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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">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.v6i4.6825</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Research on Influencing Factors of Deep Learning Among High School Students in Western China</title><url>https://artdesignp.com/journal/erd/6/4/10.26689/erd.v6i4.6825</url><author>XueJiao</author><pub-date pub-type="publication-year"><year>2024</year></pub-date><volume>6</volume><issue>4</issue><history><date date-type="pub"><published-time>2024-05-20</published-time></date></history><abstract>To clarify the influential factors of deep learning among high school students in Western China and promote the high-quality development of basic education in Western China. This study adopts the method of stratified sampling and selects high school students at different altitudes as the research object. The results show that the high school students in the western region are in the middle level of deep learning. There are differences in gender, altitude, and other variables in deep learning of students. A multiple linear regression model was used to analyze the influencing factors of deep learning for high school students in Western China. 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