The Impact of Adaptive Learning Systems on Academic Performance and Outcomes of K-12 Students with Executive Function Disorders: A Meta-Analytic Study

Students with executive function disorders (EFDs), including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASD), and learning disabilities, face significant challenges in K-12 educational settings, particularly in self-regulation, working memory, and task completion. Despite growing implementation of adaptive learning systems, empirical evidence regarding their effectiveness for students with EFDs remains fragmented and inconclusive. The purpose of this meta-analytic study was to systematically synthesize research on the impact of adaptive learning systems on academic performance and executive function outcomes among K-12 students with EFDs. A comprehensive meta-analysis was conducted using random-effects models to analyze data from 12 experimental and quasi-experimental studies encompassing 2,216 students with ADHD, ASD, and learning disabilities. The analysis examined two primary categories of adaptive learning systems: AI-based tutoring systems and personalized learning platforms. Moderator analyses explored differential effects by EFD type, subject area, and intervention characteristics. Results revealed a significant overall pooled effect size of d = 0.755 (95% CI [0.612, 0.898]), indicating that students using adaptive learning systems improved from the 50th to the 77th percentile compared to traditional instruction. Moderator analyses demonstrated the largest effects for students with ADHD (d = 0.842), with substantial benefits observed in mathematics (d = 0.801) and reading (d = 0.734). Executive function outcomes showed moderate-to-large improvements (d ≈ 0.65), and findings remained robust to publication bias sensitivity analyses. These findings extend cognitive load theory and self-regulated learning frameworks by demonstrating how adaptive systems can scaffold learning for students with EFDs. Practical implications suggest that schools should prioritize implementation of adaptive learning technologies for students with EFDs, particularly in core academic subjects. Policy recommendations include increased funding for adaptive learning infrastructure and professional development to support effective implementation. Keywords: adaptive learning systems, executive function disorders, ADHD, autism spectrum disorders, learning disabilities, meta-analysis, K-12 education, AI tutoring

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-05
DOI
https://doi.org/10.5281/zenodo.17832399
Primary Topic
Attention Deficit Hyperactivity Disorder
Type
article
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article

The Impact of Adaptive Learning Systems on Academic Performance and Outcomes of K-12 Students with Executive Function Disorders: A Meta-Analytic Study

Zenodo (CERN European Organization for Nuclear Research)
Attention Deficit Hyperactivity Disorder
article

The Impact of Adaptive Learning Systems on Academic Performance and Outcomes of K-12 Students with Executive Function Disorders: A Meta-Analytic Study

article en

Abstract

Students with executive function disorders (EFDs), including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASD), and learning disabilities, face significant challenges in K-12 educational settings, particularly in self-regulation, working memory, and task completion. Despite growing implementation of adaptive learning systems, empirical evidence regarding their effectiveness for students with EFDs remains fragmented and inconclusive. The purpose of this meta-analytic study was to systematically synthesize research on the impact of adaptive learning systems on academic performance and executive function outcomes among K-12 students with EFDs. A comprehensive meta-analysis was conducted using random-effects models to analyze data from 12 experimental and quasi-experimental studies encompassing 2,216 students with ADHD, ASD, and learning disabilities. The analysis examined two primary categories of adaptive learning systems: AI-based tutoring systems and personalized learning platforms. Moderator analyses explored differential effects by EFD type, subject area, and intervention characteristics. Results revealed a significant overall pooled effect size of d = 0.755 (95% CI [0.612, 0.898]), indicating that students using adaptive learning systems improved from the 50th to the 77th percentile compared to traditional instruction. Moderator analyses demonstrated the largest effects for students with ADHD (d = 0.842), with substantial benefits observed in mathematics (d = 0.801) and reading (d = 0.734). Executive function outcomes showed moderate-to-large improvements (d ≈ 0.65), and findings remained robust to publication bias sensitivity analyses. These findings extend cognitive load theory and self-regulated learning frameworks by demonstrating how adaptive systems can scaffold learning for students with EFDs. Practical implications suggest that schools should prioritize implementation of adaptive learning technologies for students with EFDs, particularly in core academic subjects. Policy recommendations include increased funding for adaptive learning infrastructure and professional development to support effective implementation. Keywords: adaptive learning systems, executive function disorders, ADHD, autism spectrum disorders, learning disabilities, meta-analysis, K-12 education, AI tutoring

Zenodo (CERN European Organization for Nuclear Research)
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Attention Deficit Hyperactivity Disorder
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