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Does it Compute? The Relationship Between Educational Technology and Student Achievement in Mathematics
By Harold Wenglinsky
Educational Testing Services (ETS)
(1998)
Summary and Review | Profile and Features | Complete Study | Related Studies
 Print Version of Review
APA Reference:
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.
Summary:
This article examines data obtained from the 1996 National Assessment of Educational Progress in an attempt to determine the relationship between computer use and 4th and 8th grade students’ mathematics achievement. The author found that higher mathematics scores were related to adequate access to computer technology (hardware, software, and overall infrastructure) in conjunction with teachers trained in technology use and the use of computers to learn new, higher-order concepts. The author also points out that it is precisely in the areas of teacher training and type of computer use that inequity across SES, race and geographic locale are most pronounced.
Major implications for educators/decision makers:
Computer use was associated with increased performance when the following conditions are met:- Students have adequate access to up-to-date computer technology (e.g., computers, peripheral equipment, Internet connectivity).
- Computers are employed to help students learn higher-order concepts (e.g., for 4th grade students, learning games; for 8th grade students, real-world computer simulations and applications).
- Teachers are adequately trained in computer technology to permit them to assist students in the use of computers to learn higher-order concepts.
Minority, poor, rural, and urban students in the study were no less likely to use computers in the classroom than were other classifications of students (e.g., white, suburban, well-to-do). However, frequency of school computer use by itself was not associated with increased academic achievement in mathematics. Minority, poor, and urban students were less likely to be taught by teachers who had received professional development on technology use, and--possibly as a result--these students were less likely to employ computers to learn higher-order concepts than were other classifications of students. It follows that: - Teachers need to be well prepared in using computers with curriculum to foster "higher-order" learning activities.
- Student access to up-to-date technology to take advantage of simulations and other multimedia software.
- Particular attention should be paid to providing adequate technology and training to teachers in minority and poor districts, both rural and urban.
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Major implications for educational researchers/evaluators:
The statistical control techniques employed in this study are well chosen, and the use of structural equation modeling to specify the relationship between computer use and mathematics academic achievement might be used to mine other large-scale data sets. Using these techniques, researchers might study cost-benefit aspects of technology integration, effectiveness of specific software programs, and impact of different state educational policies.
Major intervention(s) or variables studied:
The impact of computer use upon 4th grade and 8th grade students’ mathematics achievement.
Major questions addressed:
Sources of evidence identified:
This study is based upon data obtained from the 1996 National Assessment of Educational Progress and related questionnaires.
Replicable strategies, practices, and/or products:
The analytic techniques employed by Wenglinsky cannot be directly mapped onto other research activities, but they do serve as a general example of how to specify meaningful relationships among variables selected from large-scale databases, while controlling for covariance and confounding nuisance variables.
Strengths and limitations of the study:
The strengths of this study reside in the size and quality of the NAEP data set, the use of effective statistical controls to isolate specific relationships among variables, the inclusion of technology use as a variable of interest, and the use of appropriate control groups for comparison purposes. One limitation of this study is lack of a prior measure of mathematics achievement. (That is, it would be good to rule out the possibility that higher-scoring children might have gone into the 1996 test with higher math aptitude.) In future studies, it would be useful to take the specification of computer use and professional development even further, controlling for differences in curriculum, instruction, classroom setting, and types of training.
Suggested related studies or resources to consider:
* McCoy, L., P., (1996). Computer-based mathematics learning. Journal of Research on Computing in Education, 28(4), 438-460.
[go to CARET review]
* Parr, J. (2000). A review of the literature on computer-assisted learning, particularly integrated learning systems, and outcomes with respect to literacy and numeracy. Wellington, New Zealand: Ministry of Education. Retrieved August 19, 2002, from www.minedu.govt.nz/web/document/document_page.cfm?id=5499.
[go to CARET review]
Waxman, H., & Huang, S. (1996). Classroom instruction differences by level of technology use in middle school mathematics. Journal of Educational Computing Research, 14(2), 157-169.
* = Reviewed in CARET
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