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CERES: Cognitive Expertise through Repetition-Enhanced Simulation HPT&E Technical Review Decision Making & Expertise Development. Paul J. Reber, Ph.D. Northwestern University Feb 20, 2019. Objective.
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CERES: Cognitive Expertise through Repetition-Enhanced SimulationHPT&E Technical ReviewDecision Making & Expertise Development Paul J. Reber, Ph.D. Northwestern University Feb 20, 2019
Objective • Accelerate the development of expertise in a cognitive skill by training with large numbers of repetitions in simulation-based protocol • Target domain: Reading and understanding topographic maps
Background • Training typically provides very few repetitions of connecting a complex topographic map to the world around the trainee • Rules are explained, instructed in classroom • Expertise developed slowly by experience • Research Foundations: implicit learning depends on practice • Eventually produces automatic, habit-like execution of learned skills • Applications: land navigation, decision-making from topographic features
Overall Approach • Develop map training protocol with naïve NU community participants • Underway • Field test with military personnel • Software testing, SME feedback • NU NROTC personnel • Field testing (e.g., Quantico) • Quantify training benefit on orienteering assessment within Land Navigation training
Training Approach • Procedural content • Random world surfaces • Topographic map/video pairings • STATE software (Charles River Analytics, Neihaus) • Training protocol • Identify facing orientation on map from video • 30s trials with feedback • Repeated experience with map until understood • Assessment approach • Pre/post training, 10 trials no feedback
Map Training • Explicit Training • Pretest • High-repetition Training • Advance to new map when accuracy is high • Increase difficulty of task • Posttest • Questionnaire
Explicit Training Module • ID terrain features with topographic map • Modeled after APACTS (SoarTech) • Learning Objective 10
High-Repetition Map Training Where are you facing on the map? First-person View Topographic Map
Simultaneous Task Module • Maps and videos on screen at same time • Response and Feedback while terrain in view
Sequential Task Module • Map and video presented separately • Must hold terrain info in working memory Study Compare Decide Feedback
Sequential Task Module Study Compare Decide Feedback
Project Technical Progress • Pilot testing (NU community) • 4 rounds, tuned difficulty, refined measurement and assessment approach • Military personnel testing • NU NROTC contact • IRB protocol under review • Portable lab testing resources in place • Software development • Identifying features for improvement • Drone-mapping protocol
Training Data • Explicit Training (~8 minutes) • Simultaneous Task Module • 3-4 terrain decisions per minute (~150 total) • ~10 trials / map on average • Sequential Task Module • 1-2 terrain decisions per minute (~81 total) • ~9 trials / map on average
Participant Questionnaire • Good • “It feels like I got better” • “The interface was easy to use” • “The video feels quite real” • “Easier when map feature was seen multiple times” • Bad • “Sometimes the video didn’t give enough signals of where I was at” • “Hard to tell distance” • “Difficult to tell hills from valleys”
Bad Maps/Videos • “Sometimes the video didn’t give enough signals of where I was at” • “Difficult to tell hills from valleys”
Issues and Opportunities • Issue: Map quality • Artificial topo surfaces are difficult to understand, not particularly realistic • Course of action: software improvement to enhance procedural content generation, integration of real-world maps via drone • Opportunities for collaboration • Ongoing Land Navigation training development, decision-making based on topographic map features
Way Forward • Continuing pilot data collection (NU) • Extending training to multiple hours • Improving all stimuli • Engagement with instructors, trainees • SME feedback • Trainee experience testing • Applied field testing • Pending IRB, protocol stabilization, site selection • Summer 2019
Acknowledgements • Northwestern University • Marcia Grabowecky, Ph.D., Kevin Schmidt, Brooke Feinstein, Ben Reuveni, Catherine Han, Ken Paller, Ph.D., Mark Beeman, Ph.D., Satoru Suzuki, Ph.D. • Captain Adam M. North, USMCMarine Officer Instructor/Assistant Professor of Naval Science, NROTC Chicago Consortium • Charles River Analytics • James Niehaus, Ph.D., Paul Woodall, William Manning
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