遊戲式電腦化心算解題能力評量的發展

本研究發展遊戲式電腦化心算解題能力評量（Game-Based Computerized Assessment on Mental Arithmetic, GBCAMA），依據遊戲進行所需的不同心算策略與運算複雜度編擬21項解題任務，希望了解國小中年級學生心算解題能力的表現概況。結果顯示測驗架構可解釋68%心算任務的難度變異。心算解題能力達到基礎水準的學生，能提取常用心算策略來解決低運算負荷的問題（答對率60%）。未達基礎水準學生，這類問題的答對率為28%，亟需有趣而意義化的心算解題學習扶助介入。四年級男學生心算解題能力明顯優於女學生，三年級男、女學生的差異則未達顯著。

關鍵字

心算策略；心算解題能力；運算複雜度；遊戲式評量

並列摘要

The purpose of this study is to develop a Game-Based Computerized Assessment on Mental Arithmetic (GBCAMA). The GBCAMA focused on the authentic scenario of mental arithmetic and the advantages of game-based task designs. A two elements model of working memory loading was proposed for the task difficulty of mental arithmetic. They are strategy load and computation load. Basing upon different levels of strategy load and computation complexity, 21 mental arithmetic problem solving tasks were developed for GBCAMA. There are 506 3rd & 4th graders sampled as the norm for GBCAMA. The results reveal the reasonable support for the construct validity. The correlation coefficient between mental arithmetic ability and school math grade is higher than the correlation coefficients between mental arithmetic ability and the other subjects' grades. The two elements model of strategy load and computation complexity can account for 68% variance of item difficulty. The 4th graders perform better than the 3rd graders on GBCAMA. The students of basic level of mental arithmetic ability can retrieve common strategies to solve the simple computation problems. For students below the basic level, intervention programs based upon meaningful context and focusing on both computation practices and applicable strategies are needed for them to develop these important numerical competencies more efficiently.

並列關鍵字

computation strategy ； mental arithmetic problem-solving ability ； computation complexity ； game-based assessment

參考文獻

劉曼麗、侯淑芬（2006）。整數數感融入國小四年級數學科教學之研究。科學教育學刊，14 （2），121-147。 doi: 10.6173/CJSE.2006.1402.01

Swanson, H. L. (2004). Working Memory and Phonological Processing as Predictors of Children’s Mathematical Problem Solving at Different Ages. Memory & Cognition, 32(4), 648-661. doi: 10.3758/bf03195856

Thompson, C. A., & Opfer, J. E. (2008). Costs and Benefits of Representational Change: Effects of Context on Age and Sex Differences in Symbolic Magnitude Estimation. Journal of Experimental Child Psychology, 101(1), 20-51. doi: 10.1016/j.jecp.2008.02.003

Torbeyns, J., & Verschaffel, L. (2013). Efficient and Flexible Strategy Use on Multi-Digit Sums: A Choice / No-Choice Study. Research in Mathematics Education, 15(2), 129-140. doi: 10.1080/14794802.2013.797745

Vanbinst, K., & De Smedt, B., (2016). Individual Differences in Children’s Mathematics Achievement: The Roles of Symbolic Numerical Magnitude Processing and Domain-General Cognitive Functions. Progress in Brain Research, 227, 105-130. doi: 10.1016/bs.pbr.2016.04.001

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遊戲式電腦化心算解題能力評量的發展

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