While many recognize that forms of artificial intelligence (AI) technology is increasingly infused in our everyday lives, AI’s role in education (K-12, higher education and corporate) is less clear. Some are predicting that AI will enhance teaching and learning by complimenting instructional and assessment practices through big data collection, machine learning and sophisticated prediction. Some see the promise of AI through the fulfillment of support roles such as through the use of chat-bots and intelligent tutors. Others are concerned about the impact of AI on educators and learners, particularly related to security/privacy and data collection, ambiguous decision making/inherent bias, job loss and loss of control. AI is showing promise in the area of research tools, too. In this course, we explore the implications of AI in education (AEID).

Included in the course is a discussion of related terminology and core concepts, the history and current state of AIED, practical considerations, current applications and future predictions about the impact of AI on the educational field.

The readings will focus on a variety of theoretical concepts and will explore the integration of and implications of AIED.

The key, overarching questions we’ll be considering in this course are: What definitions, terminology and core concepts of AI are important to understand as they relate to education? How do we stay current with AI developments in education? What are the implications of AI integration in education today and in the future?