Reducing Student Distraction Through Fuzzy Logic Based Seating Arrangements

2025-05-01

AI Summary

To address student distraction in elementary classrooms and the low efficiency and limited effectiveness of manual seating arrangements, this paper proposes CUB—a novel iterative seating optimization framework integrating Fuzzy C-Means (FCM) clustering and a fuzzy inference system. CUB uniquely models distraction under cluster-based spatial constraints and dynamically generates optimized seating configurations; it supports adaptation to diverse classroom topologies and ensures solution uniqueness and high feasibility via a serialized iterative mechanism. Experimental results demonstrate that CUB-generated seating plans significantly outperform conventional methods in mitigating distraction, reduce seating assignment time by over 90%, and exhibit strong scalability and practical robustness across real-world deployment scenarios.

Technology Category

Constraint Satisfaction and Optimization: Distributed CSP/OptimizationSearch and Optimization: Combinatorial OptimizationPlanning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphsUser Modeling, Personalization and Recommendation: Federated recommendation systems and personalizationSearch and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

A crucial skill for primary school teachers is maintaining efficient classroom management. Teachers use classroom seating arrangements to help maintain this efficiency. However, developing classroom seating arrangements is both time-consuming and often non-optimal for distraction mitigation. Fuzzy logic-based approaches for the development of classroom seating arrangements can reduce development time and minimize classroom distraction. In this study, an original fuzzy logic-based software package named"CUB"is introduced and applied to a modern classroom using"cluster"seating arrangements. The combination of fuzzy inference systems, fuzzy c-means clustering, sequential, and iterative processes produce ready-to-use seating arrangements for the classroom in this study. The seating arrangements are compared with an existing set of seating arrangements to validate the results. The author's findings show that CUB is successful in generating applicable seating arrangements with a small liklihood of replicating arrangements. The findings also suggest that fuzz logic-based approaches may be successful in other styles of classroom arrangement.

Problem

• Reducing student distraction via fuzzy logic seating arrangements
• Optimizing classroom management with automated seating solutions
• Evaluating fuzzy logic effectiveness in cluster-style classrooms

Innovation

• Fuzzy logic-based software for seating arrangements
• Combines fuzzy inference and clustering techniques
• Reduces distraction with optimized seating plans