Accommodating heterogeneity: the interaction of instructional scaffolding with student preconditions in the learning of hypothesis-based reasoning
Tóm tắt
Hypothesis-based reasoning with conditionals is a skill that is required for engaging in integral activities of modern elementary school science-curricula. The teaching of this skill at this early stage of education, however, is demanding, particularly in whole school classes in which it is difficult to adapt teaching to children’s individual needs. We examine whether a scaffold that is static yet tailored to the context, in which the teacher explicitly models the reasoning process, manages to meet students’ individual cognitive preconditions for learning this skill. Within an inquiry-based learning setting, N = 143 third-graders underwent either an experimental condition in which they received the explicit scaffold, or a control condition in which they did not receive this specific scaffold. Employing a latent transition analysis and a general additive model, it is examined how the additional scaffold interacted with students’ prior knowledge, inhibition ability, and logical reasoning judged by their own teachers. It is found that the additional scaffolds managed to meet the needs of students with little prior knowledge; under the control condition, students with little prior knowledge showed decreased learning achievement, whereas under the experimental condition, students with differing prior knowledge learned to comparable extent and on a higher level. The scaffolds also almost fully diminished a disadvantage for students with lower teacher-judged logical reasoning, and supported students with high inhibition ability in mastering the most difficult aspect of reasoning based on irrelevant evidence. Implications for science education are discussed.
Tài liệu tham khảo
Archibald, S. J., & Kerns, K. A. (1999). Identification and description of new tests of executive functioning in children. Child Neuropsychology, 5, 115–129
Barrouillet, P., Gauffroy, C., & Lecas, J. F. (2008). Mental models and the suppositional account of conditionals. Psychological Review, 115, 760–772
Barrouillet, P., & Lecas, J. F. (1999). Mental models in conditional reasoning and working memory. Thinking & Reasoning, 5, 289–302.
Brush, T. A., & Saye, J. W. (2002). A summary of research exploring hard and soft scaffolding for teachers and students using a multimedia supported learning environment. The Journal of Interactive Online Learning, 1, 1–13.
Bybee, R. (2002). Scientific literacy - mythos oder realität? In W. Gräber, P. Nentwig, T. Koballa, & R. Evans (Eds.), Scientific literacy. Der Beitrag der Naturwissenschaften zur Allgemeinen Bildung (pp. 21–43). Wiesbaden: VS Verlag für Sozialwissenschaften.
Corno, L. (2008). On teaching adaptively. Educational Psychologist, 43, 161–173.
Cronbach, L. J., & Snow, R. (1977). Aptitudes and instructional methods. New York: Irvington.
Decristan, J., Fauth, B., Kunter, M., Büttner, G., & Klieme, E. (2017). The interplay between class heterogeneity and teaching quality in primary school. International Journal of Educational Research, 86, 109–121
Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64, 135–168
Dumont, H. (2018). Neuer Schlauch für alten Wein? Eine konzeptuelle Betrachtung von individueller Förderung im Unterricht. Zeitschrift für Erziehungswissenschaft, 103, 1–29
Dunn, T. J., Baguley, T., & Brunsden, V. (2014). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology, 105, 399–412
Gauffroy, C., & Barrouillet, P. (2009). Heuristic and analytic processes in mental models for conditionals: An integrative developmental theory. Developmental Review, 29, 249–282
Gauffroy, C., & Barrouillet, P. (2011). The primacy of thinking about possibilities in the development of reasoning. Developmental psychology, 47, 1000–1011
Greiff, S., & Heene, M. (2017). Why psychological assessment needs to start worrying about model fit. European Journal of Psychological Assessment, 33, 313–317
Grimm, H., Robisch, C., & Möller, K. (2018). Förderung hypothesenbezogener Schlussfolgerungen im naturwissenschaftlichen Sachunterricht durch gezieltes Scaffolding—Gelingt dies unter Feldbedingungen? Zeitschrift für Grundschulforschung, 11, 349–363.
