Since the emergence of learning analytics (LA) in 2011 as a distinct field of research and practice, multimodal learning analytics (MMLA), shares an interdisciplinary approach to research and practice with LA in its use of technology (eg, low cost sensors, wearable technologies), the use of artificial intelligence (AI) and machine learning (ML),…

Background: The COVID-19 pandemic disrupted higher education in many ways, such as the move to Emergency Remote Online Teaching and Learning (EROTL), often including a move to online assessments and examinations. With evidence of increased academic dishonesty in unproctored online assessment, institutions sought ways to ensure academic and…

Purpose: The purpose of this paper is to explore and establish the contours of trust in learning analytics and to establish steps that institutions might take to address the "trust deficit" in learning analytics. Design/methodology/approach: "Trust" has always been part and parcel of learning analytics research and practice,…

Evidence shows that appropriate use of technology in education has the potential to increase the effectiveness of, eg, teaching, learning and student support. There is also evidence that technology can introduce new problems and ethical issues, e.g., student privacy. This article maps some limitations of technological approaches that ensure…

Student data privacy as a research focus and practice is relatively under-researched in the context of massive open online courses (MOOCs). Central to researching student data privacy in the context of online service providers are the various user agreements that participants must accept or opt into before they can use a MOOC platform. Such…

While many strategies for protecting personal privacy rely on regulatory frameworks, consent, and anonymizing data, they are not always effective. Terms and Conditions often lag behind advances in technology, software, and user behaviours, and consent to use data for a range of unclear purposes may be provided unwittingly. As the commercial market…

In light of increasing concerns about surveillance, higher education institutions (HEIs) cannot afford a simple paternalistic approach to student data. Very few HEIs have regulatory frameworks in place and/or share information with students regarding the scope of data that may be collected, analyzed, used, and shared. It is clear from literature…