Analyzing and predicting player performance in a quantum cryptography serious game

Dilanga Abeyrathna, Srikanth Vadla, Vidya Bommanapally, Mahadevan Subramaniam, Parvathi Chundi, Abhishek Parakh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

An adaptive 3D serious game, QuaSim for imparting to learners the fundamental concepts of quantum cryptography and their applications in designing computer security protocols is described. QuaSim emulates an often used instructional model of practice exercises followed by timed-tests (practice-timed-test) in a serious game setting by automatically designing timed-tests guided by models learned from data about the performance of players in practice exercises. QuaSim also automatically selects next practice exercises based on player performance in previous exercises. The game was played by 150 students and the results are highly encouraging. They show that the model learned by the game is able to select next practice exercises to improve player performance in the timed tests and is able to generate meaningful timed-tests.

Original languageEnglish (US)
Title of host publicationGames and Learning Alliance - 7th International Conference, GALA 2018, Proceedings
EditorsHeinrich Söbke, Manuel Gentile, Mario Allegra
PublisherSpringer Verlag
Pages267-276
Number of pages10
ISBN (Print)9783030115470
DOIs
StatePublished - 2019
Event7th International Conference on Games and Learning Alliance, GALA 2018 - Palermo, Italy
Duration: Dec 5 2018Dec 7 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11385 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Games and Learning Alliance, GALA 2018
Country/TerritoryItaly
CityPalermo
Period12/5/1812/7/18

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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