Work in progress: Data explorer - Assessment data integration, analytics, and visualization for STEM education research

Abstract

We describe a comprehensive system for comparative evaluation of uploaded and preprocessed data in physics education research with applicability to standardized assessments for discipline-based education research, especially in science, technology, mathematics, and engineering. Views are provided for inspection of aggregate statistics about student scores, comparison over time within one course, or comparison across multiple years. The design of this system includes a search facility for retrieving anonymized data from classes similar to the uploader's own. These visualizations include tracking of student performance on a range of standardized assessments. These assessments can be viewed as pre- and post-tests with comparative statistics (e.g., normalized gain), decomposed by answer in the case of multiple-choice questions, and manipulated using pre-specified data transformations such as aggregation and refinement (drill down and roll up). Furthermore, the system is designed to incorporate a scalable framework for machine learning-based analytics, including clustering and similarity-based retrieval, time series prediction, and probabilistic reasoning. © American Society for Engineering Education, 2016.