RET Site: Artificial Intelligence and Machine Learning Approach for Sustainable and Resilient Infrastructure in Urban Communities

This Research Experiences for Teachers (RET) Site will work with eight school districts (ISDs) in the Dallas-Fort Worth (DFW) metropolitan area, Arlington, Duncanville, Everman, Fort Worth, Grand Prairie, Irving, Kennedale, and Mansfield. The main sub-fields of the research are artificial intelligence (AI), machine learning (ML), infrastructure sustainability and resiliency, engineering (civil, industrial, electrical, mechanical), project evaluation, and STEM education. Nine high school STEM teachers from the ISDs will partner with faculty mentors, graduate students, academic/industrial mentors, and prior RET teachers during 6-week summer programs over three years. Through four related and concurrent summer RET projects, knowledge will be advanced within and across engineering disciplines, education/assessment, and unique challenges of sustainable and resilient urban infrastructure, by finding solutions for critical issues through advanced AL/ML approach. This is important with the deteriorating infrastructure, its widespread failures and extensive human, economic and societal effects, the increasing potential of AL/ML for infrastructure improvement, increased worldwide occurrence of hazards, and the important need for economic and environmental conservation in urban settings, such as in DFW, with a population of 8.5 million. Through engaging teachers in summer research activities and providing support to transfer their research to course curricula, they will develop increased capabilities in integrating engineering topics into their courses. The experience will provide them with innovative ways to address state education standards. Supporting them to share their work with non-participant teachers through workshops and conferences will bolster their professional development by enhancing their ability to effectively communicate their research. Most of the participating ISDs have low Texas Education Agency (TEA) ratings. Equipping teachers to tailor their curriculum to the AI/ML based solutions of real-world engineering problems will improve students’ engagement and interest in engineering education/careers. The RET Site will improve: (1) teachers’ perceptions of engineering and ability to incorporate engineering topics into their courses, especially with AI/ML application; (2) students’ perceptions of and interest in STEM majors and careers; and (3) mutually beneficial partnerships with ISDs involved in the project. The project builds upon two previous successful RET projects at UT Arlington, and will provide in-service high school teachers, primarily from inner city and other high-needs schools, with stipends/support for engagement in research with the mentor groups. Teacher’s summer activities will include curricular module development, workshops, webinars, mentoring, and site visits. Follow-up during the academic year will include a workshop to share developed modules with non-RET teachers, classroom visitations, evaluation, and dissemination. An external evaluator will perform formative/summative process and outcome evaluation. The project will efficiently integrate research and education. Teachers will be immersed in innovative research under expert mentoring, field trips, presentations, workshops, and intellectual collaboration. Addressing probing and original research questions for each project will enable teachers to find reliable data-driven transformative solutions with potential for practical applications. Equipping teachers to employ universal design for learning in their teaching and assessments will improve opportunities for all students. The societal benefits of sustainable and resilient infrastructure are expected to bolster infrastructure improvement, considering the nation’s failing infrastructure and challenges in recovering from disasters (hurricanes, floods, wildfires, among others). The project will enhance long-term collaboration among teachers, faculty/students, and industrial mentors. Inherent in the research projects are strong societal impacts with improved public safety, health, and welfare associated with improved infrastructure. 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.