MDPI AG Acta Medica Okayama 1999-5903 17 8 2025 A Verilog Programming Learning Assistant System Focused on Basic Verilog with a Guided Learning Method 333 EN Pin-Chieh Hsieh Department of Electronic Engineering, National Taipei University of Technology Tzu-Lun Fang Department of Electronic Engineering, National Taipei University of Technology Shaobo Jin Department of Information and Communication Systems, Okayama University Yuyan Wang Department of Information and Communication Systems, Okayama University Nobuo Funabiki Department of Information and Communication Systems, Okayama University Yu-Cheng Fan Department of Electronic Engineering, National Taipei University of Technology With continuous advancements in semiconductor technology, mastering efficient designs of high-quality and advanced chips has become an important part of science and technology education. Chip performances will determine the futures of various aspects of societies. However, novice students often encounter difficulties in learning digital chip designs using Verilog programming, a common hardware design language. An efficient self-study system for supporting them that can offer various exercise problems, such that any answer is marked automatically, is in strong demand. In this paper, we design and implement a web-based Verilog programming learning assistant system (VPLAS), based on our previous works on software programming. Using a heuristic and guided learning method, VPLAS leads students to learn the basic circuit syntax step by step, until they acquire high-quality digital integrated circuit design abilities through self-study. For evaluation, we assign the proposal to 50 undergraduate students at the National Taipei University of Technology, Taiwan, who are taking the introductory chip-design course, and confirm that their learning outcomes using VPLAS together are far better than those obtained when following a traditional method. In our final statistics, students achieved an average initial accuracy rate of over 70% on their first attempts at answering questions after learning through our website’s tutorials. With the help of the system’s instant automated grading and rapid feedback, their average accuracy rate eventually exceeded 99%. This clearly demonstrates tha No potential conflict of interest relevant to this article was reported.