Bringing Data-Based Individualization to Scale: A Call for the Next-Generation Technology of Teacher Supports. (September 2021)

• Record Type: Journal Article
• Authors: Fuchs, Lynn S.; Fuchs, Douglas; Hamlett, Carol L.; Stecker, Pamela M.
• Other Names: Espin Christine A. guest-editor.; Förster Natalie guest-editor.; Mol Suzanne E. guest-editor.
• Is Part Of: Journal of learning disabilities. Volume 54:Number 5(2021)
• Page Start: 319
• Page End: 333
• Publication Date: 2021-09
• Subjects: curriculum-based measurement -- data-based individualization -- intensive intervention; Learning disabilities -- Periodicals; 371.905
• DOI: 10.1177/0022219420950654
• Languages: English
• ISSNs: 0022-2194

Abstract

The purpose of this narrative synthesis of the curriculum-based measure (CBM) instructional utility literature is to deepen insight into the supports required to enrich teachers' instructional decision-making within curriculum-based measure – data-based individualization (CBM-DBI) in ways that enhance the learning outcomes of students with intensive intervention needs, including students with learning disabilities. We begin by summarizing a recent meta-analysis of CBM-DBI studies focused on academic outcomes. We then reconsider studies from that meta-analysis to further explore the supports required to enrich teachers' instructional decision-making within CBM-DBI and improve student learning. We next draw conclusions and propose a renewed program of instructional utility CBM-DBI research for capitalizing on technology's potential to enhance productive instructional decision-making for students who require intensive intervention, fulfill DBI's potential, and bring CBM-DBI to scale.