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    艺术工作室模型通过将大型学习模型集成到创意过程中,有效地教导人工智能 (AI). 这种方法支持以学生为导向的学习和文物创造,证明适用于人工智能教育.

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    科学领域:

    • 人工智能教育 人工智能教育
    • 艺术工作室模型应用程序
    • 整合创作过程 整合创作过程

    背景情况:

    • 传统的AI教育模式可能无法充分利用创意潜力.
    • 艺术工作室模型提供了一个独特的,自下而上的学习方法.
    • 生成型人工智能工具与制造工件的目标保持一致.

    研究的目的:

    • 评估艺术工作室模型对于教学人工智能 (AI) 的适用性.
    • 探索学生的经验,将大型学习模型 (LLM) 整合到他们的创意工作流中.
    • 为采用这种模式在AI教育中提供证据和案例研究.

    主要方法:

    • 在2024-2025学年进行了定性研究.
    • 一个异步的,工作室风格的AI课程的四个部分被实施.
    • 学生的经验被记录下来,重点关注LLMs在创意任务中的整合.

    主要成果:

    • 艺术工作室模型被证明适用于教育学生的人工智能.
    • 学生成功地将大型学习模型整合到他们的创作过程中.
    • 定性数据和案例研究支持该模型的有效性.

    结论:

    • 艺术工作室模型是人工智能教育的可行和有效的教学方法.
    • 学生指导的学习和人工制造是成功的关键组成部分.
    • 该模型可以根据学生对人工智能的各种需求和兴趣进行调整.