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All Journal Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Sinkron : Jurnal dan Penelitian Teknik Informatika CogITo Smart Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Journal of Education Technology JURTEKSI Infotekmesin Journal of Information Systems and Informatics Jurnal Sistem Komputer dan Informatika (JSON) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Pendidikan dan Teknologi Indonesia Jurnal Ilmu Komputer dan Teknologi (IKOMTI) Jurnal Pengabdian Mitra Masyarakat (JPMM) Electronic Journal of Education, Social Economics and Technology Bulletin of Social Informatics Theory and Application CSRID Southeast Asia Journal on Open and Distance Learning
Rujianto Eko Saputro
Universitas Amikom Purwokerto
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Journal : Journal of Applied Data Sciences

 1 
Novel Predictive Framework for Student Learning Styles Based on Felder-Silverman and Machine Learning Model Maulana Baihaqi, Wiga; Eko Saputro, Rujianto; Setyo Utomo, Fandy; Sarmini, Sarmini
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.408

Abstract

This study analyzes data from the Open University Learning Analytics Dataset to evaluate how students' interactions with Virtual Learning Environment (VLE) materials influence their final outcomes. This research aims to formulate and build a novel predictive framework based on the Felder-Silverman and Machine Learning Model for student learning styles. Based on these objectives, this research provides novelty and contributions since it enhances student data analysis, uses a learning model using Felder-Silverman Learning Style Model (FSLSM) to give a more comprehensive understanding of students' learning styles, and improves prediction accuracy by introducing Artificial Neural Network (ANN) and feature selection using Random Forest. The data used includes 3 main files: vle.csv, which contains information about the materials and activities in the VLE; studentVle.csv, which records students' interactions with the materials; and studentInfo.csv, which provides demographic information of students and their final outcomes. The analysis process involved data merging and processing, including handling of missing values, data type conversion, as well as mapping activity types to learning style features based on the FSLSM. We use the Random Forest feature selection method, as well as data imbalance handling techniques such as oversampling, to improve model performance. The applied classification models include Logistic Regression, K-Nearest Neighbor, Random Forest, Support Vector Machine (SVM), and ANN. The analysis results showed that after tuning, the Random Forest model achieved 97% accuracy, while SVM achieved 97% accuracy as well, with better performance than previous studies. This research highlights the importance of comprehensive data integration and appropriate processing techniques in improving the accuracy of student learning style prediction. Based on the increase in accuracy results, it can be beneficial for more effective personalized learning and improve our understanding of students' learning style preferences. The research advances knowledge and provides practical applications for educators to tailor their teaching strategies.
Co-Authors Adam Prayogo Kuncoro Adiatma, Febriansyah Husni Adiya, Az Zahra Dwi Nur Anugerah Bagus Wijaya Armeyta Putri Tanzilla Arum Vika Ndari Aulia Hamdi Azhari Shouni Barkah Bagaskoro, Galih Berlilana Berlilana Cahyo, Samsul Dwi Chyntia Raras Ajeng Widiawati Dani Arifudin Deasy Komarasary Dhanar Intan Surya Saputra Dhanar Intan Surya Saputra Diah Ratna Febrianti Ely Purnawati Embong Octavianto Fandy Setyo Utomo Fatudin, Arif Faturama, Rafi Fery Afriansyah Filanzi, Shendy Giat Karyono Hanif Hidayatulloh Hasna Salsa Dhia Ikmah Ikmah Ilham, Rifqi Arifin Indriyani, Ria Inka Saputri Irwansyah Munandar Ismail, Dimas Shafa Malik Junianto, Haris Kusuma, Bagus Adhi Latif, Imam Sofarudin Maharani, Revalyna Octavia Maulana Baihaqi, Wiga Mohd. Hafiz Zakaria Nanjar, Agi Nia Millatul Izza Nurfaizi, Maulana Pandu W, Muhammad Arfianto Prasetyo, Agung Pungkas Subarkah Purwadi Purwadi Putranto, R. Vitto Mahendra Radeta Tea Makdatuang Ria Indriyani Rio Fadly Ramadhan Rizqi Aulia Widianto Rohmah, Umdah Aulia Rosana Fadila Sari safitri feriawan, Titi Safitri Maharani, Titi Salam, Sazilah Samsul Aimah Saputra , Dhanar Intan Surya Saputra, Alfin Nur Aziz Sari, Rida Purnama Sarmini Sarmini - Sarmini Sarmini Sarmini Sazilah Salam Serli, Serli Sofa, Nur Sri Hartini Suliswaningsih Syahputra, Akhmal Angga Tarwoto, T Toni Anwar Turino, Turino Wahyuni, Irmawati Tri Wenti Risma Damayanti Wiga Maulana Baihaqi Yuli Purwati Yulianto, Koko Edy