AI-enhanced learning and cognitive processes in digital humanities: A systematic review of executive functions

Abstract

This systematic review synthesizes empirical evidence on artificial intelligence-enhanced learning interventions targeting executive function development across diverse populations and developmental stages within digital humanities contexts. Following PRISMA guidelines, a comprehensive search of five databases (PsycINFO, ERIC, Web of Science, Scopus, PubMed) from January 2020 through December 2024 identified 14 studies encompassing 1,810 participants aged 6 to 77 years. Included studies examined adaptive intelligent tutoring systems, virtual reality platforms, computerized cognitive training programs, computational thinking interventions, and machine learning-based assessment tools applied to humanities education and research. Results demonstrated consistent positive effects on inhibitory control (effect sizes: 0.11–0.62), cognitive flexibility, working memory (effect sizes: 0.09–0.18), and planning abilities, with machine learning models achieving high diagnostic accuracy (86.8%) for executive function impairments. Effectiveness was moderated by individual baseline cognitive capacity, particularly working memory constraints. Theoretical mechanisms underlying improvements included adaptive difficulty adjustment, cognitive load optimization, personalized scaffolding through Case-Based Reasoning and reinforcement learning algorithms, and neuroplasticity-driven neural efficiency gains. Despite promising findings, limitations include intervention heterogeneity, brief intervention durations, and limited long-term follow-up. Future research should prioritize longitudinal randomized controlled trials, neuroimaging studies elucidating neural mechanisms, and implementation science investigations supporting evidence-based integration of AI technologies in digital humanities pedagogy and clinical contexts.