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Research and analysis on artificial intelligence applications in education: a study across programming, history, and English

Primary research

#760

T1new
Topic
unassigned (set during synthesis)
First seen
2026-07-25 07:19:23
Last seen
2026-07-25 07:19:23

Source raw items (1)

  • Semantic Scholar2026-07-25 07:17:18
    Research and analysis on artificial intelligence applications in education: a study across programming, history, and English

    This paper conducts a systematic review of artificial intelligence integration in programming, history, and English education, focusing on technological applications, practical outcomes, and existing challenges. Against the backdrop of global educational digitalization, AI technologies such as generative models, adaptive learning systems, intelligent tutoring systems, and AI-enhanced learning management platforms have addressed long-standing issues in these disciplines, including low engagement in programming, abstract historical instruction, and one-size-fits-all English teaching. By analyzing 10 recent scholarly works, this study first categorizes mainstream AI educational technologies, then compares their discipline-specific uses in code generation, historical simulation, argument feedback, language practice, and adaptive assessment. It also discusses how these tools influence learner autonomy, teacher workload, classroom interaction, and educational equity. Findings reveal that AI enhances personalized learning but requires pedagogical alignment to avoid superficial knowledge acquisition, student overreliance, data bias, and integrity risks. Future research should prioritize interdisciplinary AI education frameworks, ethical governance mechanisms, teacher training, and long-term impact assessments to promote sustainable AI integration in K-12 and higher education.