Teaching and Learning with AI: How Artificial Intelligence is Transforming the Future of Education
This issue of XRDS explores the budding topic of AI in education, diving into examples of applications as well as key opportunities and challenges surrounding the use of AI for teaching and learning.
Abstract
search and development and has the potential to transform the ways we teach and learn around the world. In this issue of XRDS, we explore the budding topic of AI in education, diving into examples of applications as well as key opportunities and challenges surrounding the use of AI for teaching and learning. First, Dr. Ryan Baker (professor at the University of Pennsylvania) provides an overview of key learning analytics methods that leverage AI, machine learning, and data mining techniques for educational contexts and shares examples of ways in which these methods have been applied to assess and support various aspects of students’ learning and other educational outcomes. He also draws attention to some interesting challenges, including difficulties with generalizability and the risk of algorithmic bias, and shares some ways to get involved and learn more about learning analytics. Narrowing in on the challenge of building inclusive and equitable AI for education, Dr. Rod Roscoe (associate professor at Arizona State University) uses a humancentered approach and poses four heuristic questions that we should keep in mind Blackboards are fashionable. Everyone praises them, and every school has them; ...[n]o teacher now dares question their utility; but how many teachers prove their utility by daily use? To how many are they a constant necessity, not an occasional convenience?” These words were written in a short essay published in The American Educational Monthly in 1866 [1]. More than 150 years later, the classroom looks vastly different. When I taught in a high school math classroom in 2018, my classroom did not have a blackboard, but rather a markerboard, a document camera, and a projector to broadcast a computer screen. Yet, although the technology has evolved, these presentation tools carried on the same spirit of the original blackboard. They offered students the opportunity to see the mathematics illustrated, interact with the ideas, and present their own problem-solving methods for the class to see and learn. Now, the technologies that allow us to present ideas on a board, whether written in chalk or projected as a digital image, are not just fashionable conveniences; they are constant necessities “ in the modern classroom. We use them daily, and they have shaped pedagogical approaches to emphasize visualizations of abstract ideas, facilitate lively collaborative discussions, and incorporate students’ own creative interactions. This goes to show that, as technology evolves, so do the ways in which we teach and learn. I often wonder what’s next for education. What will our future classrooms look like? What “hot” technologies exist today that will ultimately shape teaching and learning in the future? One potential answer to this question brings us to the subject of this issue: artificial intelligence (AI). AI has certainly been an upward trending topic in a variety of sectors, not just education. From self-driving cars to AI-generated art, news stories pop up every day about how advancements in AI development and research are driving new and exciting innovations, with more and more speculation about how these technologies will ultimately influence our day-to-day lives. However, in the world of education, AI has had its foot in the door for some time, with academic research on computer-assisted instruction and intelligent tutoring systems dating back to the 1950s. While academic research on AI in education has been growing for many years (for interested readers, check out the International Artificial Intelligence in Education Society1), it is only within the past few years that AI-enabled tools have really taken the spotlight in education. An increasing number of learning environments and assessment systems are using AI and data-driven approaches to support assessment, teaching, and learning behind the scenes. With a market projected to be worth $6 billion by 2024 [2], AI in education is certainly an active and thriving area for re-