Academic grades in assessments are predicted to determine if a student is at risk of failing a course. Sequential models or graph neural networks that have been employed for grade prediction do not consider relationships between course descriptions. We propose the use of text mining to extract semantic, syntactic, and frequency-based features from…

Purpose: This study aims to uncover divergent collaboration in makerspaces using social network analysis to examine ongoing social relations and sequential data pattern mining to invesitgate temporal changes in social activities. Design/methodology/approach: While there is a significant body of qualitative work on makerspaces, there is a lack of…

With national graduation rates that range from 32% among open enrollment institutions to 66% among private not-for-profits, higher education institutions have a moral imperative to improve the success of their students. Interventions to support today's students must consider the student holistically, be just-in-time, and come from a…

This study presents an advanced predictive learning analytics system, OU Analyse (OUA), and evidence from its evaluation with online teachers at a distance learning university. OUA is a predictive system that uses machine learning methods for the early identification of students at risk of not submitting (or failing) their next assignment.…

This study compared student engagement and performance in both open educational resources (OER) (n[open textbook users fall 2018] = 72) and traditional textbook (n[traditional textbook users fall 2017] = 66) classes. Data were drawn from the Learning Management System (LMS). Results show (1) final grades in the OER class were on a par with the…

"Disrupting Disruption" shows how three racially and ethnically diverse school districts--Union NJ, Union City OK, and Roanoke City VA--have defied the demographic odds, boosting overall graduation rates while shrinking or eliminating the opportunity gap. These districts resemble many others in their student population. What makes them…

This experimental research study examined the effects of using a mobile learning environment (MLE) that provided scaffolded assistive tutoring on student achievement in a Circuit Analysis (Network Theory) course. It also aimed to examine the relationships between students' user learning analytics and their learning outcomes. The design and…

Small private online courses (SPOCs) have influenced teaching and learning in China's higher education. Learning management systems (LMSs) are important components in SPOCs. They can collect various data related to student behavior and support pedagogical interventions. This research used feature engineering and nearest neighbor smoothing models…

This study investigated how English learners complete multimodal formative quizzes. Participants included 17,950 students enrolled in a mandatory English for Academic Purposes course at a university in Hong Kong. We retrieved data from Blackboard, a learning management system, and conducted a two-step cluster analysis to examine student…

The Powered by Publics (PxP) initiative has been an ambitious undertaking from the beginning, aiming to produce hundreds of thousands more undergraduate degrees and halving equity gaps for low-income, minoritized, and first-generation students by 2025. APLU has collected student performance data from the 127 participating institutions over the…

In this study, we present a case study involving two self-service dashboards providing feedback on learning and study skills and on academic achievement. These dashboards were offered to first-year university students in several study programmes in Flanders, Belgium. Data for this study were collected using usage tracking (N = 2875) and a survey…

Assessment and learning analytics both collect, analyse and use student data, albeit different types of data and to some extent, for various purposes. Based on the data collected and analysed, learning analytics allow for decisions to be made not only with regard to evaluating progress in achieving learning outcomes but also evaluative judgments…

Objective: This study examined the effects of offering proactive student-success coaching, informed by predictive analytics, on student academic performance and persistence. Specifically, this study investigated semester grade point average (GPA) and semester-to-semester persistence of community college students as outcomes. Methods: This study…

This study examined the incremental validity of different information and communication technologies (ICT)-related person characteristics over and above intelligence and and prior achievement when predicting ICT literacy across a period of three years. Relative weights analyses were performed to determine the relative contribution of each…

By collecting longitudinal learner and learning data from a range of resources, predictive learning analytics (PLA) are used to identify learners who may not complete a course, typically described as being at risk. Mixed effects are observed as to how teachers perceive, use, and interpret PLA data, necessitating further research in this direction.…