oai:eurokd.com:article/2078 2026-04-23

Toward Cognitively Grounded AI: Can a Working Memory Interface Bridge Individual Differences and System Design? Volume 3 Hassan Mohebbi Richard L. Sparks Zhisheng (Edward) Wen Working Memory Cognitive Load Theory Individual Differences Language Aptitude Artificial Intelligence in Education Instructional Design Ethics of Educational Technology Human–Computer Interaction <p style="text-align: justify;">The rapid integration of generative AI into language education has exposed a dual challenge: a &ldquo;grounding gap&rdquo; in its cognitive shallowness, and a profound ethical peril that such technology may accommodate rather than empower learners. This editorial interrogates whether a bridge is possible. We argue that working memory (WM)&mdash;empirically central to language aptitude and learning&mdash;offers the most viable, if fraught, interface for such a bridge. We introduce the Cognitive Load&ndash;WM Interaction (CLWM) Matrix not as a solution, but as a critical heuristic and necessary safeguard. It is designed to enforce a key distinction: between AI that grounds learning by managing cognitive load and AI that bypasses cognitive effort. From this, we derive a dual-path risk-aware research agenda, focused on developing WM-aware pedagogical specifications and probing hybrid AI architectures. The conclusion is not a blueprint, but a condition: progress in AI must be subordinated to progress in understanding and protecting the human cognitive processes it seeks to engage.</p> Individual Differences in Language Education: An International Journal 2026-04-23 Text https://api.eurokd.com/Uploads/Article/2078/idle.2025.03.01.pdf https://doi.org/10.32038/idle.2025.03.01 en Pages 1–13