paperarXivTrust 82 · PrimaryPublished 3d agoLive · 2d ago
DigitalCoach: Communication and Grounding Gaps in Human and Agentic Computer Use Coaching
Agents are increasingly capable of automating software tasks, but can they teach humans how to use software themselves? We introduce DigitalCoach, a multimodal dataset of 72 human expert-novice computer use coaching sessions consisting of 22,752 dialogue turns grounded in 28.1 hours of screen and input event recordings across five software applications. We use DigitalCoach to evaluate whether state-of-the-art models can teach humans how to use computers. Automated evaluation shows that models differ from humans in how they coach: models provide more direct instructions, but fewer explanations,
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Covers
Has model
Covers (incoming)
Implements (incoming)
Related across the graph
repox0c/doc-skillsnewsLearning to lead in a hybrid human-AI enterpriserepodigiteinfotech/kaironrepoapache/texerarepoxlang-ai/CUA-Gym-HubnewsAI coding agents taught robots how to install GPUs and cut zip tiesrepopandazki/pneuma-skillsrepoa-Fig/Accordionrepomicrosoft/AI-For-BeginnersrepoNatively-AI-assistant/natively-cluely-ai-assistantrepoterrylica/cc-skillsnewsVibe Coding / Agentic workflowmodelAgentCore-8BnewsHow Preply combines AI and human tutors to personalize learningnewsNVIDIA Brings Trusted, 24/7 AI Agents to Telecom OperationsrepoLDJ-creat/video-helper
