Alifah Bigum Nabila
Universitas Negeri Padang

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A Chatbot-Based Expert System for Supporting Conceptual Understanding in DC Circuit Analysis: Development and Evaluation in Electrical Engineering Education Benny Haposan Sianipar; Alifah Bigum Nabila; Usmeldi Usmeldi; Rahmiati Rahmiati
AL-ISHLAH: Jurnal Pendidikan Vol 18, No 3 (2026): In Progress September 2026
Publisher : STAI Hubbulwathan Duri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35445/alishlah.v18i3.9817

Abstract

This study addresses the limited development of chatbot-based expert systems that integrate rule-based reasoning and conceptual guidance for direct current (DC) circuit analysis learning in electrical engineering education. The study aimed to develop and evaluate a chatbot-based expert system designed to support students’ conceptual understanding of DC circuit analysis. A Research and Development (RD) approach employing the 4D model (Define, Design, Develop, Disseminate) was applied in this study. The effectiveness evaluation used a one-group pretest–posttest design involving 25 undergraduate students from an Electrical Engineering Education program. The developed system was validated by one electrical engineering expert and two educational media experts before implementation. The validation results showed high validity across all evaluated aspects, with Aiken’s V values categorized as very valid. The practicality test indicated that the system was highly practical, achieving a mean score of 4.32 out of 5.00 (86.3%). The effectiveness test showed improvement in students’ learning outcomes, reflected by a normalized gain (N-gain) score of 0.32 in the moderate category. In addition, the paired sample t-test demonstrated a statistically significant difference between pretest and posttest scores (p 0.001). Although the study was conducted with a limited sample and without a control group, the findings indicate that the chatbot-based expert system showed potential to support students’ conceptual understanding and procedural learning in DC circuit analysis. This study contributes to the development of AI-assisted learning media in vocational and engineering education, particularly in supporting interactive and concept-oriented learning environments.