This paper introduces AMMORE, a new dataset of 53,000 math open-response question-answer pairs from Rori, a mathematics learning platform used by middle and high school students in several African countries. Using this dataset, we conducted two experiments to evaluate the use of large language models (LLM) for grading particularly challenging…

Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…

This paper addresses dynamical interdependence among the actions of group members. I assume that the actions of each member can be represented as nodes of a dynamical network and then collect the nodes into disjoint subsets (components) representing the individual group members. Interdependence among group members' actions can then be defined with…

Due to the COVID-19 restrictions, high-schools in Spain are having both online and in-class lectures. As a result, the students can use not only the information provided by the teachers in class, but they can also use several other methods such as videos and online examples that allow the students to have materials from different places. In this…

The current project, Exploring Math Education Relations by Analyzing Large Data Sets (EMERALDS) II, is an attempt to identify specific Common Core State Standards procedural, conceptual, and problem-solving competencies in earlier grades that best predict success in algebraic areas in later grades. The data for this study include two cohorts of…