education. Educational Studies in Mathematics, 47(1), 35–51. https://doi.org/10.1023/A:1017936429620
  • Li, H., Liu, J., Zhang, D., & Liu, H. (2021). Examining the relationships between cognitive activation, self‐efficacy, socioeconomic status, and achievement in mathematics: A multi‐level analysis. British Journal of Educational Psychology, 91(1), 101–126. https://doi.org/10.1111/bjep.12351
  • Li, J. (2004). Learning as a task or a virtue: U.S. and Chinese preschoolers explain learning. Developmental Psychology, 40(4), 595–605. https://doi.org/10.1037/0012-1649.40.4.595
  • Lipowsky, F., Rakoczy, K., Pauli, C., Drollinger-Vetter, B., Klieme, E., & Reusser, K. (2009). Quality of geometry instruction and its short-term impact on students’ understanding of the Pythagorean Theorem. Learning and Instruction, 19(6), 527–537. https://doi.org/10.1016/j.learninstruc.2008.11.001
  • Little, R. J., & Rubin, D. B. (2002). Statistical analysis with missing data. Wiley.
  • 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), 130–149. https://doi.org/10.1037//1082-989X.1.2.130
  • Ministry of Education, People’s Republic of China. (2012). Mathematics curriculum standard for compulsory education (2011 version). Beijing Normal University Press.
  • Neubrand, J. (2006). The TIMSS 1995 and 1999 video studies. In F. K. S. Leung, K. D. Graf, & F. J. Lopez-Real (Eds.), Mathematics education in different cultural traditions: A comparative study of East Asia and the West (pp. 291–318). Springer.
  • Neubrand, M., Jordan, A., Krauss, S., Blum, W., & Löwen, K. (2013). Task analysis in COACTIV: Examining the potential for cognitive activation in German mathematics classrooms. In M. Kunter, J. Baumert, W. Blum, U. Klusmann, S. Krauss, & M. Neubrand (Eds.), Cognitive activation in the mathematics classroom and professional competence of teachers: Results from the COACTIV project (pp. 125–144).Springer.
  • Noftle, E. E., & Robins, R. W. (2007). Personality predictors of academic outcomes: Big Five correlates of GPA and SAT scores. Journal of Personality and Social Psychology, 93(1), 116–130. https://doi.org/10.1037/0022-3514.93.1.116
  • Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18(4), 315–341. https://doi.org/10.1007/s10648-006-9029-9
  • Pekrun, R., & Stephens, E. J. (2010). Achievement emotions: A control‐value approach. Social and Personality Psychology Compass, 4(4), 238–255. https://doi.org/10.1111/j.1751-9004.2010.00259.x
  • Rakoczy, K., Klieme, E., Drollinger-Vetter, B., Lipowsky, F., Pauli, C., & Reusser, K. (2007). Structure as a quality feature in mathematics instruction of the learning environment vs. a structured presentation of learning content. In M. Prenzel (Ed.), Studies on the educational quality of schools: The final report of the DFG priority programme (pp 101–120). Waxmann.
  • Reeve, J., Lee, W., & Won, S. (2015). Interest as emotion, as affect, as schema. In K. A. Renninger, M. Nieswandt, & S. Hidi (Eds.), Interest in mathematics and science learning (pp. 79–92). American Educational Research Association.
  • Rheinberg, F., & Vollmeyer, R. (2000). Sachinteresse und leistungsthematische Herausforderung – Zwei verschiedenartige Motivationskomponenten und ihr Zusammenwirken beim Lernen. [Content interest and task demands: Two distinct components of motivation and their interaction during learning]. In U. Schiefele, & K.-P. Wild (Eds.), Interesse und Lernmotivation: Untersuchungen zu Entwicklung, Förderung und Wirkung (pp. 145–161). Waxmann.
  • Rotgans, J. I., & Schmidt, H. G. (2017). The role of interest in learning: Knowledge acquisition at the intersection of situational and individual interest. In P. A. O’Keefe & J. M. Harackiewicz (Eds.), The science of interest (pp. 69–93).Springer.
  • Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037//0003-066X.55.1.68
  • Schiefele, U. (1998). Individual interest and learning: What we know and what we don’t know. In L. Hoffmann, A. Krapp, K. A. Renninger & J. Baumert (Eds.), Interest and learning (pp. 91–104). Institut fur die Padagogik der Naturwissenschaften an der Universitat Kiel.
  • Schiefele, U., Krapp, A., & Winteler, A. (1992). Interest as a predictor of academic achievement: A meta-analysis of research. In K. A. Renninger, S. Hidi, & A. Krapp (Eds.), The role of interest in learning and development (pp. 183–211). Erlbaum.
  • 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. https://doi.org/10.3200/JOER.99.6.323-338
  • Seidel, T., & Shavelson, R. J. (2007). Teaching effectiveness research in the past decade: The role of theory and research design in disentangling meta-analysis results. Review of Educational Research, 77(4), 454–499. https://doi.org/10.3102/0034654307310317
  • 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. https://doi.org/10.1016/j.learninstruc.2005.08.004
  • Sengupta-Irving, T., & Agarwal, P. (2017). Conceptualizing perseverance in problem solving as collective enterprise. Mathematical Thinking and Learning, 19(2), 115–138. https://doi.org/10.1080/10986065.2017.1295417
  • Shayer, M., & Adhami, M. (2007). Fostering cognitive development through the context of mathematics: Results of the CAME project. Educational Studies in Mathematics, 64(3), 265–291. https://doi.org/10.1007/s10649-006-9037-1
  • Stigler, J. W., & Hiebert, J. (2004). Improving mathematics teaching. Educational Leadership, 61(5), 12–17.
  • Taylor, A. B., MacKinnon, D. P., & Tein, J. Y. (2008). Tests of the three-path mediated effect. Organizational Research Methods, 11(2), 241–269. https://doi.org/10.1177/1094428107300344
  • Wenglinsky, H. (2002). How schools matter: The link between teacher classroom practices and student academic performance. Education Policy Analysis Archives, 10(12), 12. https://doi.org/10.14507/epaa.v10n12.2002
  • Wittrock, M. C. (1986). Students’ thought processes. In M. C. Wittrock (Ed.), Handbook of research on teaching (3rd ed., pp. 297–314).Macmillan.
  • Wright, B. D., & Masters, G. N. (1982). Rating scale analysis: Rasch measurement. MESA Press.
  • 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. https://doi.org/10.1007/s12564-016-9455-4

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