44 citations · 48 across the 5 of their papers we have counts for
4 papers · 2 filters
Beyond "ChatGPT Can Make Mistakes": Designing Interventions to Support Metacognitive Monitoring in AI-Assisted Work
Manuel A. D. Santos, Paul Thiesse, Steeven Villa +4
AI assistance places a metacognitive demand on users, who must judge their own competence and the system's. Yet designers lack comparative evidence on which interventions to choose…
Available but Unclaimed: An Empirical Study of Human-AI Synergy
Robin Welsch, Michelle Rausch, Pascal Knierim +4
People increasingly reason with large language models (LLMs), yet complementary capabilities do not guarantee outperforming both components. In a between-subjects study, participan…
Explaining Too Much? Understanding How Large Language Model Reasoning Traces Influence Performance and Metacognition
Daniela Fernandes, Daniel Buschek, Lev Tankelevitch +2
Large Language Model interfaces are increasingly verbose, exposing intermediate reasoning traces alongside final answers. Traces are framed as transparency mechanisms, yet it is un…
Conversations in Space: Non-Linear LLM Interaction in Everyday Use
Rifat Mehreen Amin, Alperen Adatepe, Daniela Fernandes +2
As LLM conversations grow, their histories capture alternative directions, decisions, and evolving lines of thought that can be difficult to navigate through chat alone. We investi…