When higher education institutions (HEIs) have the potential to collect large amounts of learner data, it is important to consider the spectrum of stakeholders involved with and impacted by the use of learning analytics. This qualitative research study aims to understand the degree of concern with issues of bias and equity in the uses of learner…

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,…

This article advances an abolitionist reframing of learning analytics (LA) that explores the benefits of productive disorientation, considers potential harms and care made possible by LA, and suggests the abolitionist imagination as an important educational practice. By applying abolitionist concepts to LA, we propose it may be feasible to open…

Ethical considerations, including transparency, play an important role when using artificial intelligence (AI) in education. Explainable AI has been coined as a solution to provide more insight into the inner workings of AI algorithms. However, carefully designed user studies on how to design explanations for AI in education are still limited. The…

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…

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…

Learning analytics needs to pay more attention to the temporal aspect of learning processes, especially in self-regulated learning (SRL) research. In doing so, learning analytics models should incorporate both the duration and frequency of learning activities, the passage of time, and the temporal order of learning activities. However, where this…

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…

Personalized feedback is important for the learning process, but it is time consuming and particularly problematic in large-scale courses. While automatic feedback may help for self-regulated learning, not all forms of feedback are effective. Social comparison offers powerful feedback but is often loosely designed. We propose that intertwining…

Collaboration is a complex, multidimensional process; however, details of how multimodal features intersect and mediate group interactions have not been fully unpacked. Characterizing and analyzing the temporal patterns based on multimodal features is a challenging yet important work to advance our understanding of computer-supported collaborative…

Preparatory learning tasks are considered critical for student success in flipped classroom courses. However, less is known regarding which learning strategies students use and when they use those strategies in a flipped classroom course. In this study, we aimed to address this research gap. In particular, we investigated mutual connections…

Learning Analytics Dashboards (LADs) are gaining popularity as a platform for providing students with insights into their learning behaviour patterns in online environments. Existing LAD studies are mainly centred on displaying students' online behaviours with simplistic descriptive insights. Only a few studies have integrated predictive…

This single-site case study will seek to answer the following question: how is the concept of privacy addressed in relation to a student success information system within a small, public institution of higher education? Three themes were found within the inductive coding process, which used interviews, documentation, and videos as data resources.…

This study examines the temporal co-occurrences of self-regulated learning (SRL) activities and three types of knowledge (i.e., task information, domain knowledge, and metacognitive knowledge) of 34 medical students who solved two tasks of varying complexity in a computer-simulated environment. Specifically, we explored how task complexity…