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Access to Algebra I: The Effects of Online Mathematics for Grade 8 Students. NCEE 2012-4021
REPORT

## Jessica B. Heppen, Kirk Walters, Margaret Clements, Ann-Marie Faria, Cheryl Tobey, Nicholas Sorensen, Katherine Culp

## Abstract

This report presents findings from a randomized control trial designed to inform the decisions of policymakers who are considering using online courses to provide access to Algebra I in grade 8. It focuses on students judged by their schools to be ready to take Algebra I in grade 8 but who attend schools that do not offer the course. The study tested the impact of offering an online Algebra I course on students' algebra achievement at the end of grade 8 and their subsequent likelihood of participating in an advanced mathematics course sequence in high school. The study was designed to respond to both broad public interest in the deployment of online courses for K-12 students and to calls from policymakers to provide students with adequate pathways to advanced coursetaking sequences in mathematics (National Mathematics Advisory Panel 2008). This study is the first of its kind to rigorously evaluate the impact of offering an online version of Algebra I in schools that otherwise do not typically offer the course, even though they have students who are ready to take it. For educators and students facing similar challenges, the results of this study may be particularly informative and promising. Results showed that offering an online course to AR students is an effective way to broaden access to Algebra I in grade 8 and later, to more challenging mathematics course opportunities. The study demonstrates that an online course as implemented is more effective in promoting students' success in mathematics than existing practices in these schools. Appended are: (1) Study Design, Study Samples, and Statistical Precision; (2) Measures; (3) Intervention Features; (4) Estimation Methods and Hypothesis Testing; (5) Sensitivity Analyses; and (6) Missing Data and Multiple Imputation. (Contains 77 tables, 12 figures and 61 footnotes.)

## Citation

Heppen, J.B., Walters, K., Clements, M., Faria, A.M., Tobey, C., Sorensen, N. & Culp, K. Access to Algebra I: The Effects of Online Mathematics for Grade 8 Students. NCEE 2012-4021. Retrieved July 23, 2021 from https://www.learntechlib.org/p/50984/.

