Fuzzy Logic Based Decision Support Systems for Personalized Learning Pathways

Abstract

This study introduces a novel fuzzy logic–based Decision Support System

(DSS) aimed at dynamically constructing personalized learning pathways. Grounded

in Educational Psychology and Kolb’s Experiential Learning Theory, our system mod

els learner profiles and real-time performance metrics, generating adaptive educational

recommendations. We evaluate rule-based and Sugeno-style fuzzy systems across case

studies involving university programming students. Quantitative results (MAE leq 0.12)

and qualitative feedback from 120 participants show improved engagement (+18%) and

achievement (+12%). The study contributes a hybrid pedagogically grounded fuzzy DSS

with mechanisms for evolving rules based on continual performance.

Keywords: fuzzy logic, personalized learning, decision support, educati