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…

Multiple-choice questions (MCQs) are widely used in educational assessments and professional certification exams. Managing large repositories of MCQs, however, poses several challenges due to the high volume of questions and the need to maintain their quality and relevance over time. One of these challenges is the presence of questions that…

Research has suggested that changing one's answer on multiple-choice examinations is more likely to lead to positive academic outcomes. This study aimed to further understand the relationship between changing answer selections and item attributes, student performance, and time within a population of 158 first-year medical students enrolled in a…

The digital transformation in educational assessment has led to the proliferation of large-scale data, offering unprecedented opportunities to enhance language learning, and testing through machine learning (ML) techniques. Drawing on the extensive data generated by online English language assessments, this dissertation investigates the efficacy…

Item response theory (IRT) is a popular method to infer student abilities and item difficulties from observed test responses. However, IRT struggles with two challenges: How to map items to skills if multiple skills are present? And how to infer the ability of new students that have not been part of the training data? Inspired by recent advances…

Many university programs include Microsoft Excel courses given their value as a scientific and technical tool. However, evaluating what is effectively learned by students is a challenging task. Considering multiple-choice written exams are a standard evaluation format, this study aimed to uncover the features influencing students' success in…

We study the automatic identification of educational items worthy of content authors' attention. Based on the results of such analysis, content authors can revise and improve the content of learning environments. We provide an overview of item properties relevant to this task, including difficulty and complexity measures, item discrimination, and…

The Internet and the software stores for mobile devices come with a huge number of digital tools for any task, and those intended for digital formative assessment (DFA) have burgeoned exponentially in the last decade. These tools vary in terms of their functionality, pedagogical quality, cost, operating systems and so forth. Teachers and learners…