The adoption of learning analytics (LA) in higher education institutions (HEIs) in Mexico is still at an early stage despite increasing global interest and advances in the field. The use of educational data remains a challenging puzzle for many universities, which strive to provide students, teachers, and institutional administrators with…

The value of students developing the capacity to accurately judge the quality of their work and that of others has been widely studied and recognized in higher education literature. To date, much of the research and commentary on evaluative judgment has been theoretical and speculative in nature, focusing on perceived benefits and proposing…

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…

Research on learning analytics (LA) has focused mostly at the university level. LA research in the K-12 setting is needed. This study aimed to understand 4,115 middle school students' learning paths based on their behavioural patterns and the relationship with performance levels when they used a digital learning game as their science curriculum.…

Like learning analytics, physics education research is a relatively young field that draws on perspectives from multiple disciplines. Network analysis has an even more heterodox perspective, with roots in mathematics, sociology, and, more recently, computer science and physics. This paper reviews how network analysis has been used in physics…

The quality of the data and the amount of correct information available is key to informed decision-making. Higher education institutions (HEIs) often employ various decision support systems (DSSs) to make better choices. However, there is a lack of systems to assist with decision-making to promote innovation in teaching and learning. In this…

Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…

An essential part of making dashboards more effective in motivating students and leading to desirable behavioural change is knowing what information to communicate to the student and how to frame and present it. Most of the research studying dashboards' impact on learning analyzes learning indicators of students as a group. Understanding how a…

The generation, use, and analysis of educational data comes with many promises and opportunities, especially where digital materials allow usage of learning analytics (LA) as a tool in data-based decision-making (DBDM). However, there are questions about the interplay between teachers, students, context, and technology. Therefore, this paper…

The construction of prediction models reflecting players' learning performance in serious games currently faces various challenges for learning analytics. In this study, we design, implement, and field test a learning analytics system for a serious game, advancing the field by explicitly showing which in-game features correspond to differences in…

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…

Socio-spatial learning analytics (SSLA) is an emerging area within learning analytics research that seeks to uncover valuable educational insights from individuals' social and spatial data traces. These traces are captured automatically through sensing technologies in physical learning spaces, and the research is commonly based on the theoretical…

This commentary discusses how research approaches from Cognitive Network Science can be of relevance to research in the field of Learning Analytics, with a focus on modelling the knowledge representations of learners and students as a network of interrelated concepts. After providing a brief overview of research in Cognitive Network Science, I…

Learning activities are at the core of every educational design effort. Designing learning activities is a process that benefits from reflecting on previous runs of those activities. One way to measure the behaviour and effects of design choices is to use learning analytics (LA). The challenge, however, lies in the unavailability of an…

Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…