Adaptation and Assessment (TwoA) asset in C# (v1.2)

Enkhbold Nyamsuren

Research output: Non-textual formSoftwareAcademic

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Abstract

Developed within the RAGE project funded by EU within Horizon2020 program. This asset enables a real-time automatic adaptation of game difficulty to player's expertise level. The adaptation algorithm makes use of a stealth assessment algorithm that assigns difficulty ratings and expertise ratings to the players and the game modules respectively. The asset tracks changes in these ratings allowing assessment of players' learning progress either by players themselves or by instructors. This is the version written in C# language. Version 1.2 includes considerable extensions to the TwoA functionalities: • API for building scenario dependency graphs • An improved scenario selection algorithm • The second module for adaptation and assessment based on continuous accuracy only • Extended parameter setting API
Original languageEnglish
Place of PublicationHeerlen
PublisherOpen Universiteit Nederland
Publication statusPublished - 23 Mar 2017

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Application programming interfaces (API)

Keywords

  • automatic game adaptation
  • stealth assessment
  • adaptation algorithm
  • RAGE

Cite this

Nyamsuren, E. (Author). (2017). Adaptation and Assessment (TwoA) asset in C# (v1.2). Software, Heerlen: Open Universiteit Nederland. Retrieved from https://github.com/rageappliedgame/HatAsset/tree/1b9b82c777ac48d97bdb8868f1488819d6bb5d52
Nyamsuren, Enkhbold (Author). / Adaptation and Assessment (TwoA) asset in C# (v1.2). [Software].
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abstract = "Developed within the RAGE project funded by EU within Horizon2020 program. This asset enables a real-time automatic adaptation of game difficulty to player's expertise level. The adaptation algorithm makes use of a stealth assessment algorithm that assigns difficulty ratings and expertise ratings to the players and the game modules respectively. The asset tracks changes in these ratings allowing assessment of players' learning progress either by players themselves or by instructors. This is the version written in C# language. Version 1.2 includes considerable extensions to the TwoA functionalities: • API for building scenario dependency graphs • An improved scenario selection algorithm • The second module for adaptation and assessment based on continuous accuracy only • Extended parameter setting API",
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Nyamsuren, E, Adaptation and Assessment (TwoA) asset in C# (v1.2), 2017, Software, Open Universiteit Nederland, Heerlen.
Adaptation and Assessment (TwoA) asset in C# (v1.2). Nyamsuren, Enkhbold (Author). 2017. Heerlen : Open Universiteit Nederland.

Research output: Non-textual formSoftwareAcademic

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T1 - Adaptation and Assessment (TwoA) asset in C# (v1.2)

AU - Nyamsuren, Enkhbold

PY - 2017/3/23

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AB - Developed within the RAGE project funded by EU within Horizon2020 program. This asset enables a real-time automatic adaptation of game difficulty to player's expertise level. The adaptation algorithm makes use of a stealth assessment algorithm that assigns difficulty ratings and expertise ratings to the players and the game modules respectively. The asset tracks changes in these ratings allowing assessment of players' learning progress either by players themselves or by instructors. This is the version written in C# language. Version 1.2 includes considerable extensions to the TwoA functionalities: • API for building scenario dependency graphs • An improved scenario selection algorithm • The second module for adaptation and assessment based on continuous accuracy only • Extended parameter setting API

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KW - stealth assessment

KW - adaptation algorithm

KW - RAGE

M3 - Software

PB - Open Universiteit Nederland

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Nyamsuren E (Author). Adaptation and Assessment (TwoA) asset in C# (v1.2) Heerlen: Open Universiteit Nederland. 2017.