Chancellor's Professor Carol Connor has published in Prevention Science: "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.
Connor, C. M., (September 2015). Using technology and assessment to personalize instruction: Preventing reading problems. Prevention Science, pp. 1-11. 10.1007/s11121-017-0842-9