Socratic Mind: Scalable Oral Assessment Powered By AI

被引：0
|
作者：
Hung, Jui-Tse [1 ]
Cui, Christopher [1 ]
Popescu, Diana M. [1 ]
Chatterjee, Saurabh [1 ]
Starner, Thad [1 ]
机构：
[1] Georgia Inst Technol, Atlanta, GA 30332 USA
来源：
PROCEEDINGS OF THE ELEVENTH ACM CONFERENCE ON LEARNING@SCALE, L@S 2024 | 2024年
关键词：
AI; Education; Oral Assessment; Socratic Questioning; Large Language Models;
D O I：
10.1145/3657604.3664661
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Interactive teaching methods often lead to higher levels of student engagement with course material. Yet, as class sizes increase, the demand on teaching staff becomes unsustainable. Our solution, Socratic Mind, employs Large Language Models to provide scalable, interactive oral assessments by functioning as a virtual instructor. This paper discusses the outcomes and user feedback from the preliminary implementation of our system in a large classroom environment with 600 students.
引用
收藏
页码：340 / 345
页数：6
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