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## References

View References & Citations Map- Adelman, C. (1999). Answers in the toolbox: Academic intensity, attendance patterns, and bachelor’s degree attainment. Washington, DC: U.S. Department of Education.
- Adelman, C. (2006). The toolbox revisited: Paths to degree completion from high school through college. Washington, DC: U.S. Department of Education.
- Allensworth, E., Nomi, T., Montgomery, N., & Lee, V.E. (2009). College preparatory curriculum for all: Academic consequences of requiring algebra and English I for ninth graders in Chicago. Educational Evaluation and Policy Analysis, 31, 367–391.
- Allison, P.D. (2009). Missing data. In R.E. Millsap & A. Maydeu-Oliveras (Eds.), The SAGE handbook of quantitative methods in psychology (pp. 72–89). Thousand Oaks, CA: Sage.
- Atanda, R. (1999). Do gatekeeper courses expand education options? (NCES 1999-303). Washington, DC: U.S. Department of Education, National Center for Education Statistics.
- Berry, A.M., & Wintle, S.E. (2009). Using laptops to facilitate middle school science learning: The results of hard fun. Gorham: University of Southern Maine, Maine Education Policy Research Institute.
- Bloom, H.S., Hill, C., Black, A., & Lipsey, M.W. (2008). Performance trajectories and performance gaps as achievement effect-size benchmarks for educational interventions. New York: MDRC.
- Bloom, H.S. (2005). Using covariates to improve precision: Empirical guidance for studies that randomize schools to measure the impacts of educational interventions. New York: MDRC.
- Burris, C., Heubert, J., & Levin, H. (2006). Accelerating mathematics achievement using heterogeneous grouping. American Educational Research Journal, 43, 105–136.
- Common Core State Standards Initiative. (2010). Common core state standards for mathematics. Retrieved September 15, 2010, from http://www.corestandards.org/assets/CCSSI_Math%20Standards.pdf.
- EdSource. (2009). Algebra policy in California: Great expectations and serious challenges. Mountain View, CA: Author.
- Gamoran, A., & Hannigan, E.C. (2000). Algebra for everyone? Benefits of college-preparatory mathematics for students with diverse abilities in early secondary school. Educational Evaluation and Policy Analysis, 22, 241–254.
- Graham, J.W. (2009). Missing data analysis: Making it work in the real world. Annual Review of Psychology, 60, 549–576.
- Hammer, P.C., Hughes, G., McClure, C., Reeves, C., & Salgado, D. (2005). Rural teacher recruitment and retention practices: A review of the research literature, national survey of rural superintendents, and case studies of programs in Virginia. Charleston, WV: Edvantia.
- Hanum, W.H., Irvin, M.J., Banks, J.B., & Farmer, T.W. (2009). Distance education use in rural schools. Journal of Research in Rural Education, 24(3). Retrieved July 9, 2009, from http://jrre.psu.edu/articles/24-3.pdf
- Hedges, L.V. (1981). Distribution theory for Glass’s estimator of effect size and related estimators. Journal of Educational Statistics, 6, 107-128.
- Hedges, L.V., & Hedberg, E.C. (2007). Intraclass correlation values for planning group randomized trials in education. Educational Evaluation and Policy Analysis, 29, 60–87.
- Holliday, B., Cuevas, G., Moore-Harris, B., & Carter, J.A. (2005). Glencoe Algebra 1. New York: Glencoe McGraw-Hill.
- Horn, L., & Nuñez, A.M. (2000). Mapping the road to college: First generation students’ math track, planning strategies and context of support (NCES 2000-153). Washington, DC: U.S. Department of Education, National Center for Education Statistics.
- Hupp, D. (2009, April). Mathematics grades 6–8: Including a brief introduction and overview of the (now) 4-state assessment collaborative. Presentation to the Maine Department of Education, Augusta, ME.
- Internet Testing Systems& SEG Assessment. (2009). Promise Assessment.
- Jabon, D., Narasimhan, L., Boller, J., Sally, P., Baldwin, J., & Slaughter, R. (2010). The Chicago Algebra Initiative. Notices of the American Mathematical Society, 57, 865–867.
- Jimerson, L. (2006). Breaking the fall: Cushioning the impact of rural declining enrollment. Washington, DC: The Rural School and Community Trust.
- Johnson, J., & Strange, M. (2007). Why rural matters 2007: The realities of rural education growth. Arlington, VA: The Rural School and Community Trust. Retrieved October 25, 2011, from http://www.eric.ed.gov/PDFS/ED498859.pdf
- Lacampagne, C.B., Blair, W.D., & Kaput, J.J. (Eds) (1995). The Algebra Initiative Colloquium papers. Paper presented at a conference on reform in algebra. Washington, DC: U.S. Department of Education, Office of Educational Research and Improvement, National Institute on Student Achievement, Curriculum, and Assessment.
- Linacre, J.M. (2006). Winsteps Rasch measurement [computer software]. Chicago: Winsteps.com.
- Little, R.J.A., & Raghunathan, T. (2004, May). Statistical analysis with missing data. Course materials presentation, Arlington, VA.
- Little, R.J.A., & Rubin, D.B. (2002). Statistical analysis with missing data (2nd ed.). Hoboken, NJ: Wiley.
- Loveless, T. (2008). The misplaced math student: Lost in eighth-grade algebra. Washington, DC: The Brookings Institute.
- Ma, X. (2003). A longitudinal assessment of early acceleration of students in mathematics on growth in mathematics achievement. Developmental Review, 25, 104–132.
- May, H., Perez-Johnson, I., Haimson, J., Sattar, S., & Gleason, P. (2009). Using state tests in education experiments: A discussion of the issues (NCEE 2009-013). Washington, DC: U.S.
- McCullagh, P., & Nelder, J.A. (1989). Generalized linear models. London: Chapman and Hall.
- National Mathematics Advisory Panel. (2008). Foundations for success: The final report of the National Mathematics Advisory Panel. Washington, DC: U.S. Department of Education.
