Congratulations Abiola Akanmu on receiving two new NSF Awards!
February 21, 2023
Abiola Akanmu, Associate Professor in the Myers-Lawson School of Construction, recently received two new awards from the National Science Foundation (NSF) from the program on Innovative Technology Experiences for Students and Teachers (ITEST) and the program on Improving Undergraduate STEM Education: Directorate for STEM Education (IUSE: EDU). The ITEST program supports applied research and development focused on increasing preK-12 students' interest in careers in information and communication technology and STEM through technology-based learning experiences. And the IUSE: EDU program supports projects to improve STEM teaching and learning for undergraduate students, including studying what works and for whom and how to transform institutions to adopt successful practices in STEM education.
As the construction industry gears toward adopting data sensing technologies, there is a demand for creating and sustaining a workforce with skills for implementing the technologies and analyzing the resulting data to support decision-making. It is also essential to improve awareness of this Science, Technology, Engineering, and Mathematics (STEM) career option among all K-12 students, develop their understanding of the applications of data sensing technologies and improve their computational thinking skills in manipulating and using data.
This project aims to investigate an immersive virtual reality-based learning environment for developing middle school students’ computational thinking skills necessary to address construction challenges and improving students’ engagement and attitudes towards STEM-related careers in the construction industry. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers.
This research will develop a DAta Sensing Learning EnvironmenT (called DASLET) to investigate how students’ computational thinking can be developed in addressing construction industry challenges with data sensing technologies and improve their engagement and attitudes toward STEM-related careers. Within DASLET, students can learn how to safely work with different data sensing technologies on a virtual construction site, translate sensor data into computational rules and extract meaningful information to support decision-making.
The research will first develop a virtual reality-based learning environment that can facilitate tangible interaction with data sensing technologies to equip middle school students with skills for addressing construction risks. Next, working closely with middle school teachers, strategies will be developed for adapting applications of data sensing technologies in construction and the proposed learning environment to the middle school curriculum. Using mixed methods and multilevel modeling, the research team will implement DASLET with approximately 40 teachers and 120 students, and develop theories to explain how embodied interaction within the learning environment can enhance students’ computational thinking, improve engagement with data sensing technologies, and interest in data sensing and STEM-related careers in the built environment. The development of DASLET will involve industry practitioners and teachers from diverse groups including females and underrepresented minorities. It will be implemented in the schools and summer camps that serve students from groups that are underrepresented in STEM.
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.
This project aims to serve the national interest by advancing the innovation needed to enhance the work environments for construction workforce interacting with robots. As the construction industry gears towards widespread acceptance of robots, there is a need to prepare Construction Engineering and Management (CEM) students to excel in highly technological work environments. However, the current curriculum is inadequate to equip CEM students with the required competencies for working alongside construction robots.
This project intends to investigate an immersive virtual reality (VR)-based learning environment to develop students' experiential skills so that the students would interact safely with robots in the construction industry after they graduate. The proposed project has the potential to provide the CEM communities with tangible benefits for advancing robotics in engineering education.
This interdisciplinary research seeks to advance the understanding of CEM students' challenges when the students learn how to interact safely with robots during construction work. The project will first identify the key competencies required for CEM students to interact with construction robots. Next, the characteristics of a virtual environment that can enhance those competencies will be investigated.
The immersive VR-based learning environment including an interactive diagnostic will be developed to help students to cultivate the hands-on skills of working with construction robots. The project intends to implement and evaluate the learning environment in terms of learning outcomes and improvement in competencies. In addition, the researchers plan to provide a learning environment adaptable to different student demographics. The Improving Undergraduate STEM Education: Directorate for STEM Education (IUSE: EDU) program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.
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.