The Computer Use of Ethnic and Linguistic Minority Students and Academic Performance

By Mido Chang, Sunha Kim and Kusum Singh.

Published by The Learner Collection

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Article: Print $US10.00
Article: Electronic $US5.00

The study examined the effects of computer use on the math and science performance of ethnic and linguistic minority students. The underachievement of ethnic minority students in math and science is well documented and is a matter of grave concern to educators, policy makers and general public. The recent massive influx of immigrant students further adds to the problem of underachievement among new minority groups. One solution offered to improve the low performance of minority students is increased computer use and skills. This study focuses on computer use in math and science classes in support of student learning. Educational researchers have noted that the advanced features of new technologies of computers can help minority students overcome learning difficulties in class. The study analyzed Early Childhood Longitudinal Survey Kindergarten Cohort (ECLS-K), a large-scale dataset, with proper weights and statistical adjustments. The statistical analyses were done on ethnic and linguistic groups of the third and fifth graders to assess the effects of computer use. The results indicated students who used computers frequently for various educational purposes showed high mathematics and science performance across all groups. The effect of the frequent computer use was positively associated with the math performance of Caucasian students, while frequency of use was negatively associated with the math and science performance of Asian immigrant students. These results contribute to a better understanding of computer use for math and science learning and provide implications for practice.

Keywords: Computer Use, Minority Students, Science Performance, Math Performance, Immigrant Students, Large Scale Data

The International Journal of Learning, Volume 15, Issue 1, pp.245-254. Article: Print (Spiral Bound). Article: Electronic (PDF File; 707.438KB).

Dr. Mido Chang

Assistant Professor, Educational Research and Evaluation, Virginia Tech, Blacksburg, VA, USA

Dr. Mido Chang is an assistant professor of Department of Educational Leadership and Policy Studies at Virginia Tech, teaching statistics courses including Quantitative Research Methods in Education, Multivariate Statistics, Multiple Regression, and Hierarchical Linear Models. Her research focuses on longitudinal growth models and multilevel models, covering multiple waves of growth trajectory; non-linear and growth curve models. She applies the statistical models to explore educational policy issues related to the academic achievement of educationally disadvantaged students. Her recent studies have dealt with the effects of social context, school programs and teachers’ class practices on the academic performance of immigrant and minority students, using nationally representative databases. She holds Ph.D. in statistics, measurement, and evaluation, and three masters’ degrees in child development, TESOL, and applied statistics, and several years of teaching elementary and high school students.

Sunha Kim

Ph.D. Candidate, Curriculum and Instruction, Virginia Tech, Blacksburg, VA, USA

Sunha Kim is a Ph.D. candidate in Instructional Design and Technology Program at Virginia Tech. Her recent research focuses on the impact of the technology on the academic achievement of students, especially linguistic and ethnic minority students.

Dr. Kusum Singh

Professor, Educational Research and Evaluation, Virginia Tech, Blacksburg, VA, USA

Dr. Kusum Singh is a professor in Educational Research and Evaluation program at Virginia Tech. Her current research interests focus on social and cognitive factors in educational achievement, school and family environments that affect math and science learning.

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