<?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">LNE</journal-id><journal-title-group><journal-title>Lecture Notes in Education, Arts, Management and Social Science</journal-title></journal-title-group><issn>TBA</issn><eissn>2705-053X</eissn><publisher><publisher-name>WHIOCE PUBLISHING PTE. LTD.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18063/LNE.v4i3.1818</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Value Symbiosis and Knowledge Reconstruction: Research on School-Enterprise Collaborative Paths of Art Basic Theory Teaching in the AI Era</title><url>https://artdesignp.com/journal/LNE/4/3/10.18063/LNE.v4i3.1818</url><author>WangZhiping,WangRong,WanCuirong,LiaoWenjing</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>4</volume><issue>3</issue><history><date date-type="pub"><published-time>2026-03-26</published-time></date></history><abstract>The rapid development of generative artificial intelligence has completely reconstructed the logic of artistic creation and the aesthetic evaluation system. The teaching of basic art theory in colleges and universities is confronted with three practical dilemmas: the disconnection between the traditional theoretical system and emerging art forms, the imbalance between a single teaching subject and interdisciplinary education demands, and the misalignment between static teaching modes and dynamic technological iteration. Based on the core perspectives of value symbiosis and knowledge reconstruction, this paper breaks through the limitation of superficial technical tool integration into teaching, takes school-enterprise collaboration as the core path, and employs bibliometric analysis to explore the internal demands of art theory teaching reform and the essential logic of school-enterprise collaboration in the AI era, to construct a teaching reform and teacher training system for basic art theory adaptable to the intelligent era. Combined with collaborative practice cases between colleges and art technology enterprises, this study reveals the operation mechanism of resource complementarity, responsibility sharing, and achievement sharing between schools and enterprises, and explores the practical path for the deep coupling of art theory and AI technology. The research results provide an operable practical paradigm for the innovation of basic art theory teaching and interdisciplinary education models in colleges and universities in the AI era, and also offer a theoretical reference for the further improvement of the school-enterprise collaborative education mechanism.</abstract><keywords>Value symbiosis, Knowledge reconstruction, Artificial intelligence, Basic art theory teaching, School-enterprise collaboration</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1] Li YZ, 2022, Reconstruction of Fundamental Art Theory Courses in the Age of Artificial Intelligence. Art Research, (3): 102&amp;ndash;107.
[2] Li SS, 2024, The Application of AI Painting in Artistic Creation: Taking Stable Diffusion as an Example. Modern Information Technology, 8(8): 133&amp;ndash;137.
[3] Wang Q, 2023, Pathways for Developing Composite Faculty in Art Education from the Perspective of School-Enterprise Collaboration. Art &amp;amp; Design, (5): 138&amp;ndash;141.
[4] Wang YX, 2022, Construction of an Industry-Academia-Research Collaborative Education System in the Context of New Engineering Construction: Taking Universities in the Guangdong-Hong Kong-Macao Greater Bay Area as Examples. China University Science &amp;amp; Technology, (5): 80&amp;ndash;85.
[5] Huang XY, 2024, The Boundary Between Generative AI and Painting Art: Artistic Redemption in the Gestell. Journal of Tianjin Academy of Fine Arts, (3): 22&amp;ndash;24.
[6] Tong LB, Chen LL, 2023, Research on the School-Enterprise Collaborative Education Mechanism Based on the Modern Apprenticeship System: Taking the Interior Art Design Major as an Example. Journal of Liaoning Economy Vocational and Technical College, (3): 159&amp;ndash;161.
[7] Yang JF, Qiao PR, Li YM, 2019, A Review of Machine Learning Classification and Algorithms. Statistics &amp;amp; Decision, 35(6): 36&amp;ndash;40.
&amp;nbsp;</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
