S-A I-EDU: A BIO-INSPIRED AND MODULAR SPARSE AI ARCHITECTURE FOR ADAPTIVE AND SYMBOLIC INTELLIGENT EDUCATIONAL SYSTEMS
Abstract
This paper introduces S-AI-EDU, a bio-inspired, modular, and parsimonious AI architecture designed for adaptive and symbolic intelligent educational systems. Unlike data-centric black-box models, S- AI-EDU employs hormonal modulation and symbolic agent orchestration to adaptively select pedagogical, motivational, and evaluation agents while maintaining transparency, interpretability, and cognitive economy. The architecture integrates a MetaAgent for global orchestration, specialized educational agents for targeted interventions, and Gland Agents simulating artificial educational hormones (e.g., Curiosin, Confusionin, Attentionin, Fatiguin, Dopaminin) to dynamically regulate instructional intensity. A symbolic memory module preserves learner paths, misconceptions, and engagement patterns, enabling explainable trace-based pedagogy.
Fields of Study & Subjects
Intelligent Tutoring Systems and Adaptive Learning
Social Robot Interaction and HRI
Explainable Artificial Intelligence (XAI)
Publication details
- Journal / source
- International Journal of Artificial Intelligence & Applications
- Publisher
- Academy and Industry Research Collaboration Center (AIRCC)
- Volume
- 17
- Issue
- 1
- Pages
- 21–40
- Publication date
- 28 January 2026