Workshop on Priorities for a Changing Landscape of Computing Education in the Age of AI

Speaker:

Dr. Shuchi Grover, Ph.D.

Looking Glass Ventures | Edfinity

Director of AI & Education Research

Senior Research Scientist | Chief Learning Officer

Bio:

Dr. Shuchi Grover is the Director of AI and Education Research at Looking Glass Ventures in Austin, TX. She is a computer scientist and learning scientist by training who has been committed to PK-12 computing education in formal and informal settings for over two decades. She has led several US National Science Foundation-funded projects involving research & design of learning that helps develop 21st-century competencies in computing, data science, and AI as well as the integration of STEM, computer science (CS) and data science. She created, co-authored, and edited Computer Science in K-12: A-to-Z Handbook on Teaching Programming, a popular resource for preparing K-12 CS teachers. She advises several national and international efforts related to advancing computing and AI education at the K-12 level. She is the recipient of the 2024 Henry and Beyna David Award from the US National Academies of Science, Engineering and Mathematics.

Grover has a Ph.D. in Learning Sciences and Technology Design (Stanford University), master’s degrees in education (Harvard University) and computer science (CWRU, Cleveland), and bachelor’s degrees in computer science and physics (India).

Title:

Priorities for a Changing Landscape of Computing Education in the Age of AI

Abstract:

This interactive teacher workshop explores the evolving landscape of K-12 computing education as we navigate the integration of AI competencies alongside traditional computer science concepts. Participants will examine how foundational computational thinking (CT) skills intersect with and support AI understanding, while identifying essential new competencies students need in an AI-driven world. Through small activities and discussions, we will explore practical approaches to weaving AI concepts into existing CS, including data literacy, model training fundamentals, and ethical considerations in AI systems. We will also examine the role of LLMs and Generative AI in K-12 CS classrooms.