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Designing and evaluating Buster: an indexical mobile travel planner for public transportation

Published:28 November 2007Publication History

ABSTRACT

This paper elaborates on previous research into the design and use of mobile information systems for supporting the use of public transportation. Contributing to this domain of HCI research, we describe the design and evaluation of a mobile travel planner, Buster, for the public city bus system of a large regional city in Denmark. Carrying on from on earlier research activities, we did contextual interviews, acting out of future scenarios in situ, and iterative paper prototyping to extend on previous design ideas and explore further the principle of indexicality in interface design for context-aware mobile systems. We then implemented a functional prototype application and evaluated it in the field.

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  1. Designing and evaluating Buster: an indexical mobile travel planner for public transportation

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    • Published in

      cover image ACM Other conferences
      OZCHI '07: Proceedings of the 19th Australasian conference on Computer-Human Interaction: Entertaining User Interfaces
      November 2007
      323 pages
      ISBN:9781595938725
      DOI:10.1145/1324892

      Copyright © 2007 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 28 November 2007

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      Acceptance Rates

      OZCHI '07 Paper Acceptance Rate26of42submissions,62%Overall Acceptance Rate362of729submissions,50%

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