A Decision Support System for Personalized Learning in Higher Education

Lusy Tunik Muharlisiani (Universitas Wijaya Kusuma Surabaya, Surabaya, Indonesia)
Widyatmike Gede Mulawarman (Education Management Department, Faculty of Teacher Training and Education, Mulawarman University, Indonesia)
R Rugaiyah (Universitas Islam Riau, Pekanbaru, Indonesia)
Siti Nur Azizah (Universitas Putra Bangsa, Kebumen, Indonesia)
Perdy Karuru (Universitas Kristen Indonesia Toraja, Toraja, Indonesia)

AL ISHLAH Jurnal Pendidikan
Vol 15, No 4 (2023): AL-ISHLAH: JURNAL PENDIDIKAN

This research presents a Decision Support System (DSS) designed to facilitate personalized learning in higher education. Utilizing the Best Worst Method (BWM), a popular Multi-Criteria Decision-Making (MCDM) technique, the study evaluated various learning strategies against set criteria based on the preferences and priorities of educators at University X. The results revealed One-on-One Tutoring as the most preferred method for personalized learning, followed by technology-enabled strategies such as Online Self-paced Courses and Adaptive Learning Software. These findings provide critical insights into the relative importance of different learning strategies, contributing to the development of a DSS capable of recommending the most suitable approaches for personalized learning. The implementation of such a system has been proposed as a means to augment decision-making processes within educational environments and potentially yield positive impacts on academic achievement. It is advisable to conduct additional research to authenticate these findings in various educational settings and investigate prospects for integrating empirical data into the process of decision-making.