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The role of metacognitive monitoring in explaining differences in mathematics achievement

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Abstract

The relationship between practised monitoring activities and performance, especially in mathematics was examined within three nested studies. The first study deals with problems of faulty term rewritings submitted to three groups of subjects—10th to 13th graders, differing in their mathematical performance—whose task was to find the mistakes. Moreover, a questionnaire on the practice and appreciation of monitoring activities was developed. The third study, first, repeats the first study with a similar population and secondly adds interviews with some of the subjects while solving additional items concerning faulty term rewritings. Studies 1 and 3 show similar success in finding mistakes and in the replies to the questionnaire within the various groups. Furthermore, the third study points up that the subject’s answers do neither predict the practised monitoring nor the success in the test. However, the success correlates significantly with the practised monitoring. For a deeper understanding concerning the role of metacognition in explaining performance, the second study examined two of the groups who had already been involved in the first study. These were assigned some problems of a matrices test as used in cognitive psychology. While trying to solve the problem, their eye movements were recorded by means of an eye-tracker. Afterwards they had to justify their solutions in an interview. The eye movements were analysed, the verbal comments classified. Again, the groups differ in their problem solving success, dependant on the quality of the monitoring practised. Altogether, the results of the three studies elucidate the importance of practised metacognitive monitoring activities not only for success in school algebra, but furthermore the ability and the willingness to do it is deeper anchored in a person than just a trained behaviour for school algebra.

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Notes

  1. The project “Analyse von Unterrichtssituationen zur Einübung von Reflexion und Metakognition im gymnasialen Mathematikunterricht der SI” was supported by Deutsche Forschungsgemeinschaft under Co 96/5-1.

  2. By discursivity, we summarize students’ and teachers behaviour to insure that, for example, contributions are tied to the matter discussed or the problem given.

  3. In the Germany states there is a divided school system with varying academic orientation, the most demanding of which is the “Gymnasium”. Approx. the upper third of an age cohort attends a “Gymnasium”.

  4. This subcategory has been newly introduced in addition to the categorizing system. It describes a monitoring activity of a person’s own monitoring processes from a meta-meta-level.

References

  • Armbrust, S. (2006). Die Werkzeuge “CoDyLa” und “QuaDiPF-Eye” zur Untersuchung funktionalen/prädikativen Denkens sowie ihre empirische Erprobung. Osnabrück: Forschungsinstitut für Mathematikdidaktik.

    Google Scholar 

  • Armbrust, S., Schwank, I., & Libertus, M. (2002). Augenblickbewegungen beim Lösen von Matrizenaufgaben (QuaDiPF). In E. van der Meer, H. Hagendorf, R. Beyer, F. Krüger, A. Nuthmann, & S. Schulz (Eds.), 43. Kongress der Deutschen Gesellschaft für Psychologie (p. 378). Lengerich: Pabst Science Publishers.

    Google Scholar 

  • Artelt, C. (2000). Strategisches Lernen. Münster: Waxmann.

    Google Scholar 

  • Brinkschmidt, S. (2005). Über die Unterschiedlichkeit kognitiver sowie metakognitiver Prozesse beim Bearbeiten von QuaDiPF-Aufgaben—Empirische Untersuchungen mit Blickbewegungsanalysen. Osnabrück: Forschungsinstitut für Mathematikdidaktik.

    Google Scholar 

  • Carpenter, P. A., & Just, M. A. (1976). Eye fixations and cognitive processes. Cognitive Psychology, 8, 441–480.

    Article  Google Scholar 

  • Carpenter, P. A., Just, M. A., & Shell, P. (1990). What one intelligence test measures: A theoretical account of the processing in the Raven progressive matrices test. Psychological Review, 97(3), 404–431.

    Article  Google Scholar 

  • Cohors-Fresenborg, E., & Kaune, C. (2003). Unterrichtsqualität: Die Rolle von Diskursivität für “guten” gymnasialen Mathematikunterricht. In Beiträge zum Mathematikunterricht 2003 (pp. 173–180). Hildesheim: Franzbecker.

    Google Scholar 

  • Cohors-Fresenborg, E., & Kaune, C. (2007a). Modelling classroom discussions and categorising discursive and metacognitive activities. In D. Pitta-Pantazi, G. Philippou (Ed.), European research in mathematics education V—Proceedings of the fifth congress of the European Society for Research in Mathematics Education (pp. 1180–1189). Larnaca: Department of Education, University of Cyprus.

