AI Implications for Education and Educators

The main goal of this paper is to propose a framework to better understand and capitalize on the many implications of Artificial Intelligence (AI) for education, especially but not limited to the most recent developments of Generative Artificial Intelligence (GenAI). Four complementary categories are identified, each presenting diverse opportunities and challenges:1)Leveraging AI to improve instruction: This involves using AI to create new and more powerful learning opportunities for learners – at all levels of schools and across subject areas as well as instructional contexts.2)Promoting AI Literacy: This involves helping everyone develop sufficient understanding of AI to function in a society where AI is increasingly used.3)Rethinking workforce preparation: This involves responding to the need to change how we prepare future workers, once uses of AI take over functions previously performed by humans in specific occupations.4)Leveraging AI to support educators’ own work: While the focus of the previous three categories is on student learning, here the focus shifts on educators’ using AI in their work to increase their productivity and well-being.In what follows, I will examine each of these areas using conceptual analysis, building on findings from relevant research studies I have been involved in, as well as recent conversations within an interdisciplinary group of faculty, staff and students as part of an internal planning grant for the University of Rochester. For each area, after a brief introduction I will identify and discuss a few key elements; selected illustrations, in most cases reporting findings from relevant research projects, will also be provided in separate “boxes” so they can be read independently.For further information about this paper please contact the author.