Open AccessDEVELOPMENT OF LARGE SCALE STEM PROBLEM DATABASES FOR STUDENT LEARNING AND ASSESSMENT TOOLS
Author(s) -
Jeffrey A. Davis,
Shelley Lorimer
Publication year - 2021
Publication title -
proceedings of the ... ceea conference
Language(s) - English
Resource type - Journals
ISSN - 2371-5243
DOI - 10.24908/pceea.vi0.14830
Subject(s) - computer science , database , sentence , variety (cybernetics) , scale (ratio) , extension (predicate logic) , open source , artificial intelligence , software , programming language , physics , quantum mechanics
Problem databases in STEM courses are used in tools for the development of student learning andfinal 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 specificcourses is limited, and in-house development of a wide variety of problems can take years. In this paper, theframework 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 problemdatabases which allow for simple extension to other courses. Using a first-year mechanics course this softwarewas populated with a few generalized question and sentence structures to create a large problem database.