Adaptation and Assessment (TwoA) asset in C# (v1.1)

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.
Original languageEnglish
Publication statusPublished - 17 Mar 2016

Keywords

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

Cite this

Nyamsuren, E. (Author). (2016). Adaptation and Assessment (TwoA) asset in C# (v1.1). Software
Nyamsuren, Enkhbold (Author). / Adaptation and Assessment (TwoA) asset in C# (v1.1). [Software].
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keywords = "automatic game adaptation, stealth assessment, adaptation algorithm, RAGE",
author = "Enkhbold Nyamsuren",
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Adaptation and Assessment (TwoA) asset in C# (v1.1). Nyamsuren, Enkhbold (Author). 2016.

Research output: Non-textual formSoftwareAcademic

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PY - 2016/3/17

Y1 - 2016/3/17

N2 - 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.

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.

KW - automatic game adaptation

KW - stealth assessment

KW - adaptation algorithm

KW - RAGE

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