The focus of ethics in learning analytics (LA) frameworks and guidelines is predominantly on procedural elements of data management and accountability. Another, less represented focus is on the duty to act and LA as a moral practice. Data feminism as a critical theoretical approach to data science practices may offer LA research and practitioners…

Learning analytics dashboard (LAD) development has been criticized for being too data-driven and for developers lacking an understanding of the nontechnical aspects of learning analytics (LA). The ability of developers to address their understanding of learners as well as systematic efforts to involve students in the development process are…

With student and staff wellbeing a growing concern, several authors have asked whether existing data might help institutions provide better support. By analogy with the established field of Learning Analytics, this might involve identifying causes of stress, improving access to information for those who need it, suggesting options, providing rapid…

The anticipation, inclusion, responsiveness, and reflexivity (AIRR) framework (Stilgoe et al., 2013) is a novel framework that has helped those in science and technology fields shift their focus from products to the processes used to create those products. However, the framework has not been known to be applied to the development and…

Data-driven learning analytics (LA) exploits artificial intelligence, data-mining, and emerging technologies, rapidly expanding the collection and uses of learner data. Considerations of potential harm and ethical implications have not kept pace, raising concerns about ethical and privacy issues (Holstein & Doroudi, 2019; Prinsloo & Slade,…

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…

Multimodal learning analytics (MMLA) integrates novel sensing technologies and artificial intelligence algorithms, providing opportunities to enhance student reflection during complex, collaborative learning experiences. Although recent advancements in MMLA have shown its capability to generate insights into diverse learning behaviours across…

Ethics is a prominent topic in learning analytics that has been commented on from conceptual viewpoints. For a broad range of emerging technologies, systematic literature reviews have proven fruitful by pinpointing research directions, knowledge gaps, and future research work guidance. With these outcomes in mind, we conducted a systematic…

Transparency and trustworthiness are among the key requirements for the ethical use of learning analytics (LA) and artificial intelligence (AI) in the context of social inclusion and equity. However, research on these issues pertaining to users is lacking, leaving it unclear as to how transparent and trustworthy current LA tools are for their…

This article systematically reviews the role of learning analytics (LA) in collaborative learning, particularly exploring how it can empower both teachers and students. Based on the analysis of 87 articles, selected by adopting the PRISMA workflow, the study discusses the intersection of LA with collaborative learning (CL), emphasizing the…

Learning Analytics are an academic field with promising usage scenarios for many educational domains. At the same time, learning analytics come with threats such as the amplification of historically grown inequalities. A range of general guidelines for more equity-focused learning analytics have been proposed but fail to provide sufficiently clear…

The adoption of learning analytics (LA) in complex educational systems is woven into sociocultural and technical challenges that have induced distrust in data and difficulties in scaling LA. This paper presents a study that investigated areas of distrust and threats to trustworthy LA through a series of consultations with teaching staff and…

This paper leverages cluster analysis to provide insight into how traditionally underrepresented learners engage with entry-level massive open online courses (MOOCs) intended to lower the barrier to university enrolment, produced by a major research university in the United States. From an initial sample of 260,239 learners, we cluster analyze a…

While teachers often monitor and adjust their learning design based on students' emotional states in physical classrooms, synchronous online environments often limit their ability to perceive the emotional climate of the class. Drawing from the concept of social translucence, it is suggested that making students' emotional states…