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Proceedings of the 10th Annual International Seminar on Transformative Education and Educational Leadership, AISTEEL 2025, 5 December 2025, Medan, North Sumatera Province, Indonesia

Research Article

Design and Evaluation of an AI-Based E-Learning System for Graduate Education

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  • @INPROCEEDINGS{10.4108/eai.5-12-2025.2363820,
        author={Ngatmini  Ngatmini and Baharuddin  Baharuddin and Mansur  AS and Sitti  Subaedah},
        title={Design and Evaluation of an AI-Based E-Learning System for Graduate Education},
        proceedings={Proceedings of the 10th Annual International Seminar on Transformative Education and Educational Leadership, AISTEEL 2025, 5 December 2025, Medan, North Sumatera Province, Indonesia},
        publisher={EAI},
        proceedings_a={AISTEEL},
        year={2026},
        month={7},
        keywords={Artificial Intelligence; e-learning; ADDIE adaptive learning intelligent systems},
        doi={10.4108/eai.5-12-2025.2363820}
    }
    
  • Ngatmini Ngatmini
    Baharuddin Baharuddin
    Mansur AS
    Sitti Subaedah
    Year: 2026
    Design and Evaluation of an AI-Based E-Learning System for Graduate Education
    AISTEEL
    EAI
    DOI: 10.4108/eai.5-12-2025.2363820
Ngatmini Ngatmini1, Baharuddin Baharuddin2,*, Mansur AS3, Sitti Subaedah4
  • 1: Department of Educational Management, Graduate School, Universitas Negeri Medan, Indonesia
  • 2: Department of Educational Technology, Graduate School, Universitas Negeri Medan, Indonesia
  • 3: Department of Computer Science, Universitas Negeri Medan, Indonesia
  • 4: Department of Community Education, Universitas Negeri Medan, Indonesia
*Contact email: baharuddin@unimed.ac.id

Abstract

The advancement of information and communication technology has driven innovation in higher education, particularly in intelligent learning systems. This study develops an Artificial Intelligence (AI)–based e-learning system to improve learning in the Educational Management Graduate Program at Universitas Negeri Medan. Using a Research and Development (R&D) approach with the ADDIE model, data were collected through interviews, surveys, and curriculum analysis involving lecturers and graduate students. The system integrates adaptive learning recommendations, automated feedback, learning analytics, and an NLP-based chatbot. Results show significant improvements, including increased learning efficiency (58%), faster feedback response time (65%), and high user satisfaction (89%). Interactivity and student motivation also improved by 54% and 61%, respectively. Expert validation through Focus Group Discussion (FGD) confirmed strong system feasibility (92%) and pedagogical relevance (85%). These findings indicate that AI-based e-learning enhances personalization, engagement, and data-driven learning in higher education.

Keywords
Artificial Intelligence; e-learning; ADDIE, adaptive learning, intelligent systems
Published
2026-07-10
Publisher
EAI
http://dx.doi.org/10.4108/eai.5-12-2025.2363820
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