{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T18:24:51Z","timestamp":1770834291145,"version":"3.50.1"},"reference-count":41,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T00:00:00Z","timestamp":1763424000000},"content-version":"vor","delay-in-days":17,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Comp Applic In Engineering"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Currently, there is a mismatch between traditional Linux teaching and dynamic learning needs. Therefore, this study proposes a dual drive intelligent teaching model based on constructivism and game theory, and constructs a collaborative optimization framework of \u201ctask chain\u2010resource game\u2010container scheduling\u201d. Firstly, design a cognitive transition task chain represented by weighted directed graphs, dynamically adjust node weights through reinforcement learning, and reduce the standard deviation of high\u2010order task completion time; Secondly, establish a tripartite game engine and use multiagent Q\u2010learning to solve Nash equilibrium; Finally, develop a lightweight Docker cluster and voice interaction system to reduce container response latency through a dual objective optimization algorithm. Empirical research has shown that the experimental group achieved a score range of 90+in the Linux certification exam, accounting for 36%. The code quality Abstract Syntax Tree (AST) similarity increased by 19.2%, and the system maintained a task completion rate of 92.7% in high concurrency scenarios. This model provides a replicable and scalable paradigm for current intelligent teaching.<\/jats:p>","DOI":"10.1002\/cae.70112","type":"journal-article","created":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T12:54:33Z","timestamp":1763470473000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Research on the Optimization of an Intelligent Teaching Model for Linux Courses Based on Constructivism and Game Theory"],"prefix":"10.1002","volume":"33","author":[{"given":"Huaibao","family":"Ding","sequence":"first","affiliation":[{"name":"School of Computer Engineering Anhui Wenda University of Information Engineering Hefei China"}]}],"member":"311","published-online":{"date-parts":[[2025,11,18]]},"reference":[{"issue":"8","key":"e_1_2_12_2_1","first-page":"14","article-title":"Optimization and Practical Exploration of Maritime English Teaching Model Based on Artificial Intelligence","volume":"3","author":"Liu 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