Despite the importance of academic counselling for student success, providing timely and personalized guidance can be challenging for higher education institutions. In this study, we investigate the impact of counselling instances supported by a learning analytics (LA) tool, called TrAC, which provides specific data about the curriculum and grades…

During the past years scholars have shown an increasing interest in supporting students' self-regulated learning (SRL). Learning analytics (LA) can be applied in various ways to identify a learner's current state of self-regulation and support SRL processes. It is important to examine how LA has been used to identify the need for support in…

The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…

Academic institutions dedicate a substantial effort to ensure the academic success of their students. At the course level, teachers recommend learning paths (RLPs) for students to guarantee the achievement of their learning outcomes. In terms of performance, these kinds of approaches are deemed more effective than others based uniquely on…

Studies examining students' learning behavior predominantly employed rich video data as their main source of information due to the limited knowledge of computer vision and deep learning algorithms. However, one of the challenges faced during such observation is the strenuous task of coding large amounts of video data through repeated viewings. In…

Teacher data use is often centered around standardized testing. Such data use that is commonly centered on standardized tests and used during professional development does not necessarily transform teacher practice toward equity and fails to change teacher conceptualizations of students while also perpetuating inequitable practices. Conversely,…

Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its…

Learning analytics intervention (LAI) studies aim to identify at-risk students early during an academic term using predictive models and facilitate educators to provide effective interventions to improve educational outcomes. A major impediment to the uptake of LAI is the lack of access to LAI infrastructure by educators to pilot LAI, which…

Learning analytics (LA) has been widely adopted in research on education. However, most studies in the area have conducted LA after computer-supported collaborative learning (CSCL) activities rather than during CSCL. To address this problem, this study proposed a LA-based real-time feedback approach based on a deep neural network model to improve…

The application of learning analytics (LA) to research and practice in higher education is expanding. Researchers and practitioners are using LA to provide an evidentiary basis across higher education to investigate student learning, to drive institutional quality improvement strategies, to determine at-risk behaviours and develop intervention…

This research paper highlights and addresses the lack of a systematic review of the methods used to evaluate Learning Analytics (LA) and Learning Analytics Dashboards (LAD) of Adaptive Learning Platforms (ALPs) in the current literature. Addressing this gap, the authors built upon the work of Tretow-Fish and Khalid (2022) and analyzed 32 papers,…

This paper describes a Human-Centred Learning Analytics (HCLA) design approach for developing learning analytics (LA) dashboards for K-12 classrooms that maintain both contextual relevance and scalability--two goals that are often in competition. Using mixed methods, we collected observational and interview data from teacher partners and…

The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and…

Precision education derives teaching and learning opportunities by customizing predictive rules in educational methods. Innovative educational research faces new challenges and affords state-of-the-art methods to trace knowledge between the teaching and learning ecosystem. Individual intelligence can only be captured through knowledge level…

Adaptivity in advanced learning technologies offer the possibility to adapt to different student backgrounds, which is difficult to do in a traditional classroom setting. However, there are mixed results on the effectiveness of adaptivity based on different implementations and contexts. In this paper, we introduce AI adaptivity in the context of a…