Unpacking the 'Black Box' of AI in Education
N. Gillani, R. Eynon, C. Chiabaut, K. Finkel (2021). Unpacking the “Black Box” of AI in K12 education. Educational Technology & Society, Forthcoming
13 Pages Posted: 19 Oct 2021 Last revised: 31 Dec 2022
Date Written: October 19, 2021
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.
Keywords: K-12 Education, Artificial Intelligence in Education, Educational Data Mining, Learning Analytics, Natural Language Processing
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