Education / end-user machine teachingmachine teaching and end-user MLParticipation documented
Crowdsourcing the Perception of Machine Teaching
College Park, United States
Participants trained, tested, and retrained a teachable model in their own environments, revealing how end users understand machine teaching.
human-centered designend-user MLdata collectionmodel trainingevaluation
- Region
- North America
- Lead organization
- University of Maryland
- Organization type
- university
- Technology group
- supervised image classification / teachable interfaces
- Activity status
- published_case
- Start year
- 2020
- Last updated
- Mar 25, 2026
- Participation mode
- end-user training and reflection in teachable interfaces
- Participants
- crowd workers; end users
- Methods
- crowdsourcing; training/testing cycles; reflective feedback
- AI lifecycle stages
- data collection; model training; evaluation
- Evidence summary
- Participants trained, tested, and retrained a teachable model in their own environments, revealing how end users understand machine teaching.
- Atlas assessment
- Cautious · Medium confidence · evidence grade B
- Uncertainty
- Participation is real but structured primarily as controlled task interaction rather than longer-term co-governance.
- Participation group
- Community In The Loop
- Technology description
- supervised image classification / teachable interfaces
- Funding
- Not documented
- Region of activity
- national
- Verification status
- Paper Verified
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