Answers are grounded in this paper and cite their sources.
Despite its promise, adaptive learning faces significant technological, pedagogical, and infrastructural challenges that hinder its large-scale adoption. This study explores pedagogical obstacles from the perspectives of educators and instructional designers, focusing on their practices, perceptions, and specific needs. A mixed-methods approach combined a quantitative survey with qualitative data. Data were collected from 90 education professionals (teachers, instructional designers, and trainers) reached through LinkedIn and academic networks. Most participants (82.2%) identified situations requiring adaptation, yet only 55.6% had implemented adaptive measures. The qualitative analysis identified four main categories of adaptation practices. Participants expressed strong interest in AI-powered features to support instructional design tasks. The study proposes actionable recommendations to bridge the gap between technology and pedagogy, including the use of AI-assisted tools combined with human expertise, the development of adaptive interactive content and investment in professional development. This balanced approach aims to address critical barriers while maintaining educational quality and effectiveness, contributing to a better understanding of how AI can be integrated into adaptive learning systems to address current challenges.
No takes yet. Share an insight, caveat, or question.
Hilali et al. (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: