Assessing student mastery is often done by using exams. Inevitably, some students will complete remediation, which may include exam retakes. This method provides students an additional opportunity to take an exam that assesses the same objectives as the original exam, while using different questions. Although this form of remediation increases…

The progressive move of higher education institutions (HEIs) towards blended and online environments, accelerated by COVID-19, and their access to a greater variety of student data has heightened the need for ethical learning analytics (LA). This need is particularly salient in light of a lack of comprehensive, evidence-based guidelines on ethics…

As online learning platforms and computerized testing become more common, an increasing amount of data are collected about users. These data include, but are not limited to, response time, keystroke logs, and raw text. The desire to observe these features of the response process reflect an underlying interest in the cognitive processes and…

The prediction of physical ability is a key point to understand the physical training effect of college students. This paper uses the error Back Propagation neural network algorithms to investigate the college students' physical test results, and predicts the future trends of the results. The findings indicate that, in future ten years, the…

Student mobility that occurs within a school year may be especially disruptive for student outcomes, yet little is known regarding the predictors of within-year mobility. In particular, research has yet to comprehensively examine the role of student achievement in predicting within-year student mobility. Thus, we sought to understand this link by…

Several daily phenomena around us can be modeled as time-evolving networks. Working with expressive and tractable models for the evolution of such networks can improve different prediction and decision-making tasks. While the literature has studied many approaches to model such networked phenomena partially, multiple gaps remain. This thesis is an…

The "surprisingly popular" method (SP) of aggregating individual judgments has shown promise in overcoming a weakness of other crowdsourcing methods--situations in which the majority is incorrect. This method relies on participants' estimates of other participants' judgments; when an option is chosen more often than the average…

This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…

Purpose: Anomia, or word-finding difficulty, is a prevalent and persistent feature of aphasia, a neurogenic language disorder affecting millions of people in the United States. Anomia assessments are essential for measuring performance and monitoring outcomes in clinical settings. This study aims to evaluate the reliability of response time (RT)…

Can genetic screening be used to personalize education for students? Genome-wide association studies (GWAS) screen an individual's DNA for specific variations in their genome, and how said variations relate to specific traits. The variations can then be assigned a corresponding weight and summed to produce polygenic scores (PGS) for given traits.…

Test development is a complicated process that demands examining various factors, one of them being writing items of varying difficulty. It is important to use items of a different range of difficulty to ensure that the test results accurately indicate the test-taker's abilities. Therefore, the factors affecting item difficulty should be defined,…

This article provides evidence about predictive relationships between features of community college interventions and their impacts on student progress. This evidence is based on analyses of student-level data from large-scale randomized trials of 39 (mostly) community college interventions. Specifically, the evidence consistently indicates that…

Background: Technological innovations such as Learning Management Systems (LMS) are becoming more and more prevalent in the learning environments of students. Distilling and acting on knowledge gathered from these systems, the field known as learning analytics, allows educators to hone their craft and support students more effectively by providing…

The construction of prediction models reflecting players' learning performance in serious games currently faces various challenges for learning analytics. In this study, we design, implement, and field test a learning analytics system for a serious game, advancing the field by explicitly showing which in-game features correspond to differences in…

Purpose: We investigated the finite verb morphology composite (FVMC), a measure associated with developmental language disorder (DLD), in a large community sample to provide evidence on its distribution, its association with other variables, and its sensitivity and specificity. Method: We coded percent occurrence of FVMC morphemes in obligatory…