How affordances and constraints of physical and virtual manipulatives support the development of procedural fluency and algorithmic thinking in Mathematics

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Palavras-chave:

Algorithmic Thinking , Physical and Virtual Manipulatives, Algebra and Rational Number

Resumo

The purpose of this study was to examine how the affordances and constraints of physical and virtual manipulatives influence the development of students’ algorithmic thinking when learning algebra and rational number concepts. Thirty-six third-grade students participated in two weeks of instruction using physical and virtual manipulatives as instructional tools. The primary design of the study was a teaching experiment in which quantitative and qualitative data were collected to provide a holistic examination. Pre- and post-test items were used in the quantitative analysis following a within-subjects crossover repeated measures design. Students’ written work, a user survey, student interviews, field notes, and classroom videotapes were used in a qualitative analysis by coding the text data for evidence of major themes. Quantitative results indicated a significant difference between the physical and virtual manipulatives teaching episodes on students’ pre- and post-test performance that was mediated by mathematics content type (fractions vs. algebra). Qualitative results confirmed that the affordances and constraints of the virtual manipulative fraction applets supported students’ development of algorithmic thinking.

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Referências

Ball, D. L. (1992). Magical hopes: Manipulatives and the reform of math education. American Educator, 16(2), 14-18, 46-47.

Bolyard, J. (2005). The Impact of Virtual Manipulatives on Student Achievement in Integer Addition and Subtraction. Unpublished doctoral dissertation, George Mason University, Fairfax, VA.

Borenson, H. (1997). Hands-On Equations Learning System. Borenson and Associates.

Campbell, D. T. & Stanley, J. C. (1963). Experimental and quasi- experimental designs for research. New York: Houghton Mifflin Company.

Carbonneau, K. J., Marley, S. C., & Selig, J. P. (2013). A meta-analysis of the efficacy of teaching mathematics with concrete manipulatives. Journal of Educational Psychology, 105(2), 380-400.

Cifarelli, V.V. (1998). The development of mental representations as a problem solving activity. Journal for the middle grades-Level 1.Dubuque, Iowa: Kendall/Hunt.

Chao, S.-J., Stigler, J. W., & Woodward, J. A. (2000). The effects of physical materials on Kindergartners’ learning of number concepts. Cognition and Instruction, 18(3), 285-316.

Clark, J.M. & Paivio, A. (1991) Dual coding theory and education. Educational Psychology Review, 71, 64-73.

Clements, D. H. (1999). “Concrete†manipulatives, concrete ideas. Contemporary Issues in Early Childhood, 1(1), 45-60.

Dorward, J. (2002). Intuition and research: Are they compatible. Teaching Children Mathematics, 8(6), 329-332.

Fennell, F., &Rowan, T. (2001). Representation: An important process for teaching and learning mathematics. Teaching Children Mathematics, 7(5), 288-292.

Goldin, G., &Shteingold, N. (2001). Systems of representations and the development of mathematical concepts. In A. A. Cuoco & F.R. Curcio (Eds.), The roles of representations in school mathematics (pp.1-23). Reston, VA: National Council of Teachers of Mathematics.

Gravemeijer, K. & Galen, F. (2001). Facts and algorithms as products of students’ own mathematical activity. A Research Companion to Principles and Standards for School Mathematics (pp. 114-122). Reston, VA: National Council of Teachers of Mathematics.

Gurbuz, R. (2010). The effect of activity-based instruction on conceptual development of seventh grade students in probability. International Journal of Mathematical Education in Science and Technology, 41, 743–767.

Kaput, J. (1989). Linking representations in the symbol system of algebra. In C. Kieran & S. Wagner (Eds.), A Research Agenda for the Learning and Teaching of Algebra. Hillsdale, NJ: Lawrence Erlbaum.

Kelly, A. E., & Lesh, R. (2000). Handbook of research design in mathematics and science education. Mahwah, NJ: Erlbaum.

Lamon, S. J. (2001). Presenting and representing: From fractions to rational numbers. In A. A. Cuoco & F.R. Curcio (Eds.), The roles of representations in school mathematics (pp.146-165).

Reston, VA: National Council of Teachers of Mathematics. McNeil, N. M., Uttal, D. H., Jarvin, L., & Sternberg, R. J. (2009). Should you show me the money? Concrete objects both hurt and help performance on mathematics problems. Learning And Instruction, 19(2), 171-184.

Pyke, C. L. (2003). The use of symbols, words, and diagrams as indicators of mathematical cognition: A causal model. Journal of Research in Mathematics Education, 34(5), 406-432.

Rieber, L.P. (1994) Computers, Graphics and Learning. Madison, WI: WCB Brown & Benchmark.

Sowell, E. J. (1989). Effects of manipulative materials in mathematics instruction. Journal for Research in Mathematics Education, 20(5), 498-505.

Steffe, L. P. (1983). The teaching experiment methodology in a constructivist research program. Paper presented at the fourth International Congress on Mathematical Education, Boston.

Suydam, M. N. (1985). Research on instructional materials for mathematics. Columbus, OH: ERIC Clearinghouse for Science, Mathematics, and Environmental Education.

Suydam, M. N., & Higgins, J. L. (1977). Activity-based learning in elementary school mathematics: Recommendations from research. Columbus, OH: ERIC Center for Science, Mathematics & Environmental Education, College of Education, Ohio State University.

Sweller, J. (1999). Instructional design in technical areas. Camberwell, Australia: ACER Press.

Sweller, J. & Chandler P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12, 185-233.

Zbiek, R. M., Heid, M. K., Blume, G. W., & Dick, T. P. (2007). Research on technology in mathematics education: A perspective of constructs. In F. Lester (Ed.), Second handbook of research on mathematics teaching and learning, Vol. 2, (pp. 1169-1207). Charlotte, NC: Information Age.

Publicado

2016-07-01

Como Citar

SUCH, J.; MOYER-PACKENHAM, P. How affordances and constraints of physical and virtual manipulatives support the development of procedural fluency and algorithmic thinking in Mathematics. Revista Internacional de Pesquisa em Educação Matemática, v. 6, n. 2, p. 245-265, 1 jul. 2016.

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