<?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">CEF</journal-id><journal-title-group><journal-title>Contemporary Education Frontiers</journal-title></journal-title-group><issn>3029-1879</issn><eissn>3029-1860</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/CEF.v4i6.15582</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Exploring the Practice of AI-Enabled Integrated “Teaching-Learning-Assessment” Reform in Undergraduate Taxation and Finance Courses</title><url>https://artdesignp.com/journal/CEF/4/6/10.26689/CEF.v4i6.15582</url><author>LiuJun</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>4</volume><issue>6</issue><history><date date-type="pub"><published-time>2026-06-26</published-time></date></history><abstract>In recent years, the rapid advancement of generative AI tools&amp;mdash;such as DeepSeek, ChatGPT, and ChatPPT&amp;mdash;has profoundly transformed university teaching models. Leveraging its powerful capabilities in deep learning and natural language processing, AI empowers classroom instruction across multiple dimensions&amp;mdash;including content generation, personalized learning, intelligent tutoring, data analysis, and virtual teaching&amp;mdash;providing new perspectives and practical pathways for teaching undergraduate finance and taxation courses. Taking the core finance and taxation course &amp;ldquo;Tax Law&amp;rdquo; as a case study, this paper proposes utilizing AI tools to implement pre-class diagnostic assessments of student learning status and resource updates; facilitate in-class scenario creation and intelligent interaction; and enable post-class dynamic evaluation and consolidation/extension of knowledge. This approach aims to shift teaching from being experience-driven to data-driven, and to transform teaching evaluation from focusing solely on final exam results to encompassing a diverse range of learning processes, thereby offering a practical pathway for addressing the fragmentation issue between &amp;ldquo;teaching, learning, and assessment&amp;rdquo; in finance and taxation courses.</abstract><keywords>Artificial intelligence,Intelligent interaction,Diversified evaluation</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1] Wei W, 2025, Challenges and Countermeasures for the Teaching of Management Accounting Courses in Applied Undergraduate Programs Enhanced by Artificial Intelligence. University Education, (S2): 25&amp;ndash;28.
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