Design and Implementation of an AI-Driven Intelligent Teaching System for Analog Electronic Technology with Integrated Learning Analytics

DOI

10.2991/978-2-38476-628-4_14How to use a DOI?

Keywords

Analog electronic technology; Intelligent teaching system; Knowledge graph; Learning analytics

Abstract

Analog electronics remains a challenge for many engineering students. The reason for this is the gradual acquisition of knowledge, ranging from semiconductor components to circuit behaviour to system design. Without a clear understanding of these connections, knowledge is fragmented and practical application leaves something to be desired. To address this Problem, this article presents an intelligent teaching system for analog electronics that can be used locally. The system organizes the course content in the Component-Circuit-System sequence and integrates structured question-answer rounds, learning analytics, and learning path suggestions based on the respective level of knowledge into a single learning platform. Instead of replacing lectures, it supports lecturers in identifying students’ difficulties, Explain key concepts and guide you to the next learning step. The strength of the system lies in the visualization of the knowledge structure, the traceability of the learning process, and the explicit explanation of the logic behind the suggestions. This Initiative provides a practical and proven framework for collaborative learning between humans and AI in engineering education.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Nan Wang
AU  - Gang Yu
AU  - Yuan Xu
AU  - Bin Sun
AU  - Kang Zhao
PY  - 2026
DA  - 2026/10/30
TI  - Design and Implementation of an AI-Driven Intelligent Teaching System for Analog Electronic Technology with Integrated Learning Analytics
BT  - Proceedings of the 2026 2nd International Conference on Education Research and Training Technologies (ERTT 2026)
PB  - Atlantis Press
SP  - 128
EP  - 135
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-628-4_14
DO  - 10.2991/978-2-38476-628-4_14
ID  - Wang2026
ER  -