2025 Vol.8 Oct.N05

• Title: Research on the Transformation of Computer Language Teaching Methods Under the Impact of Chat-Based AI
• Name: Mengxia Gu,xianghong Jiang,xiongkai Shao,huiping Zhang
• Company: Hubei University of Technology Engineering and Technology College,Wuhan,430068,China
• Abstract:

  Chat-based AI is profoundly disrupting traditional educational models. As a technology-driven discipline, computer language instruction faces particularly urgent demands for pedagogical transformation. This study explores the evolution of teaching methodologies in computer language education under the influence of Chat-based AI. By examining the multidimensional impact of Chat-based AI on computer language instruction, it systematically analyzes the core essence of this discipline. Utilizing programming languages as a medium, it cultivates computational thinking and digital problem-solving skills through structured knowledge transfer and practical training. The disruptive influence of Chat-based AI is revealed across three dimensions: teaching resources, interaction models, and evaluation systems. By establishing a tripartite interactive system of "AI Teaching Assistant-Student-Instructor," it expands the temporal and spatial boundaries of teaching interactions. Through real-time data collection embedded within programming environments, AI constructs a multi-dimensional evaluation system incorporating competency maps and dynamic profiles, shifting teaching assessment from outcome-oriented to process-empowering. Based on these impacts, specific strategies for transforming computer language teaching methods are proposed. An AI-driven dynamic resource supply chain synchronizes instructional content with technological advancements. Personalized learning pathways are designed through learner profiling and a dual-layer resource allocation system to address differentiated learning needs. Cross-disciplinary competency integration is promoted by leveraging AI to design real-world projects, cultivating versatile talents with comprehensive capabilities. This aims to provide a methodological framework for computer language instruction in the AI era, revealing pathways for the deep integration of intelligent technologies with educational fundamentals.

  
  

• Keyword: Chatbot AI; Computer Programming Languages; Teaching Methods; Transformation Strategies; Teaching Resources;
• DOI: 10.12250/jpciams2025091010
• Citation form: Mengxia Gu,xianghong Jiang,xiongkai Shao,huiping Zhang.Research on the Transformation of Computer Language Teaching Methods Under the Impact of Chat-Based AI[J]. Computer Informatization and Mechanical System,2025,Vol.8,pp.

[1] Jayabalan J, Dorasamy M. Revitalizing Higher Education Institutions: Embracing Frugal Innovation for Transformation[J]. Procedia Computer Science, 2024, 234:1305-1312.

[2] Pradana P H, Sutajaya I M, Suja I W. Transformation of Early Childhood Education: Integrating Technology in Early Childhood Learning[J]. Journal of Gemilang, 2024, 1(3):9-19.

[3] Zhang L, Bao W Y, Zhao L L. Educational Mirror of the "Intelligence Divide": An Underlying Perspectives on the Digital Transformation of Education[J]. Modern Educational Technology, 2024, 34(7):51-60.

[4] Liu Z, Li Q. Research on Work Process-Oriented Hybrid Teaching Method Based on OBE Concept [J]. Academic Journal of Management and Social Sciences, 2025, 10(1):101-105.

[5] Picano WDS, Machado GS, Carvalho MMD, et al. Hobots: A Remote Teaching Method for Collaborative Robotics Learning[J]. 2024 IEEE Frontiers in Education Conference (FIE), 2024:1-8.

[6] Krishnamurthy B, Sharma P K, Hasan N, et al. Computer simulation versus chalk and talk for experimental pharmacology teaching[J]. National Journal of Pharmacology and Therapeutics, 2024, 2(2):84-89.

[7] Brown N, Xie B, Wiese E S F S. Teaching Ethics in Computing: A Systematic Literature Review of ACM Computer Science Education Publications[J]. ACM Transactions on Computing Education, 2024, 24(1):6.1-6.36.

[8] Karmakar S, Pal T, Koley C. Detection of cognitive load during computer-aided education using infrared sensors[J]. Cognitive Neurodynamics, 2025, 19(1):1-16.

[9] Asfani K, Chen H L. Problem or project-based computer-supported collaborative learning practices in computer education: A systematic review of SSCI articles published from 2014 to 2023[J]. Education and Information Technologies, 2025, 30(6):7627-7658.

[10] Isaeva R, Karasartova N, Dznunusnalieva K, et al. ENHANCING LEARNING EFFECTIVENESS THROUGH ADAPTIVE LEARNING PLATFORMS AND EMERGING COMPUTER TECHNOLOGIES IN EDUCATION[J].Jurnal Ilmiah Ilmu Terapan Universitas Jambi, 2025, 9(1):144-160.

[11] Videnovik M, Vold T, Kinig L, et al. Game-based learning in computer science education: a scoping literature review[J]. International Journal of STEM Education, 2023, 10(1):1-23.

[12] Esteban Pérez Flores, Malacara A A, Cano S R M, et al. Competencies in Computer Security and Resolution of Technological Problems in Higher Education Students[J]. Journal of Computer and Communications, 2024, 12(4):171-185.

[13]Sonsoles López-Pernas, Saqr M, Conde M, et al. Mapping Computer Engineering Education Research: A Topic Analysis[J]. Computer, 2025, 58(1):66-75.

[14] Wang F. Comparative Study and Reform of Aesthetic Education General Education Curriculum Design[J]. International Journal of Education and Humanities, 2025, 18(2):165-173.

[15] Xu Z. Research on the Reform of School-Enterprise Cooperation Teaching and Education Mode for Computer Majors[J]. Journal of Contemporary Educational Research, 2024, 8(2):144-150.