Unpacking the "Black Box" of AI in Education
This work addresses the need for clarity and accessibility in AI terminology for educational researchers and practitioners, though it is incremental as it synthesizes existing knowledge rather than introducing new methods.
The paper tackles the problem of unclear definitions and applications of AI in education by providing an introductory overview of AI methods, advances, and limitations, aiming to equip educationalists with accessible knowledge to interrogate and shape human-centered AI development.
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.