Augmenting Instructional Design with State-Based Assessment

  • Kevin Oden
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8027)


The Trainee Engagement Management System (TEMS) is a technology—enabled instructional design concept that leverages state-based assessment techniques to improve training processes and outcomes. Specifically, the concept is designed to support military instructors in the delivery of empirically-supported instructional prompts to foster trainee engagement within a Computer Based Training (CBT) environment. The central theme of the concept is to augment, not replace, an instructor’s abilities. By reducing workload demands on an instructor, the approach enables the delivery of personalized instruction in a one (instructor) to many (trainees) context. The TEMS concept embraces a human-system philosophy and is designed to mitigate risks typically associated with the transition of advanced technologies and concepts to field settings. In this paper we discuss those challenges and describe the basic TEMS architecture.


Instructional System Design Augmented Cognition Human Systems Computer Based Training 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Yerkes, R.M., Dodson, J.D.: The Relation of Strength of Stimulus to Rapidity of Habit-formation. Journal of Comparative Neurology and Psychology 18, 459–482 (1908), CrossRefGoogle Scholar
  2. 2.
    Vygotsky, L.S., Whorf, B.L., Wittgenstein, L., Fromm, E.: Language and Consciousness. In: Pickering, John, Skinner, Martin (eds.) From Sentience to Symbols: Readings on Consciousness, Harvester Wheatsheaf (1990)Google Scholar
  3. 3.
    Hancock, P.A., Warm, J.S.: A Dynamic Model of Stress and Sustained Attention. Human Factors 31(5), 519–537 (1989)Google Scholar
  4. 4.
    Csikszentmihalyi, M.: Flow: The Psychology of Optimal Experience. Harper Perennial, New York (1991)Google Scholar
  5. 5.
    Paas, F., van Gog, T.: Principles for Designing Effective and Efficient Training of Complex Cognitive Skills (2009), doi:10.1518/155723409X448053Google Scholar
  6. 6.
    Craven, P.L., Tremoulet, P.D., Barton, J.H., Tourville, S.J., Dahan-Marks, Y.: Evaluating training with cognitive state sensing technology. In: Schmorrow, D.D., Estabrooke, I.V., Grootjen, M. (eds.) Augmented Cognition, HCII 2009. LNCS, vol. 5638, pp. 585–594. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  7. 7.
    Blackhurst, J.L., Gresham, J.S., Stone, M.O.: The Quantified Warrior. Armed Forces Journal (2012), (retrieved)
  8. 8.
    Vogel-Walcutt, J.J., Bowers, C.A., Marino-Carper, T., Nicholson, D.: Increasing Learning Efficiency in Military Learning: Combining Efficiency and Deep Learning Theories. Military Psychology (2010)Google Scholar
  9. 9.
    Brown, A.: Metacognition, Executive Control, Self-Regulation, and Other more Mysterious Mechanisms. In: Reiner, F., Kluwe, R. (eds.) Metacognition, Motivation, and Understanding, pp. 65–116. Erlbaum, Hillsdale (1987)Google Scholar
  10. 10.
    Lackey, S.: Next-Generation Expeditionary Warfare Intelligent Training (NEW-IT) Program Summary Booklet (2011),

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Kevin Oden
    • 1
  1. 1.Lockheed Martin CorporationOrlandoUSA

Personalised recommendations