Towards Sharing Student Models Across Learning Systems
ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT II(2021)
摘要
Modern AIED systems develop sophisticated and multidimensional models of students. However, what is learned about students in one system-their skills, behaviors, and affect-is not carried over to other systems that could benefit students by using the information, potentially reducing both the effectiveness and efficiency of these systems. This challenge has been cited by a number of researchers as one of the most important for the field of AIED. In this paper, we discuss existing progress towards resolving this challenge, break down five sub-challenges, and propose how to address the sub-challenges.
更多查看译文
关键词
Student model sharing, AIED system integration, BLAP
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要