Dynamic game adaptation based on detection of behavioral patterns in the player learning curve

D. Vassileva, B. Bontchev

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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    Abstract

    In educational serious games, the learning curve of a player represents his/her progress in acquiring cognitive abilities and new knowledge necessary for solving the game challenges. Hence, it is very important for an adaptive serious game to have a mechanism for detection of patterns of player´s learning curve in playing time. The paper presents the application of a game adaptation method based on automatic and dynamically detection of specific learning curves at runtime within a 3D video game of car driving in various weather conditions. The method uses a client-side software component called “Player-centric rule-and-pattern-based adaptation asset” and developed within the scope of the RAGE (Realising and Applied Gaming Ecosystem) H2020 project. The component is incorporated into a 3D car driving video game in order to enable a dynamic detection of different patterns of player performance. It allows the video game scenario to be adapted to each player by providing appropriately for him/her challenges and game features. We carried out a practical experiment with students from Sofia University, Bulgaria, where we found that adaptation of game difficulty by applying the RAGE software component resulted to improved game playability.
    Original languageEnglish
    Title of host publicationProceedings of the 10th Annual International Conference on Education and New Learning Technologies
    Subtitle of host publicationEDULEARN2018
    Place of PublicationPalma de Mallorca
    PublisherIATED Academy
    Pages8182-8191
    ISBN (Electronic)978-84-09-02709-5
    ISBN (Print)978-84-09-02709-5
    DOIs
    Publication statusPublished - 2018
    EventEDULearn18: 10th annual International Conference on Education and New Learning Technologies - Mallorca, Palma, Spain
    Duration: 2 Jul 20184 Jul 2018
    https://iated.org/edulearn18/

    Conference

    ConferenceEDULearn18
    Abbreviated titleEDULearn18
    CountrySpain
    CityPalma
    Period2/07/184/07/18
    Internet address

    Fingerprint

    Ecosystems
    Railroad cars
    Students
    Experiments
    Serious games

    Keywords

    • game adaptation
    • player learning curve
    • detection
    • behaviour pattern
    • game component
    • RAGE

    Cite this

    Vassileva, D., & Bontchev, B. (2018). Dynamic game adaptation based on detection of behavioral patterns in the player learning curve. In Proceedings of the 10th Annual International Conference on Education and New Learning Technologies: EDULEARN2018 (pp. 8182-8191). Palma de Mallorca: IATED Academy. https://doi.org/10.21125/edulearn.2018.1905
    Vassileva, D. ; Bontchev, B. / Dynamic game adaptation based on detection of behavioral patterns in the player learning curve. Proceedings of the 10th Annual International Conference on Education and New Learning Technologies: EDULEARN2018. Palma de Mallorca : IATED Academy, 2018. pp. 8182-8191
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    abstract = "In educational serious games, the learning curve of a player represents his/her progress in acquiring cognitive abilities and new knowledge necessary for solving the game challenges. Hence, it is very important for an adaptive serious game to have a mechanism for detection of patterns of player´s learning curve in playing time. The paper presents the application of a game adaptation method based on automatic and dynamically detection of specific learning curves at runtime within a 3D video game of car driving in various weather conditions. The method uses a client-side software component called “Player-centric rule-and-pattern-based adaptation asset” and developed within the scope of the RAGE (Realising and Applied Gaming Ecosystem) H2020 project. The component is incorporated into a 3D car driving video game in order to enable a dynamic detection of different patterns of player performance. It allows the video game scenario to be adapted to each player by providing appropriately for him/her challenges and game features. We carried out a practical experiment with students from Sofia University, Bulgaria, where we found that adaptation of game difficulty by applying the RAGE software component resulted to improved game playability.",
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    Vassileva, D & Bontchev, B 2018, Dynamic game adaptation based on detection of behavioral patterns in the player learning curve. in Proceedings of the 10th Annual International Conference on Education and New Learning Technologies: EDULEARN2018. IATED Academy, Palma de Mallorca, pp. 8182-8191, EDULearn18, Palma, Spain, 2/07/18. https://doi.org/10.21125/edulearn.2018.1905

    Dynamic game adaptation based on detection of behavioral patterns in the player learning curve. / Vassileva, D.; Bontchev, B.

    Proceedings of the 10th Annual International Conference on Education and New Learning Technologies: EDULEARN2018. Palma de Mallorca : IATED Academy, 2018. p. 8182-8191.

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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    AB - In educational serious games, the learning curve of a player represents his/her progress in acquiring cognitive abilities and new knowledge necessary for solving the game challenges. Hence, it is very important for an adaptive serious game to have a mechanism for detection of patterns of player´s learning curve in playing time. The paper presents the application of a game adaptation method based on automatic and dynamically detection of specific learning curves at runtime within a 3D video game of car driving in various weather conditions. The method uses a client-side software component called “Player-centric rule-and-pattern-based adaptation asset” and developed within the scope of the RAGE (Realising and Applied Gaming Ecosystem) H2020 project. The component is incorporated into a 3D car driving video game in order to enable a dynamic detection of different patterns of player performance. It allows the video game scenario to be adapted to each player by providing appropriately for him/her challenges and game features. We carried out a practical experiment with students from Sofia University, Bulgaria, where we found that adaptation of game difficulty by applying the RAGE software component resulted to improved game playability.

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    Vassileva D, Bontchev B. Dynamic game adaptation based on detection of behavioral patterns in the player learning curve. In Proceedings of the 10th Annual International Conference on Education and New Learning Technologies: EDULEARN2018. Palma de Mallorca: IATED Academy. 2018. p. 8182-8191 https://doi.org/10.21125/edulearn.2018.1905