<?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">JARD</journal-id><journal-title-group><journal-title>Journal of Architectural Research and Development</journal-title></journal-title-group><issn>2208-3529</issn><eissn>2208-3537</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/JARD.v10i5.15788</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Teaching and Study of Artificial Intelligence-Driven Regional Architectural Design Courses</title><url>https://artdesignp.com/journal/JARD/10/5/10.26689/JARD.v10i5.15788</url><author>DingDing,WangLing</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>10</volume><issue>5</issue><history><date date-type="pub"><published-time>2026-10-23</published-time></date></history><abstract>In the process of digitization and globalization, traditional regional architectural design education faces certain limitations. Although AI technology offers a new pathway for the innovation of architectural education, the integration of the two still encounters multiple challenges. To explore the compatibility between AI technology and the teaching of regional architectural design, this study proposes a reconstruction approach for the teaching system that integrates technological empowerment, cultural restructuring, and capability development. Combining teaching cases, this work constructs a multi-level modular curriculum system that progresses from foundational empowerment to core practice and then to expansive innovation. Additionally, the study introduces a multi-dimensional evaluation mechanism that emphasizes both process and outcomes, along with a multi-type supporting resource development system.</abstract><keywords>Artificial intelligence, Architecture, Style imitation, Text-to-image generation, Image-to-image generation</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;&amp;nbsp;&amp;nbsp;&amp;nbsp; Du S, Lu X, Chen Z, et al., 2024, Research Into a Stable Diffusion-Based Human-Machine-Human Teaching Model for Architectural Design Courses. Journal of Green Building, 19(3): 299&amp;ndash;318.
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