Unpacking the "Black Box" of AI in Education

TL;DR

This paper clarifies the diverse methods and limitations of AI in education, aiming to make AI concepts accessible and guide educationalists in understanding and shaping human-centered AI applications.

Contribution

It provides an accessible overview of AI methods, discusses recent advances and limitations, and offers questions for educators to critically engage with AI in education.

Findings

AI encompasses diverse methods and capabilities.

Recent AI advances have both opportunities and risks for education.

Guidelines are provided for educators to critically assess AI tools.

Abstract

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.