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<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">JCER</journal-id><journal-title-group><journal-title>Journal of Contemporary Educational Research</journal-title></journal-title-group><issn>2208-8466</issn><eissn>2208-8474</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/jcer.v10i7.15338</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Artificial Intelligence-Enhanced Digital Educational Resources in Chinese Higher Education: From Resource Availability to Quality Governance</title><url>https://artdesignp.com/journal/JCER/10/7/10.26689/jcer.v10i7.15338</url><author>ShiHui,MengXiaoyu</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>10</volume><issue>7</issue><history><date date-type="pub"><published-time>2026-08-05</published-time></date></history><abstract>Digital educational resources have become a central component of Chinese higher education, but the policy and institutional focus is shifting from resource availability to quality, adaptability, and governance. This review article examines how artificial intelligence can support the development, organization, recommendation, classroom use and evaluation of digital educational resources in Chinese higher education. Drawing on policy documents, international guidance and studies on digital competence, learning analytics and artificial intelligence in education, the article uses a resource life-cycle perspective to analyze opportunities and risks. It argues that artificial intelligence can improve resource matching, formative feedback and inclusive access, but these benefits depend on human review, pedagogical alignment, transparent platform governance, data protection and student artificial intelligence literacy. The article proposes a quality governance framework covering resource standards, teacher professional support, student competence development, platform accountability and iterative evidence-based evaluation. The study provides a practical reference for universities seeking to transform digital resource systems from repositories of content into learning-centered, responsible and continuously improved educational infrastructures.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>The State Council of the People’s Republic of China, 2022, China Launches Smart Platform for Education Public Services. Accessed on: July 22, 2026. Available from: https://english.www.gov.cn/statecouncil/ministries/202203/28/content_WS6241bacdc6d02e53353285fd.html</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B2" content-type="article"><label>2</label><element-citation publication-type="journal"><p>The State Council of the People’s Republic of China, 2025, China Unveils Blueprint for Building Strong Education System by 2035. Accessed on: July 22, 2026. Available from: https://english.www.gov.cn/policies/latestreleases/202501/20/content_WS678d85c6c6d0868f4e8eef83.html</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B3" content-type="article"><label>3</label><element-citation publication-type="journal"><p>The State Council of the People’s Republic of China, 2025, Chinese Smart Education Online Platform Surpasses 164 MLN Users. Accessed on: July 22, 2026. Available from: https://english.www.gov.cn/archive/statistics/202505/17/content_WS6828769cc6d0868f4e8f29e4.html</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B4" content-type="article"><label>4</label><element-citation publication-type="journal"><p>Kasneci E, Sessler K, Küchemann S, et al., 2023, ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education. Learning and Individual Differences, 103: 102274. DOI: 10.1016/j.lindif.2023.102274</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B5" content-type="article"><label>5</label><element-citation publication-type="journal"><p>Chan CKY, 2023, A Comprehensive AI Policy Education Framework for University Teaching and Learning. International Journal of Educational Technology in Higher Education, 20: 38. DOI: 10.1186/s41239-023-00408-3</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B6" content-type="article"><label>6</label><element-citation publication-type="journal"><p>UNESCO, 2023, Guidance for Generative AI in Education and Research. UNESCO, Paris. Accessed on: July 22, 2026. Available from: https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B7" content-type="article"><label>7</label><element-citation publication-type="journal"><p>UNESCO, 2019, Beijing Consensus on Artificial Intelligence and Education. UNESCO, Paris. Accessed on: July 22, 2026. Available from: https://unesdoc.unesco.org/ark:/48223/pf0000368303</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B8" content-type="article"><label>8</label><element-citation publication-type="journal"><p>Miao F, Holmes W, Huang R, et al., 2021, AI and Education: Guidance for Policy-makers. UNESCO, Paris. Accessed on: July 22, 2026. Available from: https://unesdoc.unesco.org/ark:/48223/pf0000376709</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B9" content-type="article"><label>9</label><element-citation publication-type="journal"><p>Crompton H, Burke D, 2023, Artificial Intelligence in Higher Education: The State of the Field. International Journal of Educational Technology in Higher Education, 