FST Graduate Research Topic

Research Topic: AGI Research and Development: Adaptive Learning Platform in Personalized Education
Suggested By: Harris Wang
Last Update: September 28th, 2025

AGI Research and Development: Adaptive Learning Platform in Personalized Education  Constrained Object Hierarchies (COH) provide a neuroscience-inspired theoretical framework for modeling Artificial General Intelligence (AGI). As a flexible and robust foundation, COH supports the representation of general intelligent systems across diverse domains. Formally, a COH is defined as a 9-tuple: O = (C, A, M, N, E, I, T, G, D) Where: C: Components – sub-objects organized hierarchically A: Attributes – state variables describing object properties M: Methods – executable actions associated with components N: Neural Components – adaptive models for learning and inference E: Embedding Neural Component – semantic representation of the COH I: Identity Constraints – rules ensuring object integrity T: Trigger Constraints – event-condition-action rules for dynamic behavior G: Goal Constraints – optimization objectives guiding intelligent behavior D: Constraint Daemons – real-time monitors enforcing system constraints Based on the COH framework, the modelling process and result of Adaptive Learning Platform in Personalized Education are as follows: System Description and Significance: This system personalizes educational content and pacing based on individual student characteristics and learning progress. Its significance lies in addressing diverse learning needs within educational settings, potentially improving outcomes through tailored instruction while accommodating different learning styles and paces. Analysis and Design: The system must model student knowledge states, learning content characteristics, and pedagogical strategies. Identity constraints encode fundamental educational principles (like the zone of proximal development), while neural components adapt to individual learning patterns. The hierarchical structure separates student modeling from content management and instructional strategy. Modelling Solution: C: {StudentModel, KnowledgeGraph, ContentBank, TutorAgent} A: student_knowledge_state, learning_objective, content_difficulty, engagement_level M: recommend_content(), adjust_difficulty(), generate_quiz() N: KnowledgeTracingModel, ContentEffectivenessPredictor E: Embedding of student's cognitive and emotional state relative to learning objective I: Next content must be within Zone of Proximal Development T: IF quiz_performance < threshold THEN recommend_remedial_content G: Maximize_long_term_knowledge_retention AND Maintain_student_engagement D: FrustrationDaemon monitoring time-on-task and error rates The COH framework captures the essence of educational intelligence: adapting to individual differences while maintaining pedagogical integrity through carefully designed constraints. You may choose this topic and pursue one of the following routes: 📝 Essay Survey existing methodologies for modeling, designing, and implementing similar intelligent systems. Include: Literature synthesis COH framework analysis Critical evaluation of competing approaches 🛠️ Project Design and implement the system using the COH model. Include: System architecture and design Development and testing Demonstration of core functionality 🎓 Thesis Explore COH’s theoretical foundations in depth. Include: Proposed enhancements or extensions Implementation and evaluation Development of an advanced intelligent system grounded in COH principles