Using Technology and Assessment to Personalize Instruction: Preventing Reading Problems
Children who fail to learn to read proficiently are at serious risk of referral to special education, grade retention, dropping out of high school, and entering the juvenile justice system. Accumulating research suggests that instruction regimes that rely on assessment to inform instruction are effective in improving the implementation of personalized instruction and, in turn, student learning. However, teachers find it difficult to interpret assessment results in a way that optimizes learning opportunities for all of the students in their classrooms. This article focuses on the use of language, decoding, and comprehension assessments to develop personalized plans of literacy instruction for students from kindergarten through third grade, and A2i technology designed to support teachers’ use of assessment to guide instruction. Results of seven randomized controlled trials demonstrate that personalized literacy instruction is more effective than traditional instruction, and that sustained implementation of personalized literacy instruction first through third grade may prevent the development of serious reading problems. We found effect sizes from .2 to .4 per school year, which translates into about a 2-month advantage. These effects accumulated from first through third grade with a large effect size (d = .7) equivalent to a full grade-equivalent advantage on standardize tests of literacy. These results demonstrate the efficacy of technology-supported personalized data-driven literacy instruction to prevent serious reading difficulties. Implications for translational prevention research in education and healthcare are discussed.
KeywordsReading Writing Literacy Academic Intervention Instruction Precision intervention Individualized instruction
These studies were funded by grants R01HD48539 and R21HD062834, and in part P50 HD052120, from the Eunice Kennedy Shriver National Institute of Child Health and Human Development; and by grants R305H04013, R305B070074, R305A130517/R305A160404, R305A170163 and R305F100027 from the U.S. Department of Education, Institute of Education Sciences. The opinions expressed are ours and do not represent views of the funding agencies.
Compliance with Ethical Standards
Conflicts of Interest
Dr. Connor has an equity interest in Learning Ovations., a company that may potentially benefit from the research results. The terms of this arrangement have been reviewed and approved by the University of California, Irvine in accordance with its conflict of interest policies.
All studies reported were approved by the Institutional Review Boards of the university at which the studies were conducted. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- Al Otaiba, S., Connor, C. M., Folsom, J. S., Greulich, L., Meadows, J., & Li, Z. (2011). Assessment data-informed guidance to individualize kindergarten reading instruction: Findings from a cluster-randomized control field trial. Elementary School Journal, 111, 535–560. https://doi.org/10.1086/659031.CrossRefPubMedPubMedCentralGoogle Scholar
- Allen, T. (1986). Patterns of academic achievement among hearing impaired students: 1974 And 1983. In A. Schildroth & M. Karchmer (Eds.), Deaf children in American (pp. 161–206). San Diego: College-Hill Press.Google Scholar
- Bronfenbrenner, U., & Morris, P. A. (2006). The bioecological model of human development. In R. M. Lerner & W. Damon (Eds.), Handbook of child psychology: Theoretical models of human development (Vol. 1, 6th ed., pp. 793–828). Hoboken: Wiley.Google Scholar
- Catts, H., & Kamhi, A. G. (Eds.). (2004). Language basis of reading disabilities (2nd ed.). Needham Heights: Allyn & Bacon.Google Scholar
- Compton, D. L., Fuchs, D., Fuchs, L. S., Elleman, A. M., & Gilbert, J. K. (2008). Tracking children who fly below the radar: Latent transition modeling of students with late-emerging reading disability. Learning and Individual Differences, 18, 329–337. https://doi.org/10.1016/j.lindif.2008.04.003.CrossRefGoogle Scholar
- Connor, C. M. (Ed.). (2016). The cognitive development of reading and reading comprehension. London: Routledge.Google Scholar
- Connor, C. M., Piasta, S. B., Fishman, B., Glasney, S., Schatschneider, C., Crowe, E., et al. (2009). Individualizing student instruction precisely: Effects of child× instruction interactions on first graders’ literacy development. Child Development, 80, 77–100. https://doi.org/10.1111/j.1467-8624.2008.01247.x.CrossRefPubMedPubMedCentralGoogle Scholar
- Connor, C. M., Morrison, F. J., Schatschneider, C., Toste, J., Lundblom, E. G., Crowe, E., & Fishman, B. (2011a). Effective classroom instruction: Implications of child characteristic by instruction interactions on first graders' word reading achievement. Journal of Research on Educational Effectiveness, 4, 173–207. https://doi.org/10.1080/19345747.2010.510179.CrossRefPubMedPubMedCentralGoogle Scholar
- Connor, C. M., Morrison, F. J., Fishman, B., Giuliani, S., Luck, M., Underwood, P. S., et al. (2011b). Testing the impact of child characteristics × instruction interactions on third graders' reading comprehension by differentiating literacy instruction. Reading Research Quarterly, 46, 189–221. https://doi.org/10.1598/RRQ.46.3.1/epdf.PubMedPubMedCentralGoogle Scholar
- Connor, C. M., Fishman, B. J., Crowe, E., Underwood, P., Schatschneider, C., & Morrison, F. J. (2013a). Third grade teachers' use of assessment to instruction (A2i) software and students' reading comprehension gains. In O. Korat & A. Shamir (Eds.), In press, technology for literacy achievements for children at risk. New York: Springer.Google Scholar
- Connor, C. M., Morrison, F. J., Fishman, B. J., Crowe, E. C., Al Otaiba, S., & Schatschneider, C. (2013b). A longitudinal cluster-randomized controlled study on the accumulating effects of individualized literacy instruction on students' reading from first through third grade. Psychological Science, 24, 1408–1419. https://doi.org/10.1177/0956797612472204.CrossRefPubMedPubMedCentralGoogle Scholar
- Connor, C. M., Sparapani, N., Ingebrand, S., Wood, T., & Crowe, E. C. (2015). A guide to individualizing student instruction in the classroom. Paradise Valley: Learning Ovations.Google Scholar
- Connor, C. M., Dombek, J., Crowe, E. C., Spencer, M., Tighe, E. L., Coffinger, S., et al. (2016). Acquiring science and social studies knowledge in kindergarten through fourth grade: Conceptualization, design, implementation, and efficacy testing of content-area literacy instruction (CALI). Journal of Educational Psychology, No Pagination Specified. https://doi.org/10.1037/edu0000128.
