Immersive Games and Expert-Novice Differences

  • Amanda J. H. Bond
  • Jay Brimstin
  • Angela Carpenter
Conference paper

DOI: 10.1007/978-3-319-42070-7_65

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 498)
Cite this paper as:
Bond A.J.H., Brimstin J., Carpenter A. (2017) Immersive Games and Expert-Novice Differences. In: Kantola J., Barath T., Nazir S., Andre T. (eds) Advances in Human Factors, Business Management, Training and Education. Advances in Intelligent Systems and Computing, vol 498. Springer, Cham

Abstract

Immersive game-based training has been used effectively for years to train within numerous domains. Immersive simulations and games, however, are frequently used to train at the pinnacle of instruction, though research shows that game- and simulation-based training platforms are consistently more effective than traditional training across all phases of instruction. Game-based training has potentially limitless variables on which training can be adapted: troops can change efficacy, weather can turn and equipment can malfunction. Understanding the relationships between adaptive variables is key to effective game design that distinguishes expert and novice performers for assessment. This paper describes the development of a simulation-based game using distributed concept maps for expertise categorization. The expert models were incorporated into a real-time strategy game intended for use to train and assess understanding of and adherence to Army doctrine. Preliminary validation data are also presented comparing the game to traditional Interactive Multimedia Instruction (IMI) courseware.

Keywords

Serious games Expert-novice differences Adaptive training Scenario-based training 

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Amanda J. H. Bond
    • 1
  • Jay Brimstin
    • 2
  • Angela Carpenter
    • 1
  1. 1.Cubic Global DefenseOrlandoUSA
  2. 2.Maneuver Center of ExcellenceFort BenningUSA

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