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Evaluating Singleplayer and Multiplayer in Human Computation Games

2017/03/02 by Kristin Siu, Matthew Guzdial, Siu, Kristin +4
Computer Science · #Data Visualization and Analytics #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Innovative Human-Technology Interaction #Mobile Crowdsensing and Crowdsourcing #cs.HC

paper · pdf · doi:10.48550/arxiv.1703.00818

10 pages, 4 figures, 2 tables

arxiv created 2017/03/02 · openalex publication_date 2017/03/02 · arxiv updated 2017/03/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Human computation games (HCGs) can provide novel solutions to intractable computational problems, help enable scientific breakthroughs, and provide datasets for artificial intelligence. However, our knowledge about how to design and deploy HCGs that appeal to players and solve problems effectively is incomplete. We present an investigatory HCG based on Super Mario Bros. We used this game in a human subjects study to investigate how different social conditions---singleplayer and multiplayer---and scoring mechanics---collaborative and competitive---affect players' subjective experiences, accuracy at the task, and the completion rate. In doing so, we demonstrate a novel design approach for HCGs, and discuss the benefits and tradeoffs of these mechanics in HCG design.

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