human-computer interaction at cmu jodi forlizzi jason hong
TRANSCRIPT
Human-Computer Interaction at CMU
Jodi ForlizziJason Hong
Why are these hard to use?
HCI at CMU
Our mission is to create and evaluate effective, useful, and enjoyable experiences with technology, through engagement with the disciplines of computer science, social science, cognitive science, design, and engineering.
HCI at CMU
• Multidisciplinary research areas:• Enabling technology• Human assistance and well-being• Interdisciplinary centers• Learning science and technology• Social computing• Research through design
• ~20 faculty, ~40 PhD students
HCI at CMU
Our approach• User-centered design and development• Qualitative and quantitative study• Active role of prototyping• Labs and naturalistic settings• With the people who will use the product
HCI at CMU
Multidisciplinary research areas:• Enabling technology• Human assistance and well-being• Interdisciplinary centers• Learning science and technology• Social computing• Research through design
Enabling Technology
• Natural Programming• Alice: Making Programming Accessible• Automatic calibration of projectors• Human-Robotic interaction / Assistive robots• Context-aware computing• Human modeling• Models of attention• Tools for creating web-based mashups• Usable Privacy and Security
Making Mashups with Marmite
Anti-Phishing Training
Anti-Phishing Phil
Web Browser Warnings
• How effective are browser warnings?
Privacy and Security for Pervasive Computing
Privacy and Security for Pervasive Computing
Social Computing
• Footprints, use social nets vs global warming• Designing online communities• HomeNet• Mobile social computing• Information displays• MOVE• Impact• Glanceable email displays• My agent as myself or another
Social computing
Our research is developing social, context-aware applications that:
• Sense and provide information about people and their physical and social context
• Improve decision-making by creating applications that present information in appropriate ways
• Inspire positive changes in people’s behavior
Information display
Create visualizations that:• Build on the science of warnings• Integrate multiple pieces of data• Show trends and relationships• Avoid information overload
A Science of Warnings
See the warning?Understand?Believe it?Motivated?
Planning on refining this model for computer warnings
Information display
Design variables we have explored
• Abstraction
• Symbolism
• Complexity
• Social representation
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MOVE
Maps Optimized for the Vehicular Environment
• Goal: use cognitive resources efficiently in the context of in-car navigation
• Approach: systematic study of navigation activities, information design techniques, information optimization techniques
• Fivefold improvement over static maps
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IMPACT
Improving and Motivating Physical Activity Using Context• Goal: allow people to see opportunities for increasing
daily activity, motivate them to change their behavior to do so
• Approach: ethnographic study with those who have set and reached or failed to reach goals to become more active, system design and evaluation
• To date, users increase awareness and motivation for increasing physical activity
Glanceable email displaysHow to design glanceable visuals for contexts of
divided attention?• Simple visuals are not preferred over complex
ones• Colored representations can be successfully
interpreted peripherally• Impact on performance small, impact on
preference large
My agent as myself or another
How would users interact with agents that resembled the user?
• Agents that look like the self are rated highly for credibility
• Seen as more credible when someone else creates the faces
• Self-esteem may play a role in the adoption of an agent that looks like the user or is simply familiar
• Design implications for agents that maintain social relationships with users
Conclusions
Multidisciplinary research areas:• Enabling technology• Human assistance and well-being• Interdisciplinary centers• Learning science and technology• Social computing• Research through design