Authors:
Meina Legista, Lili Nurlaili, Imas Masriah
Addresses:
Department of Education Management, Head of Education Program, Head of School Al Azkar, Pamulang, Kota Tangerang Selatan, Banten, Indonesia.
Using deep learning to create an adaptive system transforms high school students’ independent learning. This study will create and deploy a personalized learning pathway system for private senior high school Ridyadlul Jannah Ciseeng students based on their learning styles and progress. The system uses deep learning algorithms, notably neural networks, to analyze student performance data, anticipate learning outcomes, and offer resources and activities that match each student’s competency and speed. Our mixed-method approach included qualitative educator interviews and quantitative student learning data analysis to identify pedagogical issues. The system architecture incorporates a user-friendly interface, real-time data collection, and a CNN-powered recommendation engine. Initial testing focused on maths and science with 100 kids. The technology adapts dynamically to varied learning contexts, improving student engagement and comprehension. Student and teacher feedback shows that personalized recommendations address shortcomings and improve understanding. The system’s scalability makes it applicable across subjects and grade levels. This study shows that deep learning can bridge the gap between traditional teaching methods and current technology to revolutionize education. It improves academic achievement and gives pupils lifelong learning skills by encouraging autonomous study. Future studies will integrate gamification and peer collaboration to enhance learning.
Keywords: Adaptive Learning System; Deep Learning; Independent Learning; Personalized Education; Convolutional Neural Network (CNN); Real-Time Data; Traditional Teaching; Academic Performance.
Received on: 01/04/2024, Revised on: 29/06/2024, Accepted on: 05/08/2024, Published on: 16/12/2024
AVE Trends in Intelligent Techno Learning, 2024 Vol. 1 No. 2, Pages: 107-120