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A location-based educational game for understanding the traveling salesman problem: a case study

Published: 04 September 2017 Publication History

Abstract

Due to the high potential of digital media to support learning processes and outcomes, educational games have gained wide acceptance over the years. The combination of mobile devices with location-based technologies offers new options and possibilities for the development of educational games in consideration of learners' environment with the positive side effect to promote learner's physical activities. This paper introduces a mobile educational game for promoting a better understanding of concepts related to route problems and route optimization on the basis of real world examples in a playful manner. The game combines problem-solving tasks with a quiz to teach concepts related to the Traveling Salesman Problem (TSP) by using the Global Positioning System (GPS) technology.

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  • (2024)An exploration of quantitative models and algorithms for vehicle routing optimization and traveling salesman problemsSupply Chain Analytics10.1016/j.sca.2023.1000565(100056)Online publication date: Mar-2024

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    cover image ACM Conferences
    MobileHCI '17: Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services
    September 2017
    874 pages
    ISBN:9781450350754
    DOI:10.1145/3098279
    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 04 September 2017

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    Author Tags

    1. game-based learning
    2. global positioning system
    3. location-based game
    4. traveling salesman problem

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    • Austrian Federal Ministry of Science, Research, and Economy

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    MobileHCI '17 Paper Acceptance Rate 45 of 224 submissions, 20%;
    Overall Acceptance Rate 202 of 906 submissions, 22%

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    • (2024)An exploration of quantitative models and algorithms for vehicle routing optimization and traveling salesman problemsSupply Chain Analytics10.1016/j.sca.2023.1000565(100056)Online publication date: Mar-2024

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