computing for social needs jennifer mankoff uc berkeley
TRANSCRIPT
Computing for Social Needs
Jennifer Mankoff
UC Berkeley
Inspiration in the World: Finding the Right Combination
Hard, real problemsHard HCI problems
Low intuition about users Success hard to test Technology not always a good solution
Hard computer science problems
ExamplesWord prediction (+ & -)Augmented canes (+ & -)
OutlineApproaches to research in computing
for social needs (CSN)Example: DesignExample: MethodExample: ToolConclusions
Approaches To Research in CSNDesign: For usersMethod: For designers/evaluatorsTool: For programmers/designers
Approaches To Research in CSNDesign: For users
Identify need Investigate solutions Prototype, test & iterate
Method: For designers/evaluatorsTool: For programmers/designers
Approaches To Research in CSNDesign: For usersMethod: For designers/evaluators
Identify model or theory Test against circumstances or population Iterate
Tool: For programmers/designers
Approaches To Research in CSNDesign: For usersMethod: For designers/evaluatorsTool: For programmers/designers
Identify repeating need or use of technology
Abstract out Test for reusability
OutlineApproaches to research in computing
for social needs (CSN)Example: DesignExample: MethodExample: ToolConclusions
Design Example: NutritionNeed: Healthier dietsAssumptions Idea: Keep track of purchases, display
advice
Design Example: NutritionNeed: Healthier diets
Manage disease America’s weight problem Manage child health
Assumptions Idea: Keep track of purchases, display
advice
Design Example: NutritionNeed: Healthier dietsAssumptions
People don’t really know what they consume
Receipts contain enough information for us to estimate nutrition
Idea: Keep track of purchases, display advice
Design Example: NutritionNeed: Healthier dietsAssumptions Idea: Keep track of purchases, display
advice
Nutrition: Hard HCI ProblemsFormative evaluation: testing perception Interface designSummative evaluation in real-use
setting
Nutrition: Formative EvalSurvey shoppersBackground research
Nutrition: Formative EvalSurvey shoppers
Perceived calcium consumption Perceived need for supplements Calcium consumption in receipts
Background research
Nutrition: Formative EvalSurvey shoppersBackground research
Use of shopping receipts in bookkeeping Interest in nutrition % of time eating out Impact of coupons, advice on shopping
behavior
Nutrition: Hard HCI ProblemsFormative evaluation: testing perception Interface design
While at home Continual Peripheral
While shopping While entering data
Summative evaluation in real-use setting
“Was that ‘Apple cider’Or ‘Apple scraper’
Nutrition: Hard HCI ProblemsFormative evaluation: testing perception Interface designSummative evaluation in real-use
setting Measures change in awareness Measures change in behavior
Nutrition: Hard Computer Science ProblemsRecognition
OCR Who eats what Quantities, ingredients
Ambiguity
Nutrition: Hard Computer Science ProblemsRecognition
OCR Who eats what Quantities, ingredients
Ambiguity
Nutrition: Hard Computer Science ProblemsRecognitionAmbiguity
Resolving imperfect recognition automatically
Resolving imperfect recognition with user’s help
OutlineApproaches to research in computing
for social needs (CSN)Example: DesignExample: MethodExample: ToolConclusions
Method Example: Comparative AccessibilityNeed: Increased accessibility in all
interfacesAssumptions Idea: Develop metrics for interpreting
simulated testing results
Method Example: Comparative AccessibilityNeed: Increased accessibility in all
interfaces More inclusive Increase quality of life
Assumptions Idea: Develop metrics for interpreting
simulated testing results
Method Example: Comparative AccessibilityNeed: Increased accessibility in all
interfacesAssumptions
Can’t test every interface with every type of disability
Can simulate disability sufficiently for testing
Idea: Develop metrics for interpreting simulated testing results
Method Example: Comparative AccessibilityNeed: Increased accessibility in all
interfacesAssumptions Idea: Develop metrics for interpreting
simulated testing results
Comparative Accessibility: Hard HCI ProblemsCan a novice simulating disability give
feedback on an interface designed for experts in that disability?
How should heuristics include accessibility?
How do disabilities impact GOMS models?
How do disabilities impact Fitts’ law?
OutlineApproaches to research in computing
for social needs (CSN)Example: DesignExample: MethodExample: ToolConclusions
Tool Example: Mouse predictionsNeed: Access to any application Assumptions Idea: Recognize problems, predict
targets, and use that to make the mouse do the right thing
Tool Example: Mouse predictionsNeed: Access to any application
Equal access Increased independence
Assumptions Idea: Recognize problems, predict
targets, and use that to make the mouse do the right thing
Tool Example: Mouse predictionsNeed: Access to any applicationAssumptions
Low vision or motor impairment No access to application code Access to OS (e.g. app can be installed)
Idea: Recognize problems, predict targets, and use that to make the mouse do the right thing
Tool Example: Mouse predictionsNeed: Access to any application Assumptions Idea: Recognize problems, predict
targets, and use that to make the mouse do the right thing.
Mouse predictions: Hard HCI problemsExisting motion models only account for
averagesExisting user models inaccurateUI for compensation unclear
Mouse predictions: Hard HCI problemsExisting motion models only account for
averages Minimum jerk model:
X(t) = X0 + (X0 – Xf) (154 - 65 - 103)
Fitts’ law: MT = a + b log(A/W)
Existing user models inaccurateUI for compensation unclear
Mouse predictions: Hard HCI problemsExisting motion models only account for
averagesExisting user models inaccurate
KLM extra cognitive cycles No model of fatigue
UI for compensation unclear
Mouse Prediction: Other Models Velocity
Thrashing ( = target)
Spasming
Overshooting
Other characteristics?
Mouse predictions: Hard HCI problemsExisting motion models only account for
averagesExisting user models inaccurateUI for compensation unclear
“Beat Fitts’ law” Feedback affects recognition
Mouse Predictions – UIs for CompensationGravity wells and area mouseMediation
Mouse Predictions: Hard Computer Science ProblemsRecognition
Account for feedback Account for fatigue
Ambiguity Better interfaces for multiple targets? Interface for multiple directions? Appropriate balance of control and
automation
OutlineApproaches to research in computing
for social needs (CSN)Example: DesignExample: MethodExample: ToolConclusions
ConclusionsPlenty of hard real problemsPlenty of hard HCI problemsPlenty of hard computer science
problemsResearch needed in designs, methods
& tools
Tool Example: Reconstruction of Mismatched InterfacesNeed: Adaptation to any set of input
devices