    Google Scholar 

  • Cohors-Fresenborg, E., & Kaune, C. (2007b). Kategoriensystem für metakognitive Aktivitäten beim schrittweise kontrollierten Argumentieren im Mathematikunterricht 2. überarbeitete Auflage. Arbeitsbericht Nr. 44. Osnabrück: Forschungsinstitut für Mathematikdidaktik.

    Google Scholar 

  • Cohors-Fresenborg, E., & Schwank, I. (1997). Individual differences in the managerial representation of business processes. In R. Pepermans, A. Buelens, C. Vinkenburg, & P. Jansen (Eds.), Managerial behaviour and practices: European research issues (pp. 93–106). Leuven: Acco.

    Google Scholar 

  • Cohors-Fresenborg, E., Sjuts, J., & Sommer, N. (2004). Komplexität von Denkvorgängen und Formalisierung von Wissen. In M. Neubrand (Hrsg.), Mathematische Kompetenzen von Schülerinnen und Schülern in Deutschland: Vertiefende Analysen im Rahmen von PISA-2000 (pp. 109–144). Wiesbaden: Verlag für Sozialwissenschaften.

    Google Scholar 

  • De Corte, E., & Verschaffel, L. (1986). Eye-movements of first graders during word problem solving. In M. Askew (Ed.), Proceedings of the International Conference for Psychology of Mathematics Education (PME10) (pp. 421–426). London: University of London, Institute of Education.

    Google Scholar 

  • De Corte, E., & Verschaffel, L. (1987). First graders eye movements during elementary addition and subtraction word problem solving. In G. Lüer & U. Lass (Eds.), Fourth European Conference on Eye Movements, Volume 1: Proceedings (pp. 148–150). Göttingen: Hogrefe.

    Google Scholar 

  • Flavell, J. (1976). Metacognitive aspects of problem solving. In L. Resnik (Ed.), The nature of intelligence (pp. 231–236). Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Gundlach, K.-B. (1968). Kenntnisse der Abiturienten und Studienerfolg in den Anfängervorlesungen im Fach Mathematik. Mathematisch-Physikalische Semesterberichte, XV, 20–31.

  • Kaune, C. (2006). Reflection and metacognition in mathematics education—Tools for the improvement of teaching quality. Zentralblatt für Didaktik der Mathematik, 38(4), 350–360.

    Article  Google Scholar 

  • Kramarski, B., & Mevarech, Z. R. (2003). Enhancing mathematical reasoning in the classroom: The effects of cooperative learning and metacognitive training. American Educational Research Journal, 40(1), 281–310.

    Article  Google Scholar 

  • Lind, G., & Sandmann, A. (2003). Lernstrategien und Domänenwissen. Zeitschrift für Psychologie, 211(4), 171–192.

    Article  Google Scholar 

  • Mevarech, Z. R., & Amrany, C. (2008). Immediate and delayed effects of meta-cognitive instruction on regulation of cognition and mathematics achievement. Metacognition and Learning, 3, 147–157.

    Article  Google Scholar 

  • Mölle, M., Schwank, I., Marshall, L., Klöhn, A., & Born, J. (2000). Dimensional complexity and power spectral measures of the EEG during functional versus predicative problem solving. Brain and Cognition, 22(3), 547–563.

    Article  Google Scholar 

  • Neubrand, M., Biehler, R., Blum, W., Cohors-Fresenborg, E., Flade, L., Knoche, N., et al. (2001). Grundlagen der Ergänzung des internationalen PISA-Mathematiktests in der deutschen Zusatzerhebung. Zentralblatt für Didaktik der Mathematik, 33(2), 45–59.

    Article  Google Scholar 

  • Neubrand, M., Biehler, R., Blum, W., Cohors-Fresenborg, E., Flade, L., Knoche, N., et al. (2004a). Eine systematische und kommentierte Auswahl von Beispielaufgaben des Mathematiktests in PISA 2000. In M. Neubrand (Hrsg.), Mathematische Kompetenzen von Schülerinnen und Schülern in Deutschland: Vertiefende Analysen im Rahmen von PISA-2000 (pp. 259–270). Wiesbaden: Verlag für Sozialwissenschaften.

