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2013 Conference Proceedings - University of Nevada, Las Vegas

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algebraic expression is carried out from the bottom <strong>of</strong> the tree toward the top <strong>of</strong> the tree (bottomup).In this sense, the limit computation tree has an “opposite” meaning to that <strong>of</strong> the algebraicexpression trees as the first limit property to be chosen to apply to the expression is determinedby the operation with the least precedence in that expression. That is, the computation <strong>of</strong> thelimit <strong>of</strong> an expression starts from the top <strong>of</strong> the tree and moves downwards (top-down).We believe that the students’ trouble in understanding the structure <strong>of</strong> math expressions isrelated to their reading habit. There is an obvious disparity in the reading <strong>of</strong> symbols/mathexpressions and prose. Students are accustomed to reading prose from left to right and top tobottom. Quinnell and Carter (2012, p.36) stated, “…. students must use judgment or experiencein deciding how to read a symbol. This could be why some students manage to grasp thesubtleties <strong>of</strong> decoding symbols, while others remain perplexed.”Regarding the popularity and claimed success <strong>of</strong> MML (see resources mentioned at thebeginning <strong>of</strong> the paper), we do note that in most <strong>of</strong> those cases, students’ success is defined bytheir completing a course with a grade <strong>of</strong> A, B, or C, and most <strong>of</strong> the results were reported viavenue associated with Pearson Education. Southeast Comprehensive Center (SECC) <strong>of</strong> SEDL(2011) conducted a search to collect studies related to the effectiveness <strong>of</strong> mathematics s<strong>of</strong>twareproducts; no MML research studies were located. Nevertheless, a study by Kodippili andSenaratne (2008) does indicate a strong MML-related student success rate, although the authorsadmit some methodological shortcomings.Concluding RemarksMathematics learning, especially problem solving, is not just about finding the (correct)answers. Rather, gaining a substantial understanding for relevant concepts and subsequentlyapplying this understanding logically in problem solving is more important than the answeritself. MML, as the leading computer s<strong>of</strong>tware for mathematics education on the market,unfortunately takes an unsound approach in that all it requires from the student for problemsolving is a correct answer. In order to address this issue, we have proposed two specificsolutions in this paper toward improving MML. We believe that the paper makes the followingcontributions: The “111” style for limit computation, which can be easily implemented on MML,rectifies MML’s “answers only” problem.<strong>Proceedings</strong> <strong>of</strong> the 40 th Annual Meeting <strong>of</strong> the Research Council on Mathematics Learning <strong>2013</strong> 142

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