20: 22. DOI: 10.1186/s41239-023-00392-8</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B10" content-type="article"><label>10</label><element-citation publication-type="journal"><p>Vuorikari R, Kluzer S, Punie Y, 2022, DigComp 2.2: The Digital Competence Framework for Citizens. Publications Office of the European Union, Luxembourg. DOI: 10.2760/115376</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B11" content-type="article"><label>11</label><element-citation publication-type="journal"><p>Redecker C, Punie Y, 2017, European Framework for the Digital Competence of Educators: DigCompEdu. Publications Office of the European Union, Luxembourg. DOI: 10.2760/159770</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B12" content-type="article"><label>12</label><element-citation publication-type="journal"><p>Miao F, Cukurova M, 2024, AI Competency Framework for Teachers. UNESCO, Paris. Accessed on: July 22, 2026. Available from: https://www.unesco.org/en/articles/ai-competency-framework-teachers</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B13" content-type="article"><label>13</label><element-citation publication-type="journal"><p>Miao F, Shiohira K, Lao N, 2024, AI Competency Framework for Students. UNESCO, Paris. Accessed on: July 22, 2026. Available from: https://www.unesco.org/en/articles/ai-competency-framework-students</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B14" content-type="article"><label>14</label><element-citation publication-type="journal"><p>Siemens G, 2013, Learning Analytics: The Emergence of a Discipline. American Behavioral Scientist, 57(10): 1380–1400. DOI: 10.1177/0002764213498851</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B15" content-type="article"><label>15</label><element-citation publication-type="journal"><p>Zawacki-Richter O, Marin VI, Bond M, et al., 2019, Systematic Review of Research on Artificial Intelligence Applications in Higher Education: Where Are the Educators? International Journal of Educational Technology in Higher Education, 16(1): 39. DOI: 10.1186/s41239-019-0171-0</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B16" content-type="article"><label>16</label><element-citation publication-type="journal"><p>Pardo A, Siemens G, 2014, Ethical and Privacy Principles for Learning Analytics. British Journal of Educational Technology, 45(3): 438–450. DOI: 10.1111/bjet.12152</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B17" content-type="article"><label>17</label><element-citation publication-type="journal"><p>Tzimas D, Demetriadis S, 2021, Ethical Issues in Learning Analytics: A Review of the Field. Educational Technology Research and Development, 69: 1101–1133. DOI: 10.1007/s11423-021-09977-4</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B18" content-type="article"><label>18</label><element-citation publication-type="journal"><p>Selwyn N, 2019, Should Robots Replace Teachers? AI and the Future of Education. Polity Press, Cambridge.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B19" content-type="article"><label>19</label><element-citation publication-type="journal"><p>Guzman-Valenzuela C, Gomez-Gonzalez C, Rojas-Murphy Tagle A, et al., 2021, Learning Analytics in Higher Education: A Preponderance of Analytics but Very Little Learning? International Journal of Educational Technology in Higher Education, 18: 23. DOI: 10.1186/s41239-021-00258-x</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B20" content-type="article"><label>20</label><element-citation publication-type="journal"><p>Romero C, Ventura S, 2020, Educational Data Mining and Learning Analytics: An Updated Survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10(3): e1355. DOI: 10.1002/widm.1355</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B21" content-type="article"><label>21</label><element-citation publication-type="journal"><p>Ifenthaler D, Yau JYK, 2020, Utilising Learning Analytics to Support Study Success in Higher Education: A Systematic Review. Educational Technology Research and Development, 68: 1961–1990. DOI: 10.1007/s11423-020-09788-z</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B22" content-type="article"><label>22</label><element-citation publication-type="journal"><p>Holmes W, Bialik M, Fadel C, 2019, Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign, Boston.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B23" content-type="article"><label>23</label><element-citation publication-type="journal"><p>OECD, 2021, OECD Digital Education Outlook 2021: Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots. OECD Publishing, Paris. DOI: 10.1787/589b283f-en</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B24" content-type="article"><label>24</label><element-citation publication-type="journal"><p>Luckin R, Holmes W, Griffiths M, et al., 2016, Intelligence Unleashed: An Argument for AI in Education. Pearson, London.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B25" content-type="article"><label>25</label><element-citation publication-type="journal"><p>Xue E, Li J, 2021, Improving the Quality of Online Education in China. In: Creating a High-Quality Education Policy System: Insights from China. Springer, Singapore, 191–201.</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
