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Computer-based instruction’s (CBI) rediscovered role in K-12: An evaluation case study of one high school’s use of CBI to improve pass rates on high-stakes tests

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Abstract

Patriot High School (PHS) adopted a remediation strategy to help its 10th-grade students at risk of failing the Math portion of MCAS, the state’s end of year competency exam. The centerpiece of that strategy was a computer-based instructional (CBI) course. PHS used a commercially available CBI product to align the course content with the competencies covered on the MCAS exam. This case study examines the overall effectiveness of the PHS strategies, and in particular, the role of CBI. Participant MCAS scores and CBI performance (measured by module-mastery data) are analyzed, and an interview with the course instructor is summarized. Finally, PHS scores were compared to the overall state MCAS scores for the same years. Overall scores of all 10th graders increased significantly compared to their 8th-grade scores, students who participated in the CBI course improved more than the students who did not. The passing rate at PHS improved from 40% in 1999 to 84% in 2001, compared to an improvement of from 47% to 75% statewide. A significant correlation was identified between the MCAS scores and the program usage data, with student CBI module mastery correlated with higher MCAS scores. Overall, the instructor was positive about the impact of the course and believed that the course gave many under-performers a chance to succeed when more traditional methods had failed. It seems likely that CBI contributed to PHS’s success. Although we report herein on just one case, we argue that CBI might play an important a role in the high stakes test environment in the USA and eleswhere.

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Notes

  1. The discrepancy between this average scale score (237) and the average score calculated in the earlier analysis (239) is that the latter does not include all students; it only includes students for whom 8th and 10th grade scores were available. Of the 146 PHS students who took the exam (and are included in Table 2), 126 students were included in the earlier analysis.

  2. Note that Table 3 includes a category for the % of student who failed. The number of students who passed is the sum of the Advanced, Proficient, and Needs Improvement categories.

References

  • Clark, R. E. (1983). Reconsidering research on learning from media. Review of Educational Research, 53(4), 445–459.

    Article  Google Scholar 

  • Clark, R. E. (1994). Media will never influence learning. Educational Technology Research and Development, 42(2), 21–29.

    Article  Google Scholar 

  • Cuban, L. (1986). Teachers and Machines: The Classroom Use of Technology Since 1920. New York: Teachers College Press.

    Google Scholar 

  • Foshay, W. R. (1998). Instructional philosophy of PLATO, Tech Paper #3. Bloomington, MN: PLATO Learning, Inc. Available at http://www.plato.com

  • Foshay, W. R. (2000). Instructional models: Four ways to integrate PLATO into the curriculum. Technical Paper #6. Bloomington, MN: PLATO Learning, Inc.

  • Hannafin, R. D. (2002). Study on the effect of PLATO-supported instruction on NC competency test results of one NC high school. Unpublished evaluation report available at http://www.plato.com

  • Hannafin, R. D. & Oppenheimer, D. (1999). Study on the effect of PLATO-supported instruction on standardized test performance and on the graduation rate of one Oregon high school. Unpublished evaluation report available at http://www.plato.com

  • Hess, F. (2000). None of the above: Promise and peril of high stakes testing. The American School Board Journal, 187(1), 26–29.

    Google Scholar 

  • Jonassen, D. (2000). Computers as mindtools for schools: Engaged critical thinking. Upper Saddle River, NJ: Prentice-Hall, Inc.

    Google Scholar 

  • Kinzie, M., Sullivan, H., & Berdel, R. (1992). Motivational and achievement effects of learner control over content review within CAI. Journal of Educational Computing Research, 8(1), 101–114.

    Article  Google Scholar 

  • Kulik, J., Kulik, C., & Bangert-Drowns, R. (1985). Effectiveness of computer-based education in elementary schools. Computers in Human Behavior, 1, 59–74.

    Article  Google Scholar 

  • Kulik, C., & Kulik, J. (1991). Effectiveness of computer-based instruction: An updated analysis. Computers in Human Behavior, 7, 75–94.

    Article  Google Scholar 

  • Kozma, R. (1994). Will media influence learning? Reframing the debate. Educational Technology Research and Development, 42(2), 6–19.

    Article  Google Scholar 

  • Means, B., & Olson, K. (1995). Technology’s role within constructivist classrooms. San Francisco, CA: Paper presented at the annual meeting of the American Educational Research Association.

    Google Scholar 

  • Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. New York: Basic Books, Inc.

    Google Scholar 

  • Seymour, S., Sullivan, H., Story, N., & Mosley, M. (1987). Microcomputers and continuing motivation. Educational Communication and Technology, 35(1), 18–23.

    Google Scholar 

  • Sivin-Kachala, J. (1997). Report on the effectiveness of technology in schools, 1990–1997. Software Publisher’s Association.

  • Swenson, R., & Anderson, C. (1982). The role of motivation in computer-assisted instruction. Creative Computing, 8(10), 134–139.

    Google Scholar 

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Correspondence to Robert D. Hannafin.

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Hannafin, R.D., Foshay, W.R. Computer-based instruction’s (CBI) rediscovered role in K-12: An evaluation case study of one high school’s use of CBI to improve pass rates on high-stakes tests. Education Tech Research Dev 56, 147–160 (2008). https://doi.org/10.1007/s11423-006-9007-4

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  • DOI: https://doi.org/10.1007/s11423-006-9007-4

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