Background: Dashboards play a prominent role in learning analytics (LA) research. In collaboration activities, dashboards can show traces of team participation. They are often evaluated based on students' perceived satisfaction and engagement with the dashboard. However, there is a notable methodological gap in understanding how these dashboards…

Despite the growing use of large language models (LLMs) in educational contexts, there is no evidence on how these can be operationalized by students to generate custom datasets suitable for teaching and learning. Moreover, in the context of network science, little is known about whether LLMs can replicate real-life network properties. This study…

Institutions of higher education possess large amounts of learning-related data in their student registers and learning management systems (LMS). This data can be mined to gain insights into study paths, study styles and possible bottlenecks on the study paths. In this study, we focused on creating a predictive model for study completion time…

Inquiry-based learning (IBL) is a practice-oriented approach where students pose questions, conduct investigations, and interpret data to develop scientific knowledge and exploratory skills. Learning analytics (LA) holds great potential to capture these dynamic processes, which provides valuable insights to understand student inquiry behaviours…

The integration of advanced learning analytics and data-mining technology into higher education has brought various opportunities and challenges, particularly in enhancing students' self-regulated learning (SRL) skills. Analyzing developed features for SRL support, it has become evident that SRL support is not a binary concept but rather a…

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…

Intelligent tutoring systems are increasingly used in schools, providing teachers with valuable analytics on student learning. However, many teachers lack the time to review these reports in detail due to heavy workloads, and some face challenges with data literacy. This project investigates the use of large language models (LLMs) to generate…

Digital traces have been used to measure self-regulated learning (SRL), yet the validity of inferences made about these traces has often been questioned. Recently, researchers have used multiple channels of data -- including digital traces, verbalizations, and self-reports -- to validate inferences about individual SRL events. Research on the…

Analyzing how participants learn from each other during online forums on discussion boards or social media platforms is often challenging. One of the predominant methods of analyzing such learning is through qualitative content analysis or interaction analysis. The Interaction Analysis Model (IAM), developed by Gunawardena, Lowe and Anderson which…

In this article, we offer theory-grounded narratives of a 4-year participatory design process of a Learning Analytics tool with K-12 educators. We describe how we "design-in-partnership" by leveraging educators' routines, values and cultural representations into the designs of digital dashboards. We make our long-term reasoning visible…

The artificial intelligence methods might be applied to see through the education problems, and make effective prediction and decision. The transformation from data to decision are inseparable from the learning analytics. In order to solve the dynamic multi-objective decision problems, a decision learning algorithm is designed to analyze the…

The purpose of this study was to investigate the use of predictive video analytics in online courses in the literature. A systematic literature review was performed based on a hybrid search strategy that included both database searching and backward snowballing. In total, 77 related publications published between 2011 and April 2023 were…

The e-learning domain has witnessed a shift from the traditional behavioral approach to an individual centered learning approach based on learning analytics, with the aim of creating personalized and learner sensitive designs. A systematic literature review of 284 articles published between 2011 and 2022 in 133 different journals was conducted to…

Learning analytics dashboards (LADs) are emerging tools that convert abstract, complex information with visualizations to facilitate teachers' data-driven pedagogical decision-making. While many LADs have been designed, teachers' capacities for using such LADs are not well articulated in the literature. To fill the gap, this study provided a…

Helping students gradually develop collective knowledge is critical but generally faces great challenges. Employing a quasi-experimental design, this study investigated the impacts and mechanisms of analytics-supported reflective assessment on the collective knowledge advancement of undergraduates. The experimental group (n = 55) engaged in…