Handley, S. J., Capon, A., Beveridge, M., Dennis, I., & Evans, J. S. B. (2004). Working memory, inhibitory control and the development of children’s reasoning. Thinking & Reasoning, 10, 175–195
Hattie, J. (2009). Visible learning. A synthesis of over 800 meta-analyses relating to achievement. London: Routledge
Hertel, S. (2014). Adaptive Lerngelegenheiten in der Grundschule: Merkmale, methodisch-didaktische Schwerpunktsetzungen und erforderliche Lehrerkompetenzen. In B. Kopp, S. Martschinke, M. Munser-Kiefer, M. Haider, E. M. Kirschhock, & G. Ranger (Eds.), Individuelle Förderung und Lernen in der Gemeinschaft (pp. 19–34). Wiesbaden: Springer VS
Hickendorff, M., Edelsbrunner, P. A., McMullen, J., Schneider, M., & Trezise, K. (2018). Informative tools for characterizing individual differences in learning: Latent class, latent profile, and latent transition analysis. Learning and Individual Differences, 66, 4–15
Hogan, K., & Pressley, M. (1997). Scaffolding scientific competencies within classroom communities of inquiry. In K. Hogan (Ed.), Scaffolding student learning. Instructional approaches and issues (pp. 75–107). Cambridge: Brookline Books.
Jansen, S., Mannhaupt, G., Marx, H., & Skowronek, H. (1999). Bielefelder Screening zur Früherkennung von Lese-Rechtschreibschwierigkeiten. Göttingen: Hogrefe
Johnson-Laird, P. N., & Byrne, R. M. J. (2002). Conditionals: A theory of meaning, pragmatics, and inference. Psychological Review, 109, 646–678
Kang, S., Scharmann, L. C., & Noh, T. (2004). Reexamining the role of cognitive conflict in science concept learning. Research in Science Education, 34, 71–96
Koerber, S., Mayer, D., Osterhaus, C., Schwippert, K., & Sodian, B. (2015). The development of scientific thinking in elementary school: A comprehensive inventory. Child Development, 86(1), 327–336
Kyllonen, P. C., & Lajoie, S. P. (2003). Reassessing aptitude: Introduction to a special issue in honor of Richard E. snow. Educational Psychologist, 83, 79–83.
Lazonder, A. W., & Harmsen, R. (2016). Meta-analysis of inquiry-based learning. Review of Educational Research, 86, 681–718.
Lederman, N., Lederman, J., & Antink, A. (2013). Nature of science and scientific inquiry as contexts for the learning of science and achievement of scientific literacy. International Journal of Education in Mathematics Science and Technology, 1, 138–147.
Machts, N., Kaiser, J., Schmidt, F. T. C., & Möller, J. (2016). Accuracy of teachers’ judgments of students’ cognitive abilities: A meta-analysis. Educational Research Review, 19, 85–103
Martin, N. D., Tissenbaum, D., Gnesdilow, C., & Puntambekar, S. (2018). Fading distributed scaffolds: The importance of complementarity between teacher and material scaffolds. Instructional Science, 53, 1–30.
NGSS (2013). Next generation science standards for today’s students and tomorrow’s workforce (second draft; Appendix F). Washington: Archieve, Inc. with NRC, NISTA, AAAS. Retrieved from https://www.nextgenscience.org/ Accessed 16 April 2020
Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural equation modeling, 14, 535–569
Opitz, A., Heene, M., & Fischer, F. (2021). Using differential item functioning to analyze the domain generality of a common scientific reasoning test. European Journal of Psychological Assessment, 38(4), 251–260. https://doi.org/10.1027/1015-5759/a000662
Pea, R. (2004). The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity. Journal of the Learning Sciences, 13, 423–451
Pianta, R. C., & Hamre, B. K. (2009). Conceptualization, measurement, and improvement of classroom processes: Standardized observation can leverage capacity. Educational Researcher, 38, 109–119.
Piekny, J., Grube, D., & Maehler, C. (2013). The relation between preschool children’s false-belief understanding and domain-general experimentation skills. Metacognition and Learning, 8, 103–119.
Popper, K. R. (1972). Objective knowledge. Oxford: Oxford University Press
Posner, G., Strike, K., Hewson, P., & Gertzog, W. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66, 211–227
Puntambekar, S., & Hübscher, R. (2005). Tools for scaffolding students in a complex learning environment: What have we gained and what have we missed? Educational Psychologist, 40, 1–12
Randi, J., & Corno, L. (2005). Teaching and learner variation. British Journal of Educational Psychology, 3, 47–69
Reiser, B. J. (2004). Scaffolding complex learning: The mechanisms of structuring and problematizing student work. The Journal of the Learning Sciences, 13, 273–304.
