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…

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…

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…

By participating in asynchronous course discussion forums, students can work together to refine their ideas and construct knowledge collaboratively. Typically, some messages simply repeat or paraphrase course content, while others bring in new material, demonstrate reasoning, integrate concepts, and develop solutions. Through the messages they…

Predictive Learning Analytics (PLA) aim to improve learning by identifying students at risk of failing their studies. Yet, little is known about how best to integrate and scaffold PLA initiatives into higher education institutions. Towards this end, it becomes essential to capture and analyze the perceptions of relevant educational stakeholders…