Online AI Literacy Course Design and Measurement: A Community of Inquiry Framework and the Scale for the Assessment of Non-Experts’ AI Literacy

Abstract

Artificial intelligence is increasingly embedded in everyday life, reshaping how people think, live, and work. AI outputs include hallucinations because they are likelihoods and probabilities derived from the trained data. The AI outputs reinforce existing biases because AI systems are trained on content that already contains them. AI literacy and critical thinking are crucial, debunking AI hype and enabling people to leverage AI’s potential effectively and ethically. This study is theoretically rooted in constructivism, which holds that individuals actively construct and confirm knowledge. This paper proposes three pillars for an online AI literacy course and an instrument to measure learning outcomes for non-expert AI users, serving as both a theoretical framework for AI literacy course design and an educational intervention. A community of inquiry (CoI) framework provides a theoretical foundation for an online AI literacy course and supports critical thinking. The online AI literacy course is structured around three pillars: technical understanding, critical appraisal, and practical application, which correspond to the three factors of the scale for the assessment of non-experts’ AI literacy (SNAIL). Integrating the three pillars of the course into the SNAIL offers methodological and pedagogical benefits by enabling educators and instructional designers to ensure alignment between what is taught and what is evaluated.

Keywords: AI literacy, SNAIL, constructivism, a CoI framework, critical thinking, hallucinations