    Google Scholar 

  • Neubrand, M., Biehler, R., Blum, W., Cohors-Fresenborg, E., Flade, L., Knoche, N., et al. (2004b). Der Prozess der Itementwicklung bei der nationalen Ergänzungsuntersuchung von PISA 2000: Vom theoretischen Rahmen zu den konkreten Aufgaben. In M. Neubrand (Hrsg.), Mathematische Kompetenzen von Schülerinnen und Schülern in Deutschland: Vertiefende Analysen im Rahmen von PISA-2000 (pp. 31–49). Wiesbaden: Verlag für Sozialwissenschaften.

  • Polya, G. (1945). How to solve it. Princeton: Princeton University Press.

    Google Scholar 

  • Pundsack, F. (2009). Zusammenhang von Monitoring und mathematischer Leistung—eine (empirische) Studie und Entwicklung eines Trainingsprogramms. Unpublished Master Thesis. Osnabrück: Universität Osnabrück.

  • Raven, J. C. (1965). Advanced progressive matrices. Sets I and II. London: Lewis.

    Google Scholar 

  • Schoenfeld, A. H. (1985). Metacognitive and epistemological issues in mathematical understanding. In E. A. Silver (Ed.), Teaching and learning mathematical problem solving: Multiple research perspectives (pp. 361–380). Hillsdale, NJ: Erlbaum.

  • Schoenfeld, A. H. (1992). Learning to think mathematically: Problem solving, metacognition, and sense making in mathematics. In D. A. Grouws (Ed.), Handbook of research on mathematics teaching and learning (pp. 334–370). New York: Macmillan.

    Google Scholar 

  • Schwank I. (1986). Cognitive structures of algorithmic thinking. In Proceedings of the 10th conference for the psychology of mathematics education (pp. 195–200). University of London, Institute of Education, London

  • Schwank, I. (1993). On the analysis of cognitive structures in algorithmic thinking. Journal of mathematical behaviour, 12(2), 209–231.

    Google Scholar 

  • Schwank, I. (1998). QuaDiPF—Qualitative diagnostic instrument for predicative versus functional thinking. Osnabrück: Forschungsinstitut für Mathematikdidaktik.

    Google Scholar 

  • Schwank, I. (2001). Analysis of eye-movements during functional versus predicative problem solving. In J. Novotna (Ed.), European research in mathematics education II (pp. 489–498). Prague: Charles University.

  • Schwank, I. (2003). Einführung in prädikatives und funktionales Denken. Zentralblatt für Didaktik der Mathematik, 38(4), 350–360.

    Google Scholar 

  • Sjuts, J. (2003). Metakognition per didaktisch-sozialem Vertrag. Journal für Mathematik-Didaktik, 24(1), 18–40.

    Google Scholar 

  • Sjuts, J., & Xu, B. Y. (2007). Mehr Erfolg mit Metakognition? Ergebnisse einer chinesisch-deutschen Vergleichsuntersuchung. SEMINAR, Lehrerbildung und Schule, 12(2), 59–75.

    Google Scholar 

  • Veenman, M. V. J., Kok, R., & Blöte, A. W. (2005). The relation between intellectual and metacognitive skills in early adolescence. Instructional Science, 33, 193–211.

    Article  Google Scholar 

  • Veenman, M. V. J., Van Hout-Wolters, B. H. A. M., & Afflerbach, P. (2006). Metacognition and learning: conceptual and methodological considerations. Metacognition and Learning, 1, 3–14.

    Article  Google Scholar 

  • Velichkovsky, B. M., Sprenger, A., & Unema, P. J. A. (1997). Towards gaze-mediated interaction: Collecting solutions of the “Midas touch problem”. In S. Howard, J. Hammond, & G. Lindgaard (Eds.), Human-Computer Interaction: INTERACT ’97. London: Chapman & Hall.

    Google Scholar 

  • Wang, M. C., Haertel, G. D., & Walberg, H. J. (1993). Toward a knowledge base for school learning. Review of Educational Research, 63(3), 249–294.

    Google Scholar 

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Correspondence to Elmar Cohors-Fresenborg.

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Cohors-Fresenborg, E., Kramer, S., Pundsack, F. et al. The role of metacognitive monitoring in explaining differences in mathematics achievement. ZDM Mathematics Education 42, 231–244 (2010). https://doi.org/10.1007/s11858-010-0237-x

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