Prompting Future Journalists to Prompt: An Experiential Study on GenAI, Critical Literacy, and Reflective Practice in Data News

Abstract

Generative AI (GenAI) is rapidly integrating into newsrooms, creating a paradox: while the industry embraces AI for efficiency, public skepticism persists, and scholars warn of AI's potential to exacerbate information disorder. This underscores an urgent need for a sophisticated approach to AI literacy in journalism education. This paper reports findings from the first phase of a two-phase case study investigating how undergraduate communication students (N=19) with prior journalism training interact with a custom GenAI tool for data-driven storytelling. Through a three-part methodology—pre-study questionnaire, logged experiential task, and post-study survey—our analysis reveals that prior AI experience does not uniformly predict success or critique. Instead, a data-driven thematic analysis identifies four emergent archetypes of engagement: the Director, who treats the AI as a controllable instrument; the Collaborator, who frames it as a creative partner; the Delegator, who views it as an often-unreliable shortcut; and the Antagonist, who experiences it as a deficient obstacle. These archetypes, which align with existing frameworks of user-AI interaction, are actively shaped by students' pre-existing journalistic philosophies. This paper argues for a phenomenologically-informed critical AI literacy that equips students with the metacognitive awareness to reflect on the technological relationships they are building.