Use of university students' educational data for learning analytics has spurred a debate about whether and how to provide students with agency regarding data collection and use. A concern is that students opting out of learning analytics may skew predictive models, in particular if certain student populations disproportionately opt out and biases…

The purpose of this study is to review journal papers on educational big data research published from 2010 to 2018. A total of 143 papers were selected. The papers were characterized based on three dimensions: (a) educational goals; (b) educational problems addressed; and (c) big data analytical techniques used. A qualitative content analysis…

The rapid development of big data technology has attracted a variety of sectors, including tertiary education. The purpose of this paper is to construct a precision teaching mode based on big data technology in order to improve teaching quality and further promote education and teaching reform. The proposed mode, based on the theory of precision…

A fixed learning path for all learners is a major drawback of virtual learning systems. An online learning path recommendation system has the advantage of offering flexibility to select appropriate learning content. Learning Analytics Intervention (LAI) provides several educational benefits, particularly for low-performing students. Researchers…

With this 2022 data and analytics edition, EDUCAUSE further expands their series of Horizon Reports to focus on an emerging area of practice that is driving institutional decision-making and strategic planning for the future--the trends, technologies, and practices that are shaping the world of postsecondary data and analytics. Based on a…

Many educational institutions lack well-defined, targeted policies to address problems relating to student smartphone use on campus. In this study, we analyse the patterns of student smartphone use on academic campuses and propose a range of policy measures to address the problems arising from such use. Our research, which draws on primary data…

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…

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…

Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…

The future of university learning in Sub-Saharan Africa has become increasingly digitally transformed by both e-Learning, and learning analytics, post-COVID-19 pandemic. Learning analytics intervention is critical for effective support of socially-shared regulated learning skills, which are crucial for twenty-first-century e-Learners.…

Monitoring students' academic progress is vital for ensuring timely completion of their studies and supporting at-risk students. Educational Data Mining (EDM) utilizes machine learning and feature selection to gain insights into student performance. However, many feature selection algorithms lack performance forecasting systems, limiting their…

The quality of the data and the amount of correct information available is key to informed decision-making. Higher education institutions (HEIs) often employ various decision support systems (DSSs) to make better choices. However, there is a lack of systems to assist with decision-making to promote innovation in teaching and learning. In this…

Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…

Scholarly interests in developing personalized learning analytics dashboards (LADs) in universities have been increasing. LADs are data visualization tools for both teachers and learners that allow them to support student success and improve teaching and learning. In most LADs, however, a teacher-centric, institutional view drives their designs,…

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…