Evaluation of an LLM-Powered Student Agent for Teacher Training

被引：2

作者：

Bhowmik, Saptarshi ^{[1
]}

West, Luke ^{[1
]}

Barrett, Alex ^{[1
]}

Zhang, Nuodi ^{[1
]}

Dai, Chih-Pu ^{[2
]}

Sokolikj, Zlatko ^{[1
]}

Southerland, Sherry ^{[1
]}

Yuan, Xin ^{[1
]}

Ke, Fengfeng ^{[1
]}

机构：

[1] Florida State Univ, Tallahassee, FL 32306 USA

[2] Univ Hawaii Manoa, Honolulu, HI 96822 USA

来源：

TECHNOLOGY ENHANCED LEARNING FOR INCLUSIVE AND EQUITABLE QUALITY EDUCATION, PT II, EC-TEL 2024 | 2024年 / 15160卷

关键词：

Teaching simulation; Teacher education; Large Language Model; Sentiment Analysis; Cognitive-affective states; Virtual Student Agent;

D O I：

10.1007/978-3-031-72312-4_7

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

As technology continues to advance, there is a growing interest in exploring the potential of generative agents and large language model (LLM)-powered virtual students to revolutionize the field of education. In this work, we present Evelyn AI, a LLM-powered virtual student conversation agent that we developed for pre-service teacher training in a virtual environment. Students powered by Evelyn AI exhibit varying baseline conceptual understanding levels, dynamic cognitive-affective states, and short-term memory. These features enable personalized, adaptive training and promote a more engaging and immersive learning experience for pre-service teachers. We describe the design and implementation of Evelyn AI, and report results of alpha testing to assess the utility of Evelyn AI for pre-service teacher training.

引用

页码：68 / 74

页数：7

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