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Human-Centered Design for Connected Automation: Predicting Pedestrian Crossing Intentions
Sanaz Motamedi, Viktoria Marcus, Griffin Pitts
More than half of the 1.19 million annual traffic fatalities globally involve vulnerable road users, such as pedestrians, with a significant proportion attributable to human error.…
Trust and Reliance on AI in Education: AI Literacy and Need for Cognition as Moderators
Griffin Pitts, Neha Rani, Weedguet Mildort
As generative AI systems are integrated into educational settings, students often encounter AI-generated output while working through learning tasks, either by requesting help or t…
Personalized Worked Example Generation from Student Code Submissions Using Pattern-based Knowledge Components
Griffin Pitts, Muntasir Hoq, Peter Brusilovsky +4
Adaptive programming practice often relies on fixed libraries of worked examples and practice problems, which require substantial authoring effort and may not correspond well to th…
What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AI
Griffin Pitts, Sanaz Motamedi
Conversational AI tools have been rapidly adopted by students and are becoming part of their learning routines. To understand what drives this adoption, we draw on the Technology A…
Impact of eHMI on Pedestrians' Interactions with Level-5 Automated Driving Systems
Viktoria Marcus, Griffin Pitts, Sanaz Motamedi
Each year, over half of global traffic fatalities involve vulnerable road users (e.g. pedestrians), often due to human error. Level-5 automated driving systems (ADSs) could reduce…