This article investigates the state of AI regulations from diverse geopolitical contexts including the European Union, the United States, China, and several African nations, and their implications for learning analytics (LA) and AI research. We used a comparative analysis approach of 11 AI regulatory documents and applied the OECD framework to…

Learning analytics (LA) adoption is a challenging task for higher education institutions (HEIs) since it involves different aspects of the academic environment, such as information technology infrastructure, human resource management, ethics, and pedagogical issues. Therefore, it is necessary to provide institutions with supporting instruments to…

Despite the increasing availability of data used to inform educational policies and practices, concerns persist regarding its quality and accessibility. This study surveys quality education data from Brazil, Colombia, and Peru and evaluates their alignment with the FAIR principles and availability to support academic analytics (AA) and learning…

Socially shared regulation in learning (SSRL) contributes to successful collaborative learning (CL). Empirical research into SSRL has received considerable attention recently, with increasingly available multimodal data, advanced learning analytics (LA), and artificial intelligence (AI) providing promising research avenues. Yet, integrating these…

Researchers in learning analytics have created indicators with learners' trace data as a proxy for studying learner behaviour in a college course. Student Approaches to Learning (SAL) is one of the theories used to explain these behaviours, distinguishing between deep, surface, and organized study. In Latin America, researchers have demonstrated…

Behavioural engagement as a predictor of academic success hinges on the interplay between effort and time. Exploring the longitudinal development of engagement is vital for understanding adaptations in learning behaviour and informing educational interventions. However, person-oriented longitudinal studies on student engagement are scarce.…

As learning analytics practices become more commonplace in educational settings, student knowledge about the collection and use of their data becomes more of an interest. How students perceive the collection and use of their data has been researched for many years, with legitimate privacy and ethical concerns raised. While various guidelines,…

Visual Learning Analytics (VLA) uses analytics to monitor and assess educational data by combining visual and automated analysis to provide educational explanations. Such tools could aid teachers in primary and secondary schools in making pedagogical decisions, however, the evidence of their effectiveness and benefits is still limited. With this…

With student and staff wellbeing a growing concern, several authors have asked whether existing data might help institutions provide better support. By analogy with the established field of Learning Analytics, this might involve identifying causes of stress, improving access to information for those who need it, suggesting options, providing rapid…

Engaging students in creating high-quality novel content, such as educational resources, promotes deep and higher-order learning. However, students often lack the necessary training or knowledge to produce such content. To address this gap, this paper explores the potential of incorporating generative AI (GenAI) to review students' work and…

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…

In June 2022, the Norwegian Expert Commission on Learning Analytics delivered an interim report to the Norwegian Minister of Education and Research. Motivated by the need to establish a solid foundation upon which to regulate and promote the use of learning analytics in the Norwegian educational sector, the Ministry asked the Expert Commission to…

Digital transformation in schools involves the use of digital data to inform teachers' pedagogical decisions. Previous research indicates that a deeper understanding of the factors influencing teacher utilization of learning analytics and a comprehensive school context analysis is required. In this article, we conducted a survey study with N =…

Supporting academically at-risk students has attracted much attention in the field of learning analytics. However, much of the research in this area has focused on developing advanced machine learning models to predict students' academic performance, which alone is insufficient to improve student learning without the implementation of timely…

Understanding students' emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging to disentangle individual performance from group-based deliverables. This study introduces new learning…