Applying Collaborative Learning Principles to Teaching with GenAI: A Pre-Calculus Assignment Example

Abstract

As generative artificial intelligence (GenAI) becomes increasingly available to students in higher education, educators face the challenge of designing assignments that promote meaningful learning while minimizing misuse. This conceptual paper demonstrates ways in which six principles originally developed to enhance collaborative learning during group work (positive interdependence, cognitive load management, individual accountability, promotive interaction, social skills development, and group processing) can be effectively applied to a GenAI-supported STEM assignment. We present a detailed analysis of a pre-calculus assignment designed using research-based collaborative learning principles and illustrate how structured prompting, role definition, and iterative reflective cycles can increase the likelihood that GenAI enhances rather than replaces human learning. The proposed framework supports the development of critical thinking, communication, and metacognitive awareness. We conclude with general recommendations for adapting these principles across disciplines and suggest directions for future empirical research and faculty development to support effective GenAI integration in student assignments.