This workshop for UNLV educators, co-hosted by Lied Library’s Data Services and the Teaching and Learning Commons (TLC), explores practical ways to embed data into coursework so students must interpret, analyze, and communicate findings in their own voice. We’ll look at assignment types that are inherently resistant to GenAI shortcuts while deepening students’ quantitative and critical-thinking skills.

Workshop Outcomes

• Design data-driven assignments that incorporate authentic, geographical, or otherwise impactful datasets to reduce generic GenAI responses.
• Integrate multimodal outputs (such as story maps, data visualizations, and digital narratives) that demand critical interpretation and creative synthesis.
• Evaluate when and how to scaffold reasoning steps so students must show process, decision-making, and justification rather than only final outputs.
• Apply strategies to detect AI-generated work and develop assessment criteria that reward originality, data literacy, and presentation.