Effects of Data-Based Individualization for Students with Intensive Learning Needs: A Meta-Analysis

Pyung Gang Jung, Kristen L McMaster, Amy K. Kunkel, Jaehyun Shin, Pamela M. Stecker

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

We examined the mean effect of teachers’ use of data-based individualization (DBI) on the performance of students with intensive learning needs across academic areas and factors influencing the effects of DBI on student achievement. A total of 57 effect sizes from 14 studies were categorized into two comparisons: DBI Only (comparisons between DBI and a business-as-usual control) and DBI Plus (comparisons in which DBI implementers had access to additional information on student performance while they implemented DBI, compared to a control). The mean effect of DBI Only on student performance was g = 0.37; the mean effect of DBI Plus was g = 0.38. Differential effects of DBI were found depending on the nature of CBM tasks, frequency of CBM administration, and type and frequency of supports provided to teachers. Findings support the use of DBI to enhance student outcomes across academic areas.

Original languageEnglish (US)
Pages (from-to)144-155
Number of pages12
JournalLearning Disabilities Research and Practice
Volume33
Issue number3
DOIs
StatePublished - Aug 2018

Bibliographical note

Publisher Copyright:
© 2018 The Division for Learning Disabilities of the Council for Exceptional Children

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