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


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
Number of pages10
ISBN (Print)9783030921811
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


Conference10th International Conference on Games and Learning Alliance, GALA 2021
CityVirtual, Online


  • 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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