This scoping review aims to provide an overview of how multimodal learning analytics has been applied in K-8 research and offers methodological insights and recommendations to bridge the gap between theory and practice. We identified 14 peer-reviewed empirical studies published between 2011 and 2023 through searches in relevant databases and…

While high-accuracy machine learning (ML) models for predicting student learning performance have been widely explored, their deployment in real educational settings can lead to unintended harm if the predictions are biased. This study systematically examines the trade-offs between prediction accuracy and fairness in ML models trained on the…

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…

In this work, we consider learning analytics for primary and secondary schools from the perspective of the designer of a learning system. We provide an overview of practically useful analytics techniques with descriptions of their applications and specific illustrations. We highlight data biases and caveats that complicate the analysis and its…

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…