Robisch, C., Tröbst, S., & Möller, K. (2014). Hypothesenbezogene Schlussfolgerungen im Grundschulalter fördern. Zeitschrift für Grundschulforschung, 2, 88–101
Roll, I., Butler, D., Yee, N., Welsh, A., Perez, S., & Briseno, A. (2018). Understanding the impact of guiding inquiry: the relationship between directive support, student attributes, and transfer of knowledge, attitudes, and behaviours in inquiry learning. Instructional Science, 46, 77–104
Sandoval, W. A., Sodian, B., Koerber, S., & Wong, J. (2014). Developing children's early competencies to engage with science. Educational Psychologist, 49(2), 139–152. https://doi.org/10.1080/00461520.2014.917589
Schauble, L. (1996). The development of scientific reasoning in knowledge-rich contexts. Developmental Psychology, 32, 102–119
Schneider, M., & Hardy, I. (2013). Profiles of inconsistent knowledge in children’s pathways of conceptual change. Developmental Psychology, 49, 1639–1649
Schnotz, W. (2010). Reanalyzing the expertise reversal effect. Instructional Science, 38, 315–323
Schroeders, U., Schipolowski, S., Zettler, I., Golle, J., & Wilhelm, O. (2016). Do the smart get smarter? Development of fluid and crystallized intelligence in 3rd grade. Intelligence, 59, 84–95
Schwichow, M., Croker, S., Zimmerman, C., Höffler, T., & Härtig, H. (2016). Teaching the control-of-variables strategy: A meta-analysis. Developmental Review, 39, 37–63
Scott, C. (2013). The search for the key for individualized instruction. In J. Hattie & E. M. Andermann (Eds.), International guide to student achievement. Educational psychology handbook series (pp. 385–388). New York, NY: Routledge.
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, 454–499.
Seiz, J., Decristan, J., Kunter, M., & Baumert, J. (2016). Differenzielle Effekte von Klassenführung und Unterstützung für Schülerinnen und Schüler mit Migrationshintergrund. Zeitschrift für Pädagogische Psychologie, 30, 237–249
Simonsmeier, B. A., Flaig, M., Deiglmayr, A., Schalk, L., & Schneider, M. (2022). Domain-specific prior knowledge and learning: A meta-analysis. Educational Psychologist, 57, 31–54
Sodian, B., Zaitchik, D., & Carey, S. (1991). Young children’s differentiation of hypothetical beliefs from evidence. Child Development, 62, 753–766
Subban, P. (2006). Differentiated instruction: A research basis. International Education Journal, 7, 935–947
Südkamp, A., Kaiser, J., & Möller, J. (2012). Accuracy of teachers’ judgments of students’ academic achievement: A meta-analysis. Journal of Educational Psychology, 104, 743–762
Suprayogi, M. N., Valcke, M., & Godwin, R. (2017). Teachers and their implementation of differentiated instruction in the classroom. Teaching and Teacher Education, 67, 291–301
Thiel, S. (1987). Wie springt ein Ball? Grundschule, 1, 18–23
Tiego, J., Testa, R., Bellgrove, M. A., Pantelis, C., & Whittle, S. (2018). A hierarchical model of inhibitory control. Frontiers in Psychology, 9, 1339.
Tomlinson, C. A., Brighton, C., Hertberg, H., Callahan, C. M., Moon, T. R., & Brimijoin, K. (2003). Differentiating instruction in response to student readiness, interest, and learning profile in academically diverse classrooms: A review of literature. Journal for the Education of the Gifted, 27, 119–145.
Vaci, N., & Bilalić, M. (2017). Chess databases as a research vehicle in psychology: Modeling large data. Behavior research methods, 49, 1227–1240
van de Pol, J., Volman, M., & Beishuizen, J. (2010). Scaffolding in teacher–student interaction. A decade of research. Educational Psychology Review, 22, 271–296.
Vergauwe, E., Gauffroy, C., Morsanyi, K., Dagry, I., & Barrouillet, P. (2013). Chronometric evidence for the dual-process mental model theory of conditional. Journal of Cognitive Psychology, 25, 174–182
Vorholzer, A., Aufschnaiter, C., & Boone, W. J. (2018). Fostering upper secondary students’ ability to engage in practices of scientific investigation: A comparative analysis of an explicit and an implicit instructional approach. Research Science Education, 103, 1–27.
Vosniadou, S. (2019). The development of students’ understanding of science. Frontiers in Education, 4, 32.
Wagensveld, B., Segers, E., Kleemans, T., & Verhoeven, L. (2015). Child predictors of learning to control variables via instruction or self-discovery. Instructional Science, 43, 365–379
Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem-solving. Journal of Child Psychology and Psychiatry and Allied Disciplines, 17, 89–100