Prior Knowledge and AI Engagement Intentions in Non-STEM Graduate Students

• In Event: AERA Poster Session Sunday 7:45 am
  In Poster Session: Disposition, Identity and Intention: Understanding Adult Learning and Educational Engagement

Abstract

AI literacy education for non-STEM post-secondary students is still in its infancy, often focusing on conceptual understanding. In addition, students' skewed understanding of AI, often derived from social media, can create misconceptions that impede formal education. To address this, we delivered a one-week online module to graduate students in media and instructional design, aiming to develop comprehensive AI understanding and practical skills. Using an exploratory sequential mixed-methods design, we examined the relationship between students' prior AI knowledge, perceived AI benefits, and their intention to engage with AI. Results showed that students' prior knowledge, reinforced by the module, positively predicted their cognitive levels of perceived benefits. However, this positive perception surprisingly negatively impacted students' change of intention toward AI engagement.

Authors

• Shenghua Zha, University of South Alabama

• Yuming He, Suffolk University

• Wu He, National Science Foundation