Effects on Training a Naval Spatial Task
Periscope Operator Adaptive Trainer Leaderboard Screenshot 
The Periscope Operator Adaptive Trainer (POAT) is a computer-simulated periscope adaptive trainer, which focuses on the spatial task of calling angle on the bow. To test whether game features can improve adaptive training, we created a new version of POAT that includes games features: leaderboard, score, and performance gauges.
My role: Co-Principal Investigator
- Conducted experiments with university students and military end-users at the Submarine Officer Basic Course
- Developed research questions and experimental design to determine the efficacy of game features on learning from an adaptive computer-based simulation
- Co-authored a book chapter on the types of instructional feedback in serious games
- Bug tested extensively a modified build of POAT to train periscope operations (e.g., angle on the bow, range)
- Led statistical data analyses (Mixed Effects ANOVA and Regression) and interpreted results for publication
- Completed documents for the Institutional Review Board (IRB)
2016 - Best Paper in Training at the Interservice/Industry Training, Simulation and Education Conference
Johnson, C.I., Bailey, S.K.T., & Van Buskirk, W.L. (2017). Designing effective feedback messages in serious games and simulations: A research review. In P. Wouters & H. van Oostendorp (Eds.), Techniques to Improve the Effectiveness of Serious Games. Switzerland: Springer International Publishing.
Landsberg, C.R., Bailey, S.K.T., Van Buskirk, W.L., Gonzalez-Holland, E., & Johnson, C.I. (2016). Designing effective feedback in adaptive training systems. Proceedings of the Interservice/Industry Training, Simulation and Education Conference. *Best Paper in Training