Qualitative analysis reveals AI enhances learning outcomes in online systems, highlighting engagement issues and privacy challenges.
This activity examines the application of Artificial Intelligence (AI) technology in online learning systems through a qualitative approach using library research methods. The industrial revolution 4.0 era and transformation towards Society 5.0 have accelerated AI adoption in education, particularly post-COVID-19 pandemic. This activity utilizes secondary data from international and national journals from IEEE Xplore, ACM Digital Library, SpringerLink, and Google Scholar databases for the 2020-2025 period. Data analysis was conducted through content analysis and thematic analysis techniques. Results indicate that AI provides significant transformative impact through personalized learning, adaptive systems, learning analytics, and automated assessment. AI integration with Learning Management Systems proves to enhance student engagement and learning outcomes. However, implementation faces challenges including infrastructure constraints, data privacy issues, user resistance, and resource limitations. Optimization strategies include human resource capacity development, technological infrastructure development, and comprehensive regulation. Long-term roadmap is divided into three phases: foundation building, acceleration, and transformation to achieve adaptive and sustainable education systems
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Steven S. N. Rogahang (2025) studied this question.
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