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Discussion and Implications

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Book cover Cognitive and Metacognitive Problem-Solving Strategies in Post-16 Physics

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Abstract

This chapter provides final responses to the research questions: 1. How do A-level physics students in an inner London comprehensive school approach GCE A-level physics problem solving? and 2. What generative mechanisms are triggered by the explicit teaching of strategies for physics problem solving and how do these generative mechanisms compare to the existing approach? A shift in the regularities was observed which indicated the triggering and suppression of different mechanisms for successful problem solving. However, these observed regularities were different for different students. In addition to discussing the results, this chapter discusses the limitations and implications for practice.

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References

  • Abdullah, F. A. P. (2010). Patterns of physics problem-solving and metacognition among secondary schol students: a comparative study between the UK and Malaysian cases. In 5th International Conference on Interdisciplinary Social Sciences, 2–5 August 2010, University of Cambridge, United Kingdom.

    Google Scholar 

  • Artzt, A. F., & Armour-Thomas, E. (1992). Development of a cognitive-metacognitive framework for protocol analysis of mathematical problem solving. Cognition and Instruction, 9, 137–175.

    Article  Google Scholar 

  • Bandura, A. (1997). Self efficacy: The exercise of control. New York: Freeman.

    Google Scholar 

  • Bolton, J., & Ross, S. (1997). Developing students’ physics problem-solving skills. Physics Education, 32(3), 176.

    Article  Google Scholar 

  • Bong, M., & Skaalvik, E. M. (2003). Academic self-concept and self-efficacy: How different are they really? Educational Psychology Review, 15, 1–40.

    Article  Google Scholar 

  • Boudon, R. (1998.) Social mechanisms without black boxes. In P. Hedström & R. Swedberg (Eds.), (1996) Social mechanisms: An analytical approach to social theory. Cambridge: Cambridge University Press.

    Google Scholar 

  • Chi, M., & VanLehn, K. (2007). Accelerated future learning via explicit instruction of a problem solving strategy. In R. Luckin, K. R. Koedinger, & J. Greer (Eds.), The 13th International Conference on Artificial Intelligence in Education (pp. 409–416). Amsterdam, Netherlands: IOS Press.

    Google Scholar 

  • Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152.

    Article  Google Scholar 

  • Cohen, L., Manion, L., & Morrison, K. (2011). Research methods in education (7th ed.). New York: Routledge.

    Google Scholar 

  • Coleman, J. S. (1990). Foundations of social theory. Cambridge, MA: Belknap Press of Harvard University Press.

    Google Scholar 

  • Dillenbourg, P. (1999). What do you mean by ‘collaborative learning’? In P. Dillenbourg (Ed.), Collaborative learning: Cognitive and computational approaches (pp. 1–19). Oxford: Elsevier.

    Google Scholar 

  • Dori, Y. J., Mevarech, Z., & Baker, D. (2018). Cognition, metacognition and culture in STEM education. Cham, Switzerland: Springer.

    Book  Google Scholar 

  • Etkina, E., Heuvelen, A. V., & Rosengrant, D. (2009). Do students use and understand free-body diagrams? Physical Review Special Topics—Physics Education Research, 5.

    Google Scholar 

  • Ferguson-Hessler, M. G. M., & de Jong, T. (1990). Studying physics texts: Differences in study processes between good and poor performers. Cognition and Instruction, 7, 41–54.

    Article  Google Scholar 

  • Glennan, S. (2002). Rethinking mechanistic explanation. Philosophy of Science, 69, 342–353.

    Article  Google Scholar 

  • Hauser, R. M. (1976). On Boudon’s model of social mobility. American Journal of Sociology, 81(4), 911–928.

    Article  Google Scholar 

  • Hedström, P., & Swedberg, R. (Eds.). (1998). Social mechanisms. Cambridge: Cambridge University Press.

    Google Scholar 

  • Heller, P., & Hollabaugh, M. (1992). Teaching problem solving through cooperative grouping. Part 2: Designing problems and structuring groups. American Journal of Physics, 60(7), 637–644.

    Google Scholar 

  • Heller, P., Keith, R., & Anderson, S. (1992). Teaching problem solving through cooperative grouping. Part 1: Group versus individual problem solving. American Journal of Physics, 60, 627–636.

    Article  Google Scholar 

  • Hestenes, D. (1987). Toward a modelling theory of physics instruction. American Journal of Physics, 55, 440–454.

    Article  Google Scholar 

  • Hoffman, B., & Schraw, G. (2009). The influence of self-efficacy and working memory capacity on problem-solving efficiency. Learning and Individual Differences, 19, 91–100.

    Article  Google Scholar 

  • Huffman, D. (1997). Effect of explicit problem solving instruction on high school students’ problem solving performance and conceptual understanding of physics. Journal of Research in Science Teaching, 34, 551–570.

    Article  Google Scholar 

  • Jonassen, D. H. (2011). Learning to solve problems: A handbook for designing problem-solving learning environments. New York: Routledge.

    Google Scholar 

  • Kemper, E., Stringfield, S., & Teddlie, C. (2003). Mixed methods sampling strategies in social science research. In A. Tashakkori & C. Teddlie (Eds.), Handbook of mixed methods in social and behavioral research (pp. 273–296). Thousand Oaks, CA: Sage.

    Google Scholar 

  • Larkin, J. H., & Reif, F. (1979). Understanding and teaching problem solving in physics. European Journal of Science Education, 1(2), 191–203.

