THE IMPORTANCE OF LMS TO IMPROVE DATA SCIENCE LEARNING PERFORMANCE

Abstract

The increasing demand for talent with Artificial Intelligence competencies in recent years has driven the growth of various non-formal educational institutions in Indonesia. These include training programs, bootcamps, short courses, and eLearning formats—ranging from fully online or offline learning to distance and blended learning models. These programs are typically offered at more affordable prices and with shorter learning durations. Making them attractive to both fresh graduates and professionals seeking to switch careers into the field of Data Science. This has contributed to greater diversity within the Data Science learning ecosystem.

The learning in these non-formal education institutions are usually trainer-centered instruction. The materials of these trainings are delivered with examples. At the end of the training period, participants are assigned a capstone project to examine their understanding of materials.

Although pedagogical methods are commonly used, they often fail to address the specific learning needs of adult learners. Leading to cognitive overload, low engagement, and suboptimal learning outcomes. This study explores the role of Learning Management Systems (LMS) and andragogical approaches to improve data science learning outcome. Drawing on literature reviews and empirical findings, this paper argues that integrating LMS with andragogical approaches can significantly enhance the effectiveness of non-formal Data Science education, particularly in addressing Indonesia’s digital talent gap.