Lorimer, ShelleyDavis, Jeffrey A.2022-10-282022-10-282021Davis, J.A, & Lorimer, S.A. (2021) Development of large scale STEM problem databases for student learning and assessment tools. Proceedings of the Canadian Engineering Education Association (CEEA). https://doi.org/10.24908/pceea.vi0.14830https://hdl.handle.net/20.500.14078/2850Presented on June 21-23, 2021, at the "Canadian Engineering Education Association (CEEA-ACEG) Conference" held at the University of Prince Edward Island in Charlottetown, Prince Edward Island.Problem databases in STEM courses are used in tools for the development of student learning and final assessment. In addition, large problem databases are used to develop models for automatic assessment and feedback of students’ work. However, the availability of large, open source, problem databases for specific courses is limited, and in-house development of a wide variety of problems can take years. In this paper, the framework for a problem database in STEM courses was created using semantic analysis of sentence structure and composition. Problem statements were analyzed to determine the key grammatical constructs that are used in commonly posed problems. Based on this analysis, software was developed to create large problem databases which allow for simple extension to other courses. Using a first-year mechanics course this software was populated with a few generalized questions and sentence structures to create a large problem database.enAll Rights Reservedlarge problem databasesproblem statementsPresentationhttps://doi.org/10.24908/pceea.vi0.14830