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Updated: Oct 26, 2026

Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
Published on: October 11, 2018
The Effect of Technology-Based Reading Comprehension Instruction for Students With or at Risk for Reading
Linling Shen1, Xueye Yan2, Peng Peng1
1The University of Texas at Austin, USA.
Abstract:
Effective instruction is shaped by four interrelated components: instructional Quality, Appropriate levels of instruction, Incentives to motivate students, and sufficient Time for practice and feedback (QAIT). As many schools have adopted educational technology to provide reading instruction, this review examined the extent to which instructional technologies targeting reading comprehension align with Slavin's effective instruction framework, evaluated their overall effects, and identified which components differentiate intervention effectiveness. We identified 25 articles (26 studies) published from 2000 to 2025 examining technology-based reading comprehension interventions. Only nine studies included all four QAIT components. Using a random-effects correlated and hierarchical effects model, we estimated both main and moderation effects. The overall effect of technology-based programs on reading comprehension was small-to-medium (Hedges' g = 0.13, 95% CI [0.03, 0.23]) according to contemporary perspectives on effect size magnitude in education intervention research. Meta-regression analyses revealed that interventions incorporating extrinsic incentives (e.g., points and badges) were associated with smaller effect sizes. No significant moderation effects were observed for the other QAIT components or for the presence of all four components simultaneously. Implications for educational practice and directions for future research are discussed.

