By Ariadni Papana (Cleveland State University)
Information
"BASE-on-AI” is a baseline model for integrating Generative-AI into online and hybrid statistics courses, supporting instructors and students in today’s AI-driven analytics era. Motivated by the growing role of AI in academia and the workforce, this model builds students’ AI literacy and critical thinking while promoting personalized, collaborative, and engaged learning—skills essential for careers in data science, statistics, and research. The model consists of two core components: a syllabus AI-statement and AI-modified labs (AILs). AILs combine traditional data analysis with AI-guided problems, balancing conventional and AI-enhanced learning. These problems, engineered by instructors or students using structured or exploratory prompts, focus on conceptual understanding rather than coding and contribute no more than 15% of total points.
The model provides a strong foundation for AI-enhanced learning offering real-time support in a low-stress environment. Designed for research universities, community colleges, four-year colleges, and AP Statistics, it supports classes of up to 35 students at all levels. While built for online delivery, it is adaptable for in-person instruction. Evidence for efficacy is based on comparing modified and unmodified lab scores, reflections, and conceptual assessments. The activity aims to improve exam performance, adopt new technology, and enhance engagement through teamwork. IRB is not required.