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Exploring Human-AI Control Over Dynamic Transitions Between Individual and Collaborative Learning

机译:探索人与人工智能对个体学习与协作学习之间动态过渡的控制

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Dynamically transitioning between individual and collaborative learning activities during a class session (i.e., in an un-planned way, as-the-need-arises) has advantages for students, but existing orchestration tools are not designed to support such transitions. This work reports findings from a technology probe study that explored alternative designs for classroom co-orchestration support for dynamically transitioning between individual and collaborative learning, focused on how control over the transitions should be divided or shared among teachers, students, and orchestration system. This study involved 1) a pilot in an authentic classroom scenario with AI support for individual and collaborative learning; and 2) design workshops and interviews with students and teachers. Findings from the study suggest the need for hybrid control between students, teachers, and AI systems over transitions as well as for adaptivity and/or adaptability for different classrooms, teachers, and students' prior knowledge. This study is the first to explore human-AI control over dynamic transitions between individual and collaborative learning in actual classrooms.
机译:在课堂上,个人学习活动与协作学习活动之间的动态转换(即按计划外的方式,按需增加)对学生有利,但现有的编排工具并非旨在支持这种转换。这项工作报告了一项技术调查研究的结果,该研究探索了课堂协同管理支持的替代设计,以支持在个人学习和协作学习之间动态过渡,重点在于如何在老师,学生和编排系统之间划分或共享对过渡的控制。这项研究涉及1)一名飞行员在真实的课堂场景中进行,并为个人和协作学习提供了AI支持; 2)设计工作坊并与学生和老师进行访谈。该研究的发现表明,需要在过渡期间对学生,教师和AI系统之间进行混合控制,以及针对不同教室,教师和学生的先验知识的适应性和/或适应性。这项研究是第一个探索人类AI控制实际教室中个体学习和协作学习之间的动态过渡的方法。

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