Learning analytics are starting to become standardized in higher education as institutions use the techniques of Big Data analytics to make decisions to help them reach their goals. The widespread use of student information brings forth ethical concerns primarily in relation to privacy. While the overarching ethical issues related to learning…

Libraries remain one of the last places on campus where the purging of usage data is encouraged and "tracking" is a dirty word. While some libraries have demonstrated the usefulness of analytics, opponents bring up issues of privacy and debate the feasibility of student-generated library data for planning and assessment. Using a study…

Leveraging big data for student data analytics is increasingly integrated throughout university operations from admissions to advising to teaching and learning. Though the possibilities are exciting to consider, they are not without risks to student autonomy, privacy, equity, and educational value. There has been little research showing how…

Higher education data mining and analytics, like learning analytics, may improve learning experiences and outcomes. However, such practices are rife with student privacy concerns and other ethics issues. It is crucial that student privacy expectations and preferences are considered in the design of educational data analytics. This study forefronts…

This chapter examines the application of learning analytics techniques within higher education -- learning analytics -- and its application in supporting "student success." Learning analytics focuses on the practice of using data about students to inform interventions aimed at improving outcomes (e.g., retention, graduation, and learning…

Digital data are transforming higher education (HE) to be more student-focused and metrics-centred. In the UK, capturing detailed data about students has become a government priority, with an emphasis on using student data to measure, compare and assess university performance. The purpose of this paper is to examine the governmental and commercial…

As institutions of higher education increasingly look to data as evidence to support planning, allocate resources, and inform teaching and pedagogy, ethical considerations regarding learning analytics have evolved from being on the margins to more central in the conversations surrounding institutional uses of student data. After outlining this…

The increasing number of students in higher education has led to the formation of large class teaching and learning environments, which is a threat to quality education. The Department of Fashion Design and Textiles Studies of Kumasi Technical University is one such department that is facing this challenge. Computer-based technology has…

Institutions are applying methods and practices from data analytics under the umbrella term of "learning analytics" to inform instruction, library practices, and institutional research, among other things. This study reports findings from interviews with professional advisors at a public higher education institution. It reports their…

"Trust and Inclusion in AI-Mediated Education: Where Human Learning Meets Learning Machines" is a resource for researchers and practitioners in a field where the mainstreaming of AI technologies, and their increased capacities for deception, have produced confusion and fear. Identifying theoretical frameworks and practices in teaching…

While universities routinely use student data to monitor and predict student performance, there has been limited engagement with student and staff views, social and ethical issues, policy development, and ethical guidance. We reviewed peer-reviewed and grey-literature articles of 2007 to 2018 describing the perspectives of staff and students in…

In this article, Susan Haarman discusses the ways in which datafication technologies such as Big Data and algorithms have the potential to either challenge or exacerbate what Miranda Fricker calls epistemic injustice. She briefly defines epistemic injustice using Fricker's subsets of testimonial and hermeneutical injustice before moving to the…

In this chapter, we explore the contexts within which institutional researchers must try to ensure the ethical use of data. We also identify challenges institutional research professionals can face when navigating college culture while trying to ensure the ethical use of data. Finally, we identify potential solutions for improving institutional…

There are good reasons for higher education institutions to use learning analytics to risk-screen students. Institutions can use learning analytics to better predict which students are at greater risk of dropping out or failing, and use the statistics to treat "risky" students differently. This paper analyses this practice using…

The aim of this paper is to identify and describe the key traits of research with life histories. Previous studies on disability and my own work conducting research with the life histories and university experiences of students with disabilities help to explain how these key characteristics manifest themselves in practice. There are six traits…