    Article  Google Scholar 

  • Larkin, J. H., McDermott, J., Simon, D. P., & Simon, H. A. (1980). Model of competence in solving physics problems. Cognitive Science, 4, 317–345.

    Article  Google Scholar 

  • Lombard, M., Synder-Duch, J., & Bracken, C. C. (2003). Content analysis in mass communication: Assessment and reporting of intercoder reliability. Human Communication Research, 29, 469–472.

    Article  Google Scholar 

  • Meijer, J., Veenman, M., & van Hout-Wolters, B. (2006). Metacognitive activities in text-studying and problem-solving: Development of taxonomy. Educational Research and Evaluation, 12(3), 209–237.

    Article  Google Scholar 

  • OECD. (2014). PISA 2015 Draft Collaborative Problem Solving Framework. http://www.oecd.org/pisa/pisaproducts/Draft%20PISA%202015%20Collaborative%20Problem%20Solving%20Framework%20.pdf.

  • Pajares, F., & Miller, M. D. (1995). Mathematics self-efficacy and mathematics outcomes: The need for specificity of assessment. Journal of Counselling Psychology, 42, 190–198.

    Article  Google Scholar 

  • Pawson, R. (2006). Evidence-based policy: A realist perspective. London: Sage.

    Book  Google Scholar 

  • Pintrich, P. R. (2002). The role of metacognitive knowledge in learning, teaching, and assessing. Theory into Practice, 41(4), 219–225.

    Article  Google Scholar 

  • Proctor, R. W., & Capaldi, E. J. (Eds.). (2012). Psychology of science: Implicit and explicit processes. New York: Cambridge University Press.

    Google Scholar 

  • Reif, F., & Heller, J. (1982). Knowledge structure and problem solving in physics. Educational Psychology, 17(2), 102–127.

    Article  Google Scholar 

  • Robson, C. (2011). Real world research: A resource for social-scientists and practitioner-researchers (3rd ed.). Oxford: Blackwell.

    Google Scholar 

  • Rogoff, B. (1990). Apprenticeship in thinking: Cognitive development in social context. New York: Oxford University Press.

    Google Scholar 

  • Rohrkemper, M. M. (1989). Self-regulated learning and academic achievement: A Vygotskian view. In B. J. Zimmeman & D. H. Schunk (Eds.), Self-regulated learning and academic achievement: Theory, research, and practice (pp. 143–167). New York: Springer.

    Chapter  Google Scholar 

  • Roschelle, J., & Teasley, S. (1995). The construction of shared knowledge in collaborative problem solving. In C. E. O’Malley (Ed.), Computer supported collaborative learning (pp. 69–97). Heidelberg: Springer-Verlag.

    Chapter  Google Scholar 

  • Schoenfeld, A. H. (1985). Mathematical problem solving. Orlando, FL: Academic Press.

    Google Scholar 

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

    Google Scholar 

  • Schreier, M. (2012). Qualitative content analysis in practice. London: Sage.

    Google Scholar 

  • Schunk, D. H., & Pajares, F. (2009). Self-efficacy theory. In K. R. Wenzel & A. Wigfield (Eds.), Educational psychology handbook series: Handbook of motivation at school (pp. 35–53). New York, NY: Routledge.

    Google Scholar 

  • Selçuk, G. S., Çalışkan, S., & Erol, M. (2008). Physics self-efficacy beliefs of student teachers’: The relationships with gender and achievement perception. In Balkan Physics Letters, Special Issue: Turkish Physical Society 24th International Physics Congress, 648–651.

    Google Scholar 

  • Silverman, D. (2011). Qualitative research (3rd ed.). London: Sage.

    Google Scholar 

  • Sweller, J. (1994). Cognitive load theory, learning difficulty and instructional design. Learning and Instruction, 4, 295–312.

    Article  Google Scholar 

  • Thiede, K. W., Anderson, M. C. M., & Therriault, D. (2003). Accuracy of metacognitive monitoring affects learning of texts. Journal of Educational Psychology, 95, 66–73.

    Article  Google Scholar 

  • Veenman, M. V. J., & Verheij, J. (2003). Technical students’ metacognitive skills: Relating general vs. specific metacognitive skills to study success. Learning and Individual Differences, 13, 259–272.

    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 

  • Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (A. R. Luria, M. Lopez-Morillas & M. Cole [with J. V. Wertsch], Trans.) Cambridge, Mass.: Harvard University Press. (Original work [ca. 1930–1934]).

    Google Scholar 

  • Zimmerman, B. J., & Martinez-Pons, M. (1988). Construct validation of a strategy model of student self-regulated learning. Journal of Educational Psychology, 80, 284–290.

    Article  Google Scholar 

  • Zohar, A., & Dori, Y. J. (2003). Higher order thinking skills and low achieving students—Are they mutually exclusive? The Journal of the Learning Sciences, 12(2), 145–182.

    Article  Google Scholar 

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Authors and Affiliations

  1. University of Suffolk, Suffolk, UK

    Ronald Mazorodze

  2. Institute of Education, University College London, London, UK

    Michael J. Reiss

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  1. Ronald Mazorodze
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  2. Michael J. Reiss
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Correspondence to Ronald Mazorodze .

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Mazorodze, R., Reiss, M.J. (2019). Discussion and Implications. In: Cognitive and Metacognitive Problem-Solving Strategies in Post-16 Physics. Springer, Cham. https://doi.org/10.1007/978-3-030-24686-0_5

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  • DOI: https://doi.org/10.1007/978-3-030-24686-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24685-3

  • Online ISBN: 978-3-030-24686-0

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