- Connor, C., Day, S., & Zargar, E. (2017a) The word knowledge e-book: Building comprehension monitoring and word learning skills. Washington, DC: Presented at the annual conference of the American Psychological Association (APA).Google Scholar
- Connor, C. M., Mazzocco, M. M. M., Kurz, T., Crowe, E. C., Tighe, E. L., Wood, T. S., & Morrison, F. J. (2017b). Using Assessment to Individualize Early Mathematics Instruction. Journal of School Psychology. https://doi.org/10.1016/j.jsp.2017.04.005
- Connor, C., Taylor, K., Wood, T., & Siegal, S. (2017c) Using fidelity data to elucidate the results of a design study on Assessment-2-Instruction technology. Washington, DC: Presented at the annual conference of the Society for Research in Educational Effectiveness (SREE).Google Scholar
- Daniels, P. T., & Bright, W. (Eds.). (1996). The world's writing systems. Oxford: Oxford University Press.Google Scholar
- Deno, S. L., Espin, C. A., Fuchs, L. S., Shinn, M. R., Walker, H. M., & Stoner, G. (2002). Evaluation strategies for preventing and remediating basic skill deficits. In Anonymous (Ed.), Interventions for academic and behavior problems II: Preventive and remedial approaches (pp. 213–241). Washington, DC: National Association of School Psychologists.Google Scholar
- Duncan, A. (2009). Teacher's College. Columbia University policy address on teacher preparation Retrieved from http://www.tc.edu/news/article.htm?id=7195.
- Duncan, G. J., & Murnane, R. J. (Eds.). (2011). Whither opportunity? Rising inequality, schools, and children's life changes. New York: Russel Sage.Google Scholar
- Fishman, B. J., Penuel, W. R., Allen, A.-R., Cheng, B. H., & Sabelli, N. (2013). Design-based implementation research: An emerging model for transforming the relationship of research and practice. Yearbook of the National Society for the Study of Education, 112, 136–156.Google Scholar
- Gersten, R. (2007). Impact of teacher study groups on observed teaching practice and student vocabulary and comprehension for first grade teachers: Results of a large scale randomized controlled trial. Paper presented at the SSSR Conference, Prague.Google Scholar
- Lederberg, A. R., Miller, E. M., Easterbrooks, S. R., & Connor, C. M. (2014). Foundations for literacy: An early literacy intervention for deaf and hard-of-hearing children. Journal of Deaf Studies and Deaf Education, 19, 438–455. https://doi.org/10.1093/deafed/enu022.CrossRefPubMedPubMedCentralGoogle Scholar
- National Early Literacy Panel. (2008). Developing early literacy: Report of the National Early Literacy Panel. Washington DC: National Institute for Literacy and the National Center for Family Literacy.Google Scholar
- NICHD National Reading Panel. (2000). Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction. Washington DC: U.S. DHHS, PHS, NICHD.Google Scholar
- Shavelson, R. J., & Towne, L. (Eds.). (2002). Scientific research in education. Washington DC: National Academy Press.Google Scholar
- Simos, P. G., Fletcher, J. M., Sarkari, S., Billingsley, R. L., Denton, C., & Papanicolaou, A. C. (2007). Altering the brain circuits for reading through intervention: A magnetic source imaging study. Neuropsychology, 21, 485–496. https://doi.org/10.1037/0894-422.214.171.1245.CrossRefPubMedGoogle Scholar