Session Information
27 SES 04 C, Parallel Paper Session
Parallel Paper Session
Contribution
Along with a number of other East Asian countries or cities and one Northern European country (Finland), Singapore has led the world in international assessments in Mathematics, Science and Reading. In PISA 2009, for example, Singapore ranked second in Mathematics, fourth in science and fifth in reading literacy. In this paper we attempt to offer a partial account of why it has done so well by focusing on the character of instructional tasks in a national sample of Secondary 3 English and Mathematics classes. Specifically, we (1) develop a general conceptual model of the structure of instructional tasks, (2) test the validity empirically of two key elements of this revisionist model – the epistemic and cognitive framing of instructional tasks -- in Secondary 3 mathematics and English classes in Singapore, (3) use a combination of descriptive statistics, confirmatory factor analyses, and structural equation model to identify the pattern and strength of the relationships between key features of the model, and (4), briefly explore the relationships between instructional tasks and other aspects of instructional task. Theoretically, the study draws on recent work in epistemology, disciplinarity, instructional design, cognitive science, functional systemic grammar and the sociology of knowledge as well as the rich analytical capacities of confirmatory factor analysis and structural equation modelling.
In the paper we address five research questions:
1. 1. How might we usefully conceptualize the internal structure and composition of instructional tasks and their relationship to other instructional practices (instructional methods/strategies, classroom talk, curriculum materials and resources, classroom organization, and classroom environment)?
2. 2. What is the nature and extent of the epistemic framing of instructional tasks? Specifically, what is the epistemic focus of instructional tasks (factual, procedural, conceptual, epistemic, hermeneutical, rhetorical etc) and what kinds of domain-specific knowledge work or practices does the instructional task require students, at least in principle, to engage in? How are these elements related to each other? To what extent do the epistemic elements of instructional tasks vary by subject, class, stream and school?
3. 3. To what extent does the epistemic tasks approximate normative disciplinary models of domain specific knowledge practice?
4. 4. What is the nature and extent of the cognitive framing of instructional tasks? What kind of cognitive demands do tasks place on students? To what extent are the cognitive demands of instructional tasks a design feature of the instructional tasks or a contingent artefact of the instructional tasks chosen by the teacher? How are these elements related to each other? To what extent do the cognitive demands of instructional tasks vary by subject, class, stream and school?
5. 5. How tightly are the epistemic and cognitive aspects of instructional tasks linked to other aspects of instructional practice in the classroom?
The paper will particularly rely on structural equation modelling statistical procedures to identify the pattern and strength of the pathways between the various components of instructional tasks and estimate the overall goodness of fit of the theoretically specified model to the data.
Method
Expected Outcomes
References
Anderson, L., and Krathwohl, D., eds. (2001). A Taxonomy for Learning, Teaching and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. New York: Longmans. Boaler, J. (2002a) “The Development of Disciplinary Relationships: Knowledge, Practice and Identity in Mathematics Classrooms. Proceedings of the Annual Meeting of the International Group for the Psychology of Mathematics Education, July 21-26. Collins, A., Brown, J.S. & Newman, S.E. (1989). Cognitive apprenticeship: Teaching the craft of reading, writing and matematics. In L.B. Resnick (Ed.), Knowing, learning and instruction: Essays in honor of Robert Glaser. Hillsdale, NJ: Erlbaum, pp. 453-494. Doyle, W. (1983). Academic Work. Review of Educational Research, 53(2), 159-199. Hiebert, J., & Lefevre, P. (1986). Conceptual and procedural knowledge in mathematics: An introductory analysis. In J.Hiebert (Ed.), Conceptual and procedural knowledge: The case of mathematics. Hillsdale, NJ: Erlbaum, pp. 1-27. Hiebert, James et al., (1997). Making Sense: Teaching and Learning Mathematics With Understanding. Portsmouth, NH: Heinmann. Lave, J. and Wenger, E. (1991); Situated Learning: Legitimate Peripheral Participation. Cambridge: Cambridge University Press. Putnam, R., Lampert, M., & Peterson, P. (1990). Alternative perspectives on knowing mathematics in elementary schools. Review of Research in Education, 16, pp. 57-150. Rittle-Johnson, B. & Alibali M.W. (1999). Conceptual and procedural knowledge of mathematics: Does one lead to the other? Journal of Educational Psychology, 91, No.1, pp. 175-189. 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. New York: MacMillan, pp. 334-370. Sfard, A. (2008). Thinking as Communication: Human Development, The Growth of Discourses, and Mathematizing. Cambridge: Cambridge University Press. Stein, M. and Lane, S. (1996). 'Instructional Tasks and the Development of Student Capacity to Think and Reason: An Analysis of the Relationship between Teaching and Learning in a Reform Mathematics Project', Educational Research and Evaluation, 2: 1, 50 — 80.
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