254 citations · 345 across the 15 of their papers we have counts for
16 papers
Metacognitive Scaffolds Create Productive Friction for AI-Assisted Knowledge Work
Viktor Kewenig, Lev Tankelevitch, Sean Rintel +2
Generative AI imposes new metacognitive demands on knowledge workers as their work shifts from production to planning, evaluation, and orchestration. In a randomized, between-subje…
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…
Scaffolding Human-AI Collaboration: A Field Experiment on Behavioral Protocols and Cognitive Reframing
Alex Farach, Alexia Cambon, Lev Tankelevitch +2
Organizations have widely deployed generative AI tools, yet productivity gains remain uneven, suggesting that how people use AI matters as much as whether they have access. We cond…
Nudging Attention to Workplace Meeting Goals: A Large-Scale, Preregistered Field Experiment
Lev Tankelevitch, Ava Elizabeth Scott, Nagaravind Challakere +2
Ineffective meetings are pervasive. Thinking ahead explicitly about meeting goals may improve effectiveness, but current collaboration platforms lack integrated support. We tested…
Metacognition and Confidence Dynamics in Advice Taking from Generative AI
Clara Colombatto, Sean Rintel, Lev Tankelevitch
Generative Artificial Intelligence (GenAI) can aid humans in a wide range of tasks, but its effectiveness critically depends on users being able to evaluate the accuracy of GenAI o…
Understanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshop
Lev Tankelevitch, Elena L. Glassman, Jessica He +7
Generative AI (GenAI) radically expands the scope and capability of automation for work, education, and everyday tasks, a transformation posing both risks and opportunities for hum…
What Does Success Look Like? Catalyzing Meeting Intentionality with AI-Assisted Prospective Reflection
Ava Elizabeth Scott, Lev Tankelevitch, Payod Panda +3
Despite decades of HCI and Meeting Science research, complaints about ineffective meetings are still pervasive. We argue that meeting technologies lack support for prospective refl…
Are We On Track? AI-Assisted Active and Passive Goal Reflection During Meetings
Xinyue Chen, Lev Tankelevitch, Rishi Vanukuru +3
Meetings often suffer from a lack of intentionality, such as unclear goals and straying off-topic. Identifying goals and maintaining their clarity throughout a meeting is challengi…
Nods of Agreement: Webcam-Driven Avatars Improve Meeting Outcomes and Avatar Satisfaction Over Audio-Driven or Static Avatars in All-Avatar Work Videoconferencing
Fang Ma, Ju Zhang, Lev Tankelevitch +9
Avatars are edging into mainstream videoconferencing, but evaluation of how avatar animation modalities contribute to work meeting outcomes has been limited. We report a within-gro…
The New Calculator? Practices, Norms, and Implications of Generative AI in Higher Education
Auste Simkute, Viktor Kewenig, Abigail Sellen +2
Generative AI (GenAI) has introduced myriad opportunities and challenges for higher education. Anticipating this potential transformation requires understanding students' contextua…
"It's like a rubber duck that talks back": Understanding Generative AI-Assisted Data Analysis Workflows through a Participatory Prompting Study
Ian Drosos, Advait Sarkar, Xiaotong Xu +3
Generative AI tools can help users with many tasks. One such task is data analysis, which is notoriously challenging for non-expert end-users due to its expertise requirements, and…
The CoExplorer Technology Probe: A Generative AI-Powered Adaptive Interface to Support Intentionality in Planning and Running Video Meetings
Gun Woo Warren Park, Payod Panda, Lev Tankelevitch +1
Effective meetings are effortful, but traditional videoconferencing systems offer little support for reducing this effort across the meeting lifecycle. Generative AI (GenAI) has th…
Mental Models of Meeting Goals: Supporting Intentionality in Meeting Technologies
Ava Elizabeth Scott, Lev Tankelevitch, Sean Rintel
Ineffective meetings due to unclear goals are major obstacles to productivity, yet support for intentionality is surprisingly scant in our meeting and allied workflow technologies.…
Ironies of Generative AI: Understanding and mitigating productivity loss in human-AI interactions
Auste Simkute, Lev Tankelevitch, Viktor Kewenig +3
Generative AI (GenAI) systems offer opportunities to increase user productivity in many tasks, such as programming and writing. However, while they boost productivity in some studi…
The Metacognitive Demands and Opportunities of Generative AI
Lev Tankelevitch, Viktor Kewenig, Auste Simkute +4
Generative AI (GenAI) systems offer unprecedented opportunities for transforming professional and personal work, yet present challenges around prompting, evaluating and relying on…
Meeting effectiveness and inclusiveness: large-scale measurement, identification of key features, and prediction in real-world remote meetings
Yasaman Hosseinkashi, Lev Tankelevitch, Jamie Pool +2
Workplace meetings are vital to organizational collaboration, yet relatively little progress has been made toward measuring meeting effectiveness and inclusiveness at scale. The re…