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    生成式人工智能增强学科教学适应性的 逻辑理路与实践路径

    Logical Rational and Practical Paths for Generative Artificial Intelligence in Enhancing Subject Teaching Adaptability

    [浏览次数:2984]

【作      者】:

张玉柳, 罗江华


【关 键 词 】:

生成式人工智能; 适应性; 学科教学适应性; 人机协同; 有限理性


【栏      目】:

课程与教学


【中文摘要】:

随着生成式人工智能技术的智能涌现,增强学科教学适应性是学科教学自我发展的内部圈层和外部技术环境相互耦合下以变应变的本质反映。首先,文章对学科教学适应性的本质内涵进行了系统阐述,揭示了学科教学适应性的增强逻辑和阶段特征。其次,文章从教学内容、教学主体及教学评价三个方面论述了生成式人工智能赋能学科教学适应性在实践价值层面的增强效应。增强效应的逻辑机理是以技术适应性提升为基石,围绕教学情境智能化构建主线,最终导向师生对新技术环境的深度适应与协同发展。最后,为持续推动生成式人工智能增强学科教学适应性,文章从根植学科大模型、丰富教学场域结构、坚守学科育人主旨等方面出发,探讨了促进生成式人工智能与学科教学深度耦合的实践路径,以期为相关学科教学实践提供参考和借鉴。


【英文摘要】:

With the intelligent emergence of generative artificial intelligence technology, enhancing the adaptability of subject teaching is an essential reflection of the interplay between the internal layer of subject teaching self-development and the external technological environment. First of all, this paper systematically elaborates on the essential connotation of subject teaching adaptability, revealing the logic of enhancement and stage characteristics of subject teaching adaptability. Secondly, the paper discusses the enhancement effect of generative artificial intelligence in empowering subject teaching adaptability in terms of practical value from three aspects of teaching content, teaching subject and teaching evaluation. The logical mechanism of the enhancement effect is based on the improvement of technological adaptability, centered around the construction of intelligent teaching situation, and ultimately oriented to the deep adaptation and collaborative development of teachers and students in the new technological environment. Finally, in order to continuously promote the enhancement of subject teaching adaptability through generative artificial intelligence, this paper, starting from the aspects such as being rooted in the large model of the subject , enriching the structure of the teaching field, and adhering to the main theme of subject education,discusses the practical path to promote the deep coupling of generative artificial intelligence and subject teaching so as to provide reference and insights for the teaching practice of related subjects.

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