Validity of a Content Agnostic Game Based Stealth Assessment

Vipin Verma, Ashish Amresh, Scotty D. Craig, Ajay Bansal

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

Abstract

In an attempt to predict the learning of a player during a content agnostic educational video game session, this study used a dynamic bayesian network in which participants’ game play interactions were continuously recorded. Their actions were captured and used to make real-time inferences of the learning performance using a dynamic bayesian network. The predicted learning was then correlated with the post-test scores to establish the validity of assessment. The assessment was moderately positively correlated with the post-test scores demonstrating support for its validity.

Original languageEnglish (US)
Title of host publicationGames and Learning Alliance - 10th International Conference, GALA 2021, Proceedings
EditorsFrancesca de Rosa, Iza Marfisi Schottman, Jannicke Baalsrud Hauge, Francesco Bellotti, Pierpaolo Dondio, Margarida Romero
PublisherSpringer Science and Business Media Deutschland GmbH
Pages121-130
Number of pages10
ISBN (Print)9783030921811
DOIs
StatePublished - 2021
Externally publishedYes
Event10th International Conference on Games and Learning Alliance, GALA 2021 - Virtual, Online
Duration: Dec 1 2021Dec 2 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13134 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Games and Learning Alliance, GALA 2021
CityVirtual, Online
Period12/1/2112/2/21

Keywords

  • Dynamic bayesian network
  • Educational games
  • Game based assessment
  • Sensor-free
  • Stealth assessment

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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