Reflectai: Otomatisasi Perangkat Pembelajaran Mendalam Menggunakan Machine Learning dan Student Behavior Analysis Melalui LMS

Ahmad Yuan Arby

doi:10.61132/prosemnasproit.v2i2.203

Authors

Ahmad Yuan Arby Universitas Pembangunan Nasional “Veteran Jawa Timur”

DOI:

https://doi.org/10.61132/prosemnasproit.v2i2.203

Keywords:

Learning Style, Machine Learning, LMS, Generative AI, Adaptive Learning

Abstract

This study presents ReflectAI, a web-based system designed to automate the creation of teaching materials tailored to students' learning styles using behavior data from a Learning Management System (LMS). Student digital activity data—such as logins, material access, forum participation, assignment submission, and quiz results—are extracted and processed using a Hierarchical Clustering algorithm to categorize students into three learning styles: visual, auditory, and kinesthetic. Based on the clustering results, the system automatically generates personalized learning modules using generative AI (ChatGPT API), aligned with each student's learning preferences. Employing a data-driven system development approach, the system was tested with data from 230 students in a mathematics course. The results show diverse learning style distributions and relevant, tailored content generation. ReflectAI is designed to reduce teachers’ administrative workload and enhance personalized and adaptive learning. This system contributes to educational transformation through deep, data-driven technology integration.

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