Instructional strategies framework for military training systems

MetaCogs: Mitigating Executive Dysfunction via Agent-Based Modeling for Metacognitive Strategy Development

Executive functions (EF) are a collection of cognitive domains governing task initiation, motor planning, attention, and goal-oriented action. Difficulties with EF have marked impacts on adaptive living skills, learning outcomes, and quality of life for people with cognitive and psychosocial disabilities, as well as the broader population. While there is considerable research interest in EF training intervention for disabled populations, very few studies explore metacognitive intervention for people with cognitive disabilities. Metacognition comprises conscious beliefs and strategies around task management and goal setting. Metacognitive awareness has been shown to mediate the effects of executive function on self-regulated learning. Metacognitive interventions have also shown promise in general education, military training, and medical practice. We present a virtual reality experience deploying agent-based modeling to support explicit metacognitive strategy instruction for undergraduate students of all neurotypes. Our results support that explicit instructional material explaining executive function and metacognition in relation to problem-solving experiences influenced participant self-concept and awareness of personal traits and cognitive processes.

The effect of metacognitive monitoring feedback on performance in a computer-based training simulation

This laboratory experiment was designed to study the effect of metacognitive monitoring feedback on performance in a computer-based training simulation. According to prior research on metacognition, the accurate checking of learning is a critical part of improving the quality of human performance. However, only rarely have researchers studied the learning effects of the accurate checking of retrospective confidence judgments (RCJs) during a computer-based military training simulation. In this study, we provided participants feedback screens after they had completed a warning task and identification task in a radar monitoring simulation. There were two groups in this experiment. One group (group A) viewed the feedback screens with the flight path of all target aircraft and the triangular graphs of both RCJ scores and human performance together. The other group (group B) only watched the feedback screens with the flight path of all target aircraft. There was no significant difference in performance improvement between groups A and B for the warning task (Day 1: group A - 0.347, group B - 0.305; Day 2: group A - 0.488, group B - 0.413). However, the identification task yielded a significant difference in performance improvement between these groups (Day 1: group A - 0.174, group B - 0.1555; Day 2: group A - 0.324, group B - 0.199). The results show that debiasing self-judgment of the identification task produces a positive training effect on learners. The findings of this study will be beneficial for designing an advanced instructional strategy in a simulation-based training environment.