Proceedings of the 2026 2nd International Conference on Education Research and Training Technologies (ERTT 2026)

2026 2nd International Conference on Education Research and Training Technologies (ERTT 2026)

📍Xi'an, China🗓️ 11-13 September 2026
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Strategies for Improving Digital-Intelligent Teaching Competence of Engineering Teachers Driven by AI

Authors
Zhigang Chen1, *
1School of Mechanical and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, 100044, China
*Corresponding author. Email: gangzi22@163.com
Corresponding Author
Zhigang Chen
Available Online 30 October 2026.
DOI
10.2991/978-2-38476-628-4_10How to use a DOI?
Keywords
Artificial Intelligence; Digital-Intelligent Teaching Competence; Engineering Teachers; Electrical and Electronic Technology; Smart Teaching
Abstract

The rapid development of artificial intelligence is profoundly reshaping the higher education landscape, making the digital-intelligent teaching competencies of university engineering faculty a critical variable in driving the digital transformation of education. Taking the smart teaching practice of the Electrical and Electronic Technology course as a case study, this paper systematically elaborates a smart teaching reform pathway centered on cloud-based course resource construction, multi-dimensional knowledge graph development, the application of AI teaching assistants and intelligent agents, smart learning analytics and learner profiling, as well as online-offline blended teaching models. On this basis, it proposes strategies for enhancing university engineering teachers’ digital-intelligent teaching competencies from three dimensions: institution, teacher, and technology. The findings indicate that using course-level smart teaching reform as a practical vehicle and embedding teacher competency development into authentic teaching contexts represents an effective path for transitioning from “technical training” to “capacity generation.”

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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Volume Title
Proceedings of the 2026 2nd International Conference on Education Research and Training Technologies (ERTT 2026)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
30 October 2026
ISBN
978-2-38476-628-4
ISSN
2352-5398
DOI
10.2991/978-2-38476-628-4_10How to use a DOI?
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.

Cite this article

risenwbib
TY  - CONF
AU  - Zhigang Chen
PY  - 2026
DA  - 2026/10/30
TI  - Strategies for Improving Digital-Intelligent Teaching Competence of Engineering Teachers Driven by AI
BT  - Proceedings of the 2026 2nd International Conference on Education Research and Training Technologies (ERTT 2026)
PB  - Atlantis Press
SP  - 98
EP  - 105
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-628-4_10
DO  - 10.2991/978-2-38476-628-4_10
ID  - Chen2026
ER  -