Article: AI-powered precision training pathways for engineering ethics and professional competence in Industry 4.0 Journal: International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL) 2026 Vol.36 No.12 pp.4 - 28 Abstract: Driven by Industry 4.0, precision training pathways for engineering ethics and professional competence require deep integration with cutting-edge artificial intelligence. This study proposes an AI-driven framework for 'data-informed, adaptive delivery and iterative optimisation' in engineering ethics and professional development. The model employs natural language processing to analyse engineering case materials and ethical guidelines, constructs knowledge graphs and dynamic learner profiles to support personalised recommendation, and optimises training strategies through deep reinforcement learning. Experiments on public datasets show this approach significantly outperforms traditional instruction and baseline models, achieving an F1-score of 0.824 on professional competence prediction and improving interactive training depth by 31.5. The results validate the proposed precision pathways in enhancing targeting accuracy and pedagogical effectiveness for Industry 4.0 engineers through AI-powered adaptive learning. Inderscience Publishers - linking academia, business and industry through research

Title: AI-powered precision training pathways for engineering ethics and professional competence in Industry 4.0

Authors: Shuqin Cai; Yu Lei

Addresses: School of Marxism, Xiamen Institute of Technology, Xiamen, 361000, China ' School of Marxism, Xiamen Institute of Technology, Xiamen, 361000, China

Abstract: Driven by Industry 4.0, precision training pathways for engineering ethics and professional competence require deep integration with cutting-edge artificial intelligence. This study proposes an AI-driven framework for 'data-informed, adaptive delivery and iterative optimisation' in engineering ethics and professional development. The model employs natural language processing to analyse engineering case materials and ethical guidelines, constructs knowledge graphs and dynamic learner profiles to support personalised recommendation, and optimises training strategies through deep reinforcement learning. Experiments on public datasets show this approach significantly outperforms traditional instruction and baseline models, achieving an F1-score of 0.824 on professional competence prediction and improving interactive training depth by 31.5. The results validate the proposed precision pathways in enhancing targeting accuracy and pedagogical effectiveness for Industry 4.0 engineers through AI-powered adaptive learning.

Keywords: engineering skill training; continuing engineering education; virtual practice teaching; digital twin; ethical risk control.

DOI: 10.1504/IJCEELL.2026.156525

International Journal of Continuing Engineering Education and Life-Long Learning, 2026 Vol.36 No.12, pp.4 - 28

Received: 04 Feb 2026
Accepted: 15 Apr 2026
Published online: 28 Sep 2026 *

Title: AI-powered precision training pathways for engineering ethics and professional competence in Industry 4.0

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