Page History

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Evaluation:

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Users:

We found our users by primarily contacting our relatives and friends. However, we did not know many very-savvy users of location-sharing services. Thus, we asked our TA (Katrina) for advice. She suggested a few potential users (this practice is called Snowball Sampling), out of which we contacted one but did not hear back from that person. We informally contacted another person but that person declined from participating in the study. We then found a user who is very-savvy with mobile technologies and knew a lot about how location-sharing apps worked (through that person’s research). However, that user did not personally use those apps. Thus, we ended up doing a relative re-ordering of our users and considered this user to be our medium-savvy user and promoted our other user (who we initially considered to be medium-savvy) to the status of a very-savvy user.performed three user tests on users that we recruited from our personal networks of friends and family. We determined the suitability of the users by questioning them about their usage of mobile applications and of location-sharing applications. We found one very basic user, one medium-expert user, and one highly-expert user.
    Our basic user had never used any location-sharing apps and did not have a working knowledge of the capabilities of such mobile applications. This make the user representative of the category. Our medium-savvy user had had a mental model of how those apps worked but did not personally use them. This is slighly less savvy than our original definition, but close enough to be useful. Our expert user had used Google Latitude and Facebook checkin, but only sometimes. This is not quite as engaged as our original conception, but once again close enough to be useful.

Tests:

We performed our tests by briefing users with a written briefing, and then asking them to perform four tasks. There was one user, one facilitator and two passive observers in each case. The first task was to view information about a friend, and then determine what information about him/herself was visible to that same friend. The second task was to create a new LocaShare with parameters specified by the facilitator. The third task was to modify a LocaShare according to parameters specified by the facilitator. The fourth and final task was to obtain information from the Overview mode concerning what friends could see the user in a particular locationThough we had to do a relative re-ordering of our study participants, these users are representative of the user population categorization from GR1. User #2 never used any location-sharing apps previously and did not have a working knowledge of the capabilities of such mobile applications. Thus, that user is still a non-savvy user per the corresponding definition in GR1. We had to relax some of the constraints (usage of location-sharing apps) for the medium-savvy user because our User #3 had a mental model of how those apps worked but did not personally use them. User #1 can still be considered a very-savvy user because that user frequently used Google Latitude with family members and had previously used Facebook check-in (albeit rather infrequently).

Briefing:

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