2023 ASEE Annual Conference & Exposition

Board 324: Intelligently Preparing the Future Construction Engineering Workforce by Connecting the Professional and Educational Communities

Presented at NSF Grantees Poster Session

The purpose of this project is to investigate how the development of a framework for Connecting the Professional and Educational Communities (ConPEC). This is aimed at improving the accessibility of construction industry practitioners to instructors, so as to ensure greater interaction of students with their communities of practice (COP). This improved interaction is targeted at enhancing the disciplinary perception and professional identity development of construction engineering students by inducting them into experts’ ways of thinking, knowing, and reasoning. The ConPEC framework will provide instructors with equitable access to the construction COP by intelligently matching the practical course support needs of instructors with the offerings of industry practitioners. The practice knowledge gaps in construction engineering education would be addressed by increasing access to industry practitioners to bridge the gaps. The framework is ideally suited for creating this learning environment as it consists of platforms and layers that allow for advanced searches using machine learning algorithms as well as complex data analysis.

The first stage of this project consists of surveys being administered to industry practitioners and instructors in construction-related programs. The surveys seek to investigate the information requirements that must be accessible on a graphical user interface of the ConPEC platform for equitable matching of instructors with industry practitioners to provide practical support for courses. Focus group discussions will be conducted to validate the outcomes of the surveys. Preliminary results will be reported in this paper. Thereafter, the early version of the ConPEC platform will be designed, developed, and deployed. By combining tools from machine learning and matching theory, this project would also develop a learning-driven matching algorithm by learning users’ (instructor and industry practitioners) needs, requirements, offerings, and preferences to support optimal and equitable matching of construction engineering instructors and industry practitioners.
The project will as well determine users’ learning-driven preferences and develop many-to-many matching algorithms. The ConPEC platform will be subjected to evaluation by users and the matching algorithms will be improved to ensure enhanced equitable matching. The project will as well investigate the influence of the ConPEC platform on students’ disciplined perception and professional identity development. Substantive theories would be developed to explain how improved accessibility, enabled by the ConPEC framework, improves the disciplined perception and professional identity development of construction engineering students.
In addition to improved accessibility to construction COP, this project would contribute to the diversity of the nation’s construction workforce and strengthen diverse forms of industry-academia interactions. Also, the platform, developed theories and algorithms, can be adapted by high schools, community colleges, and researchers to develop other technological solutions to enhance the development of students in various disciplines. The deployment of ConPEC will also produce diverse datasets for engineering education researchers, institutions, and policymakers. These data include concentration areas, current and future directions of the industry, and the extent to which institutions are preparing students to meet the demands of the industry. ConPEC will also facilitate the supply chain of industries through apprenticeship programs and talent pipelines that currently are fragmented.

Authors
  1. Andres Nieto Leal Virginia Polytechnic Institute and State University
  2. Dr. Abiola Akanmu Virginia Tech
  3. Sheryl Ball Virginia Polytechnic Institute and State University [biography]
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