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Computer-based Mathematics Learning
By McCoy, Leah P.
(1996)
Summary and Review | Profile and Features | Complete Study | Related Studies
 Print Version of Review
APA Reference:
McCoy, L., P., (1996). Computer-based mathematics learning. Journal of Research on Computing in Education, 28(4), 438-460.
Summary:
McCoy reviews research in three categories of computer-based math learning: programming, computer-assisted instruction, and mathematics tools. The applications addressed are ones typically used in the early 1990’s. She conducts her analysis within the context of constructivism, asserting that “students learn mathematics by active involvement with mathematical models that allow them to internally construct their own understandings and concepts” (p. 438).
In general, McCoy suggests that the use of computer-based mathematics applications benefits students’ understanding of mathematics. Throughout the article, she also stresses the importance of having teachers involved in “guiding the discovery activities that lead to constructivist learning” (p.454).
Programming
McCoy identifies several studies showing that:
- knowledge of LOGO programming will increase elementary students’ understanding of geometry.
- knowledge of programming in LOGO and other languages (like BASIC) appears to have a positive effect on mathematical problem-solving skills of students of various ages and grades.
Computer-Assisted Instruction
The results here were inconsistent. Included in the review were “microworlds” (simulations of mathematical models), drill and practice software, and tutorials. Again, the importance of teacher involvement is noted, particularly since one article cited by McCoy found that “students would often manipulate the microworld and achieve a visual solution without conceptual understanding” (p. 446).
Mathematics Tools
Tools are defined as instruments that aid the performance of math functions. Graphing and symbolic calculators are considered tools, as are programs like Geometric Supposer and Derive. McCoy’s article analysis found that the use of tools results in “significantly higher achievement in conceptual areas and their computation and manipulations skills” (p.453-454).
Major implications for educators/decision makers:
1) Generally speaking, computer-based mathematics learning programs have been shown to be effective when implemented as part of an overall constructivist approach to education. This is true of programming learning, computer-assisted instruction, and mathematic tool applications.
2) In the case of mathematics explorations (as in the use of the Logo programming language and simulations), the teacher needs to be involved in planning and overseeing the experiences to ensure that students discover and undersand the target concepts.
3) The effectiveness of computer-assisted instruction varies with different types of students and classrooms. There is evidence that work in small groups is more effective than individual work. Advantaged, high-achieving students may learn more from CAI than do their lower-performing peers. (That is, by itself, CAI may tend to increase, rather than reduce, an achievement gap.)
4) Use of math tools such as graphing and geometry software generally contributes to a better understanding of math concepts (eight of 10 studies reviewed.) Tool software may be less helpful in promoting specific mathematical skills; three studies that distinguished between concepts and skills did not find significant differences in math skills between treatment and controls.
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Major implications for educational researchers/evaluators:
The teacher's role in guiding use of computer applications should always be considered in any study of technology effectiveness. The relation between technology and pedagogy is addressed in some more recent studies (see Suggested related studies, below).
Major intervention(s) or variables studied:
McCoy reviewed the research on three types of computer use in mathematics learning: programming, computer-assisted instruction, and mathematics tool applications.
Major questions addressed:
Sources of evidence identified:
42 studies and papers, along with related standards documents and software programs, were reviewed for this article.
Replicable strategies, practices, and/or products:
Strengths and limitations of the study:
This literature review concisely organizes and summarizes a wide range of relevant articles. Because the article was published in 1996, some of the specific software applications or versions will no longer be available. Thus this article provides general support for computer use, but not specific guidance for selection of current applications, such as web-based math explorations.
Suggested related studies or resources to consider:
* Wenglinsky, H. (1998). Does it compute? The relationship between educational technology and student achievement in mathematics. Princeton, NJ: Educational Testing Service. Retrieved March 6, 2002, from ftp://ftp.ets.org/pub/res/technolog.pdf.
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* = Reviewed in CARET
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