ActivityBased Design

1
Activity-Based Design
John Canny Computer Science Berkeley Institute
of Design
2
Activity-Based Design

• IT designers normally think about
• User needs, goals, tasks, actions (e.g. design a
  ticket machine for BART)
• The users intent is clear, and success is
  well-defined

3
Activity-Based Design

• Design for everyday life on the other hand
  involves
• User desires, motives
• Environment (surroundings)
• Context immediate and implied
• Improvisation, situated action

4
Activity

• Some examples of activity
• A knowledge-work project
• Eating-at-home
• Enjoying-Media (TV, Video, Audio)
• Learning a skill/language
• Getting a job
• Dating
• Personal Wellness

5
Activity

• We are guided by a pragmatic interpretation of
  activity theory from Russian psychology.
• Human behavior is viewed as an ongoing process
  with a stable structure involving people, a
  motive or object and the tools (often
  information objects) that they use.
• Activities are threadsthat span time and space

6
Activity maps (with X. Jiang)
Dating activity
People
Self
Date
Prospect
Mutual friend
Information objects
Movie info
Restaurant guides
Tools
Car
Cell phone
GPS gadget
Places
Home
Restaurant/Cafe
Venue
Times
Evening/weekend
Daytime
7
Using activity maps

• The activity map is a pattern, and makes use of
  patterns to define its elements (people, tools
  etc.)
• We use a method called technology probes to
  involve users in the design process.
• A technology probe is an app that is given to
  users early in the process, that encourages
  adoption and experimentation.

8
Technology probes

• To simplify use of the technology probe, we use a
  method called factoring functionality.
• e.g. for location-aware services, we factor
  complex apps into a few nouns and verbs
• Nouns people and places
• Verbs read, write, listen-to, stream-to,
  search-for
• Most existing location-aware apps can be built on
  these primitives, and we hope new ones will be
  discovered.

9
Technologies

• Native XML-server hosts map data and user data.
  Allows fast implementation of new designs (as
  queries rather than code), arbitrary data types.
• GPS-enabled smart phones (Motorola i830 with
  Java) run a vector-graphics browser to support
  server generated apps (no client code).

10
Automation modeling activities(w/ T. Rattenbury)

• We are also developing models to infer activities
  as patterns in user log data.
• The model we developed is GAP (GAmma-Poisson)
• X is an activity, Y is a hidden affinity for
  some items, and F is use of those items (e.g.
  email to someone, going to a place).

11
GAP and discrete data

• GAP was developed to model user activities from
  desktop and mobile log data.
• We have developed a logger for windows which
  tracks your email, file use and web access.
• Because of deep connections between activity and
  texts, GAP also works very well as a document
  model. It is the most accurate B.O.W.
  probabilistic model on standard (TREC) data
  Canny SIGIR 04.

12
Summary

• The Activity Perspective underpins several of our
  projects.
• It provides a good structure for human-centered
  design which is not driven by particular
  technologies or the constraints of a particular
  environment.
• At the same time, it provides a research
  trajectory which can leverage contextual
  information, to make systems more context-aware.