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Large-Scale Analysis of Visualization Options in a Citizen Science Game.
Miller, Josh Aaron; Lee, Vivian; Cooper, Seth; El-Nasr, Magy Seif.
Afiliação
  • Miller JA; Northeastern University Boston, MA, USA.
  • Lee V; Northeastern University Boston, MA, USA.
  • Cooper S; Northeastern University Boston, MA, USA.
  • El-Nasr MS; Northeastern University Boston, MA, USA.
Article em En | MEDLINE | ID: mdl-33860290
ABSTRACT
Visualization is a valuable tool in problem solving, especially for citizen science games. In this study, we analyze data from 36,351 unique players of the citizen science game Foldit over a period of 5 years to understand how their choice of visualization options are affected by expertise and problem type. We identified clusters of visualization options, and found differences in how experts and novices view puzzles and that experts differentially change their views based on puzzle type. These results can inform new design approaches to help both novice and expert players visualize novel problems, develop expertise, and problem solve.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Proc Annu Symp Comput Hum Interact Play Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Proc Annu Symp Comput Hum Interact Play Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos