Unpacking the "Black Box" of AI in Education

被引：56

作者：

Gillani, Nabeel ^{[1
]}

Eynon, Rebecca ^{[2
]}

Chiabaut, Catherine ^{[3
]}

Finkel, Kelsey ^{[3
]}

机构：

[1] MIT, Cambridge, MA 02139 USA

[2] Univ Oxford, Oxford, England

[3] Robertson Fdn, New York, NY USA

来源：

EDUCATIONAL TECHNOLOGY & SOCIETY | 2023年 / 26卷 / 01期

关键词：

K-12; education; Artificial intelligence in education; Educational data mining; Learning analytics; Natural language processing; BIG DATA;

D O I：

10.30191/ETS.202301_26(1).0008

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

Recent advances in Artificial Intelligence (AI) have sparked renewed interest in its potential to improve education. However, AI is a loose umbrella term that refers to a collection of methods, capabilities, and limitations-many of which are often not explicitly articulated by researchers, education technology companies, or other AI developers. In this paper, we seek to clarify what "AI" is and the potential it holds to both advance and hamper educational opportunities that may improve the human condition. We offer a basic introduction to different methods and philosophies underpinning AI, discuss recent advances, explore applications to education, and highlight key limitations and risks. We conclude with a set of questions that educationalists may ask as they encounter AI in their research and practice. Our hope is to make often jargon-laden terms and concepts accessible, so that all are equipped to understand, interrogate, and ultimately shape the development of human centered AI in education.

引用

页码：99 / 111

页数：13

共 82 条

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