Research Initiation: Advanced Modeling of Metacognitive Problem Solving and Group Effectiveness in Collaborative Engineering Teams

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Most engineering professionals acquire their technical skills through academic curricula. However, in order to succeed in fulfilling the missions of their professions, graduating engineers require a broader set of professional skills. Problem-solving, metacognitive awareness, teamwork, and mindsets supporting sustainability are 21st century skills that help engineers solve complex problems. These professional skills also allow engineers to work effectively in collaborative teams. This project aims to investigate how engineering students develop their professional skills and provide an approach for measuring and quantifying these skills. Undergraduate engineering students will work individually and in groups to solve real-life manufacturing problems while their professional skills are assessed and enhanced. In order to optimize team performance, the conflicts and errors that occur during the problem solving process will be minimized. By acquiring these skills, engineering students will become effective problem solvers and will be prepared to address complex problems in their work environment. Extensive academic and industry dissemination and outreach will be used to bolster the broader impact of project findings.This initiative will develop a new integrated approach to understanding professional skills in the engineering student population and determine if students are attending to the correct elements while solving engineering problems, both in individual and group settings. Physical simulations and virtual reality testbeds will be used to study metacognitive problem-solving and group effectiveness in collaborative teams. The testbeds will help to pinpoint what the students are paying attention to during the learning process as the low-level attention is measured through eye-tracking and application of psychological theories of learning and attention. The project will then develop analytical models to optimize team performance. The analytical models will combine conflict & error algorithms and statistical modeling methods to describe this learning process and identify where improvements can be made. The models will provide valuable insights into the metacognitive decision-making process. By studying eye movements (using eye-tracking), a deeper understanding of metacognition and factors affecting it can be achieved. Because eye movements are indicative of attention, this will allow determination of what information is being attended to, and ultimately processed, by students engaged in the process. By comparing physical simulations with virtual reality environments, this research will provide insights into the applicability of virtual reality technologies in the education domain. Research activities will be integrated into undergraduate courses to support problem-solving skill development. The research will contribute to the economic growth and security of our nation by enhancing the well-being, innovation, and creative problem-solving skills of undergraduate engineering students. This in turn will positively impact our society, academic environment, as well as manufacturing, service and healthcare industries.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.