Equity and Fairness Challenges in Online Learning in the Age of ChatGPT

被引:0
|
作者
Jamil, Hasan M. [1 ]
机构
[1] Univ Idaho, Dept Comp Sci, Moscow, ID 83844 USA
基金
美国国家卫生研究院;
关键词
Large language model; equity; database; authentic assessment;
D O I
10.1145/3605098.3636108
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Recent research suggest that equity remained a neglected consideration in most learning analytics and continues to be an esoteric concept. Online learning poses many additional equity challenges that largely concerns gender, access to resources, socio-economic conditions, fairness, or feeling of isolation. In this article, we discuss a novel equity concern in the emerging online learning environment often aided by large language models such as ChatGPT. It has been observed that ChatGPT-like models can be a significantly powerful learning and tutoring aid for learners. However, in online learning and in the absence of a human instructor, ChatGPT could introduce inequity in form of "wrongful" tutoring that could be devastatingly harmful for learners, which we call Ignorant Bias. We illustrate this form of inequity with an illustrative example.
引用
收藏
页码:91 / 92
页数:2
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