Effectiveness of Artificial Intelligence-Based Learning Analytics Tool in Supporting Personalized Learning in Higher Education

Abstract: Effectiveness of Artificial Intelligence-Based Learning Analytics Tool in Supporting Personalized Learning in Higher Education. Objective: The use of Artificial Intelligence (AI) in higher education has become one of the significant innovations to improve the quality of learning, especially through personalization. However, the effectiveness of AI-based learning analytics tools in supporting learning personalization in Indonesian higher education is still not widely explored. This research aims to evaluate the effectiveness of AI-based analytics tools in supporting learning personalization and identify challenges in its implementation. Method: This research uses descriptive qualitative method with in-depth interviews, observation, and document analysis. The respondents included 10 lecturers and 15 students from three universities in Indonesia who have implemented AI-based tools in the learning process. Data were analyzed using thematic analysis techniques to identify key patterns and trends. Finding: The results show that AI-based analytics tools are effective in improving learning personalization. Students using the tool recorded an average academic grade improvement of 15.03%, while lecturers found it helpful in understanding students' learning needs. The main challenges identified were low digital competency (50% of respondents) and concerns regarding data privacy (30% of respondents). Conclusion: AI tools have great potential to support personalized learning, but their success depends on digital literacy training and more transparent data management. This research has implications for the importance of investing in technology-based education infrastructure and policies to ensure sustainable adoption. Keywords: artificial intelligence, personalized learning, higher education, technology effectiveness.