Research on the Application of Generative Artificial Intelligence in Education
Generative artificial intelligence (AI), equipped with capabilities such as large language models, multimodal generation, and adaptive interaction, is deeply penetrating the education sector and driving reforms in teaching models, learning methods, and teaching evaluation systems. Adopting a collaborative analytical framework of technology, education, and ethics, this paper sorts out the technical characteristics and educational applicability of generative AI, and constructs a full-scenario application system covering basic education, higher education, and vocational education. Combined with typical cases, it reveals its application value in personalized learning, human-machine collaborative teaching, intelligent evaluation and feedback, and balanced allocation of educational resources. The study finds that generative AI can improve teaching efficiency, optimize learning experience, and promote educational equity, but it also faces multiple challenges including technical hallucinations, data security, ethical anomalies, digital divide, and academic integrity. Accordingly, this paper proposes a development path of controllable technology, education-oriented, ethics-guarded, and collaborative governance, and builds an integrated application ecosystem featuring policy regulation, technical optimization, literacy improvement, and scenario innovation, so as to provide theoretical support for the safe, standardized, and efficient implementation of generative AI in education.
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