MODELING MULTIDIMENSIONAL MATHEMATICAL ASSESSMENT USING 6-C MATRIX: A MIXED DESIGN

Julius R. Garzon

Abstract


Dealing holistically with learning centralizes metacognitive and non-cognitive principles that must be integrated in classroom assessment. These dimensions are often overlooked in the instrumentation of assessment tools. In this premise, the researcher designed a new assessment model that looks into manifestations of reflective, affective and metacognitive domains. 6C Matrix is a six-stage tool namely Collect, Create, Concert, Conclude, Connect, and Convey aimed to assess students prior knowledge, concept explored, concept developed, feelings expressed and real-life application. Using mixed design, this study attempts to evaluate and validate the effectiveness of self-structured 6C model in assessing mathematical learning vis-à-vis stimulation of non-cognitive and metacognitive skills. Experiment using pretest-posttest approach comprised two intact groups of Grade 7 students from Libhu National High School SY 2017-2018.  Through t-test analysis, experimental group showed higher manifestations in terms of reflective practices, affective behaviors and metacognitive strategies than control group which significantly improve mathematics performance. Positive written feedbacks via thematic analysis substantiated the positive findings in the quantitative results. Based on the findings, this study concluded that 6C Model is an effective assessment tool in mathematics for students’ holistic development. Hence, 6C model is recommended for classroom-based utilization for mathematics teachers to make a difference in K12 curriculum.

Keywords


6C-stages, assessment tool, reflective-affective-metacognitive manifestations

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References


Baki, A., Çatlıoglu H., Costu, S,. Birgin, O Conceptions of high school students about mathematical connections to the real-life, Procedia Social and Behavioral Sciences, 1 (2009) 1402–1407. http://dx.doi.org/10.1016/j.sbspro.2009.01.247

Bernard, M., & Bachu, E. (2015). Enhancing the Metacognitive Skill of Novice Programmers Through Collaborative Learning Metacognition: Fundaments, Applications, and Trends (pp. 277-298): Springer.

Chi, M.T.H., & Ceci, S.J. (1987). Content knowledge: Its role, representation, and restructering in memory development. In: H.W. Reese (Ed.), Advances in child development and behavior (Vol. 20, pp. 91-142). Orlando, FL: Academic Press.

DeBellis, V.A., & Goldin, G.A. (1997). The affective domain in mathematical problemsolving. In E. Pehkonen (Ed.), Proceedings of the 21st Conference of the International Group for the Psychology of Mathematics Education,, Vol. 2 (pp. 209-216). Finland: University of Helsinki.

Desoete, A. (2009). Metacognitive prediction and evaluation skills and mathematical learning in third-grade students. Educational Research and Evaluation, 15(5), 435-446.

Glaser, R. (1990). Toward new models for assessment. International Journal of Educational Research, 14 (5), 475-483.

Goldin, G.A. (2000). Affective pathways and representations in mathematical problem solving. Mathematical Thinking and Learning, 17, 209-219.

Grant, G. (2014). A metacognitive-based tutoring program to improve mathematical abilities of rural high school students: An action research study. (Ph.D), Capella University.

Grizzle-Martin, T. (2014). The Effect of Cognitive-and Metacognitive-Based Instruction on Problem Solving by Elementary Students with Mathematical Learning Difficulties. (Ph.D), Walden University

Jonassen, D.H. & Grabowski, B.L. (1993). Handbook of individual differences, learning, and instruction. Part VII, Prior knowledge. Hillsdale: Lawrence Erlbaum Associates.

Kluwe, R. H. (1982). Cognitive knowledge and executive control: Metacognition Animal mind— human mind (pp. 201-224): Springer.

Mason, J., Burton, L., & Stacey, K. (1982). Thinking mathematically. London: Addison-Wesley.

McLeod, D. B., & Adams, V. M., Eds. (1989). Affect and mathematical problem solving: Anew perspective . New York: Springer-Verlag

National Council of Teachers of Mathematics (NCTM). (2000). Principles and standards for school mathematics. Reston, VA: National Council of Teachers of Mathematics.

Nohda, N. (1991). Paradigm of the 'open-approach' methods in mathematics teaching: Focus on mathematical problem solving. ZDM, 91(2), 32-37.

Peña-Ayala, A., & Cárdenas, L. (2015). A Conceptual Model of the Metacognitive Activity Metacognition: Fundaments, Applications, and Trends (pp. 39-72): Springer.


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