- National Council of Teachers of Mathematics (2000). Principles and standards for school mathematics. Reston, VA: Author.
- National Council of Teachers of Mathematics (2006). Curriculum focal points for prekindergarten through grade 8 mathematics: A quest for coherence. Reston, VA: Author.
- National Education Association (2006). Guide to teaching online courses. Washington, DC: Author. Retrieved October 25, 2011 from http://www.nea.org/assets/docs/onlineteachguide.pdf
- Nord, C., Roey, S., Perkins, R., Lyons, M., Lemanski, N., Brown, J., & Schuknecht, J. (2011). The nation’s report card: America’s high school graduates (NCES 2011-462).
- Optimal Performance (2006). Florida virtual schools executive summary: 2005–2006 stakeholder survey. Tallahassee, FL: Author. Retrieved October 25, 2011, from http://www.flvs.net/areas/aboutus/pages/annualevaluations.aspx
- Picciano, A.G., & Seaman, J. (2007). K–12 online learning: A survey of U.S. School district administrators. Boston: The Sloan Consortium. Retrieved October 25, 2011 from http://www.sloanconsortium.org/publications/survey/K-12_06.asp
- Picciano, A., & Seaman, J. (2009). K–12 online learning: A 2008 follow-up survey of the U.S. School district administrators. Needham, MA: The Sloan Consortium. Retrieved October 25, 2011, from http://www.sloanconsortium.org/publications/survey/pdf/k12_online_learning_2008.pdf
- Puma, M.J., Olsen, R.B., Bell, S.H., & Price, C. (2009). What to do when data are missing in group randomized controlled trials (NCEE 2009-0049). Washington, DC: U.S. Department of
- Rose, H., & Betts, J. (2001). Math matters: The links between high school curriculum, college graduation, and earnings. San Francisco: Public Policy Institute of California.
- Rubin, D.B. (1976). Inference and missing data. Biometrika, 63, 581–592.
- Rubin, D.B. (1987). Multiple imputation for nonresponse in surveys. New York: Wiley.
- Schafer, J.L., & Graham, J.W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7(2), 147–177.
- Schneider, B., Swanson, C.B., & Riegle-Crumb, C. (1998). Opportunities for learning: Course sequences and positional advantages. Social Psychology of Education, 2, 25–53.
- Schochet, P.Z. (2008). The late pretest problem in randomized control trials of education interventions (NCEE 2009-4033). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance.
- Schwartzbeck, T., Prince, C., Redfield, D., Morris, H., & Hammer, P.C. (2003). How are rural school districts meeting the teacher quality requirements of No Child Left Behind? Charleston, WV: Appalachia Education Laboratory. Retrieved October 25, 2011, from http://www.edvantia.org/publications/index.cfm? & T=products & C=products & Id=480
- Seltzer, M. (2004). The use of hierarchical models in analyzing data from experiments and quasiexperiments conducted in field settings. In D. Kaplan (Ed.), Handbook of quantitative methodology for the social sciences (pp. 259–280). Thousand Oaks, CA: Sage.
- Silvernail, D.L., & Gritter, A.K. (2007). Maine’s middle school laptop program: Creating better writers. University of Southern Maine. Gorham: University of Southern Maine, Maine Education Policy Research Institute.
- Smith, J.B. (1996). Does an extra year make any difference? The impact of early algebra on longterm gains in mathematical attainment. Educational Evaluation and Policy Analysis, 18, 141– 153.
- Snijders, T., & Bosker, R.J. (1999). Multilevel analysis: An introduction to basic and advanced multilevel modeling. London: Sage.
- Spielhagen, F.R. (2006). Closing the achievement gap in math: The long-term effects of eighthgrade algebra. Journal of Advanced Academics, 18, 34–59.
- Stevenson, D.L., Schiller, K.S., & Schneider, B. (1994). Sequences of opportunities for learning. Sociology of Education, 67, 184–198.
- Stuart, E.A., Azur, M., Frangakis, C., & Leaf, P. (2009). Multiple imputation with large datasets: A case study of the children’s mental health initiative. American Journal of Epidemiology, 169(9), 1133–1139.
- Thomas, W.R. (1999). Essential elements for web-based courses for high school students. Atlanta, GA: Southern Regional Education Board. Retrieved October 25, 2011, from http://info.sreb.org/programs/EdTech/pubs/EssentialElements/EssentialElements.pdf
- Tucker, B. (2007). Laboratories of reform: Virtual high schools and innovation in public education. Washington, DC: Education Sector.
- U.S. Department of Education, National Center for Education Statistics. (1996). Pursuing excellence: A study of U.S. Eighth-grade mathematics and science teaching, learning, curriculum, and achievement in international context. Washington, DC: U.S. Department of Education, Institute for Education Sciences. National Center for Education Statistics.
- U.S. Department of Education. (1997, October). Mathematics equals opportunity (White paper prepared for U.S. Secretary of Education Richard W. Riley). Retrieved September 15, 2005, from http://www.ed.gov/pubs/math/index.html
- Viadero, D. (2010, February). “Algebra-for-all” push found to yield poor results. Education Week. Retrieved February 10, 2010, from http://www.edweek.org/ew/articles/2010/02/10/21algebra_ep.h29.html
- Walston, J., & Carlivati McCarroll, J. (2010). Eighth-grade algebra: Findings from the eighth-grade round of the early childhood longitudinal study, kindergarten class of 1998–99 (ECLS-K) (NCES 2010-016). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics. Retrieved November 10, 2010, from http://nces.ed.gov/pubs2010/2010016.pdf
- What Works Clearinghouse. (2007). Technical details of WWC-conducted computations. Washington, DC: U.S. Department of Education.
- Zandberg, I., & Lewis, L. (2008). Technology-based distance education courses for public elementary and secondary school students: 2002–03 and 2004–05 (NCES 2008-08).

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