ADAPTIVE LEARNING RECOMMENDATION SYSTEM BASED ON DATA SCIENCE ON STUDENT MOTIVATION AND LEARNING ACHIEVEMENT

Kadeni, Ekbal Santoso, Salam (2024) ADAPTIVE LEARNING RECOMMENDATION SYSTEM BASED ON DATA SCIENCE ON STUDENT MOTIVATION AND LEARNING ACHIEVEMENT. INTERNATIONAL JOURNAL OF SOCIETY REVIEWS (INJOSER), 1 (6).

[thumbnail of 9. Done+Adaptive+Learning. 837-850-1.pdf]
Preview
Text
9. Done+Adaptive+Learning. 837-850-1.pdf

Download (195kB) | Preview

Abstract

Advanced technology allows learning platforms to analyze student data in real-time and present appropriate learning material according to their level of understanding. One of the main advantages of adaptive learning is the personalization of learning. The application of this learning method provides better hope for the world of education by adapting to using sophisticated, renewable technological devices. Adaptive learning methods can also be applied to adaptive teaching by class teachers. The benefit is managing student relationship patterns in carrying out education properly and correctly. Data Science can also be used to build predictive models to predict student academic performance. This will of course be based on historical data and relevant variables. That way, education businesses will be helped in providing appropriate interventions, effective classroom settings, and additional support for students who have potential difficulties. Schools must provide adequate training programs for teachers and students to ensure that they can use educational technology effectively. In addition, schools must provide sufficient support for students who do not understand or have difficulty using educational technology.

Item Type: Article
Subjects: L Education > L Education (General)
Divisions: Faculty of Law, Arts and Social Sciences > School of Education
Depositing User: Unnamed user with email admin@adisamedutech.com
Date Deposited: 30 Mar 2026 03:03
Last Modified: 30 Mar 2026 03:03
URI: https://adisamedutech.com/id/eprint/115

Actions (login required)

View Item
View Item