To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…

Contribution: A competency assessment framework that enables learning analytics for course monitoring and continuous improvement. Our work fills the gap in systematic methods for competency assessment in higher education. Background: Many institutions are shifting toward competency-based education (CBE), thus encouraging their educators to start…

In this contribution to the Platform Studies in Education symposium, Luci Pangrazio, Amy Stornaiuolo, T. Philip Nichols, Antero Garcia, and Thomas M. Philip explore how digital platforms can be used to build knowledge and understanding of datafication processes among teachers and students. The essay responds to the turn toward data-driven teaching…

Student success, both during and after college, is central to the mission of higher education. Within the higher-education and, more specifically, the student-success context, the core raison d'être of machine learning (ML) is to help institutions achieve their social mission in an efficient and effective manner. While there should be synergy…

The emergence of online learning has sparked increased interest in predicting learners' academic performance to enhance teaching effectiveness and personalized learning. In this context, we propose a complex model APPMLT-CBT which aims to predict learners' performance in online learning settings. This systemic model integrates cognitive, social,…

Postsecondary education is awash in data. Postsecondary institutions track data on students' demographics, academic performance, course-taking, and financial aid, and have put these data to use, applying data analytics and data science to issues in college completion. Meanwhile, an extensive amount of higher education data are being collected…

The purpose of this study is to define learning analytics, to introduce concepts related to learning analytics and to introduce potential study topics related to learning analytics. Today's education model has changed with evolving social and economic conditions over time. This change in education has created such new situations as individualized…

This chapter addresses how IR/IE both responds to and leads in our institutions and across higher education in measuring and improving student success. We introduce a new student success measurement framework in the context of internal and external facing needs, we define the importance of actionable information to inform decision-making, and we…

During the COVID-19 pandemic, an adult noncredit program in the California Community College system partnered with Ease Learning to help convert face-to-face courses to an online modality. Subsequent data revealed a misalignment in the courses' Student Learning Outcomes and Instructional Objectives which became a barrier to student success. Wile's…

Contemporary students have a varied set of needs--the "lifecycle" of a typical student may no longer be 4 years of continuous enrollment between the ages of 18 and 22, and many students bring rich and varied experiences with them to college. As institutions strive to allocate resources in ways that provide the most benefit to student…

"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…

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…

Data collection and analysis is nothing new in computer-assisted language learning, but with the phenomenon of massive sets of human language collected into corpora, and especially integrated into systems driven by artificial intelligence, new opportunities have arisen for language teaching and learning. We are now seeing powerful artificial…

Bay Path University in Massachusetts developed a COVID dashboard and related safety practices enabled by data (Anderson, 2020) during the pandemic. The dashboard has capabilities, in which information technology staff partnered with executive management, human resources staff, health offices, and others to identify key performance indicators…

Due to the fundamental differences between traditional education and massive open online courses (MOOCs), and because of the ever-increasing popularity of the latter, more research is needed to understand current and future trends in MOOCs. Although research in the field has grown rapidly in recent years, one of the main challenges facing…