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Implementation Drivers of Data-Based Instruction for Students With Intensive Learning Needs: A Systematic Review.

Seohyeon ChoiEmma ShanahanBess Casey-WilkeJechun AnLeAnne D Johnson
Published in: Journal of learning disabilities (2023)
Despite decades of research efforts, data-based instruction (DBI) for students with intensive intervention needs are not being widely used in practice as anticipated, and many educators have difficulties in implementing it. This systematic review aimed to examine what kinds of implementation drivers and strategies have been used to support educators implementing DBI and what kinds of implementation outcomes researchers have measured. Eighteen studies were synthesized using the Implementation Drivers framework and Implementation Outcomes taxonomy and were quality appraised. We found that the majority of studies primarily used competency drivers to increase teachers' DBI expertise, while a limited number of studies focused on organizational and leadership drivers. Acceptability and fidelity were frequently assessed as implementation outcomes. We discussed the implications of the findings, including the need for researchers to incorporate implementation drivers and outcomes at diverse levels to best support educators' implementation of DBI, as well as the limitations of this review, such as the limited generalizability of the findings.
Keyphrases
  • quality improvement
  • primary care
  • healthcare
  • systematic review
  • randomized controlled trial
  • type diabetes
  • electronic health record
  • big data
  • machine learning
  • meta analyses