<?xml version="1.1" encoding="utf-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">erd</journal-id><journal-title-group><journal-title>Education Reform and Development</journal-title></journal-title-group><issn>2652-5364</issn><eissn>2652-5372</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/erd.v8i8.15279</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Exploring Training Pathways for Interdisciplinary Industrial Software Professionals</title><url>https://artdesignp.com/journal/erd/8/8/10.26689/erd.v8i8.15279</url><author>WangJing,LuYan,ChenZhaoying,ZengChenxi</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>8</volume><issue>8</issue><history><date date-type="pub"><published-time>2026-09-10</published-time></date></history><abstract>Against the backdrop of industrial software localization and the increasing integration of artificial intelligence, computer-related programs urgently need to prepare interdisciplinary professionals who combine software development skills, an understanding of industrial contexts, and AI engineering competence. Using a literature review, theoretical analysis, and illustrative case analysis, this study examines current challenges in industrial software education. It identifies three major problems: a mismatch between curricula and industry needs, insufficient depth in industry-education collaboration, and an expanding shortage of interdisciplinary professionals as AI reshapes the field. The study then proposes a curriculum model with regularly updated case resources, AI-augmented teaching supported by AI teaching assistants (AI-TAs), differentiated development of industrial scenario judgment, industrial data sandboxes, and a graded competence evaluation system. The proposed framework offers a reference for computer-related programs seeking to strengthen industrial software education and advance AI-enabled teaching reform.</abstract><keywords>Computer education, Industrial software, Artificial intelligence, Interdisciplinary professional development, Industry-education integration</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1]&amp;nbsp;&amp;nbsp; Pan S, Li J, Gu N, 2025, Artificial Intelligence, Industrial Integration and Industrial Structure Transformation and Upgrading. China Industrial Economics, 2: 23&amp;ndash;41.
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