Chris Noessel > Masters Project: Free Range Learning Support> Building a Profile
Introduction  |  Process  |  The Service  |  Experience Prototypes  |  Conclusion  |  Appendices

Building a Profile

  For the simplest features of the service such as SMS Reference, The Cavalry, Media Agent, and Wunderkasten users could sign up on the website via phone. For other service features that require a proprietary interface or particular hardware, potential customers can visit one of the service's storefronts.

Providing a useful learning service depends on knowing some information about each member as a learner. New members would be encouraged to complete a learner profile.

Most people enjoy learning about themselves. Fresh can take advantage of this fact to build learner profiles, manually and automatically, the results of which are used to raise the learner's self-awareness and encourage membership.


Members are free at any time to go online to take tests that refine their profile, or to manually adjust their profile if they feel that the results do not accurately reflect them.


As described in Real-time Links, cooperating free-choice learning environments can track visitors and infer their interests. Some members who join after visiting such places can benefit from having part of their learning profiles already created. Similarly, desktop browser agents could passively note the sites at which participating members spend their time, and infer interests that are incorporated to the profile.

What information does the profile contain?

  1. Learning preferences:
    1. What attitudes hinder their learning?
    2. What is their learning style?
  2. Learning interests: What topics interest them?
  3. Expertise: What do they know already?

What do users do with this profile?

Simple awareness of this information contributes to the development of metacognition skills. For example, a learner who discovers that they learn best at night may deliberately choose to schedule their reading after dinner, and avoid study early in the morning. Additionally, learning achievements can be reflected by changes in a user's profile, over time for the learner's review.

What does Fresh do with this profile?

The profile can be used when matching learners in communities of practice. For example, in the Learn Gety service component, users visiting a history museum may want to be notified if another WWII aficionado is nearby for discussion.

With the service component called Topic Drift, past learning successes can be used to establish meaningful connections between topics the user would like to learn and what he or she already knows. Both Learn Gety and Topic Drift are discussed below. Several other service components rely on the stored information.

Description of Use

References and Influences:

  • The Creativity Pool: This site lets users type in a topic, and its search engine finds related ideas for inspiration. Users can read other's ideas, browse from a menu to the left of related topics, or post their own. Users can also collaboratively filter the ideas they read.
  • Everything2: This site is a text-based semantic node network which allows its users to create new nodes of meaning to which all others can contribute. At the bottom of each page are links of varying relation to the main topic. Everything2's open-ended structure and addictive surfability ground my faith in the usefulness of this component and serve as one its main inspirations.

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