Rethinking Computer Science Education in the Age of GenAI
Orit Hazzan, Yael Erez
Abstract
In this opinion piece, we explore the idea that GenAI has the potential to fundamentally disrupt computer science education (CSE) by drawing insights from 10 pedagogical and cognitive theories and models. We highlight how GenAI improves CSE by making educational practices more effective and requires less effort and time, and all at a lower cost, properties that have the potential to make GenAI a disruptive technology for CSE. Each of the 10 theories and models examined serves as a lens through which we observe and interpret the impact of GenAI on CSE. The 10 theories and models are grouped into 3 categories: Learning (Constructivism, Cognitive Load, and Motivation), Pedagogy (Bloom’s Taxonomy, Assessment, Personalization/Diversity/Equity, and Didactic Transposition), and Competencies (the KSA Model, Computational Thinking, and Metacognition).