Due notably to the emergence of massive open online courses (MOOCs), stakeholders in online education have amassed extensive databases on learners throughout the past decade. Administrators of online course platforms, for instance, possess a broad spectrum of information about their users. This information spans from users' areas of interest to…

The Modular Object-Oriented Dynamic Learning Environment (Moodle), a type of Learning Management System (LMS), is growing globally. Across the world, the student population keeps growing, making it challenging for the existing physical infrastructure to accommodate all the students. Despite the enormous potential significance of Analytics Graphs,…

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,…

Emotions are vital to learning success, especially in online learning environments. They make the difference between learning success and failure. Unfortunately, learners' emotional state is still rarely considered in online learning and teaching, although it is an important driver of learning success. This paper reports a work-in-progress…

Computational analysis methods and machine learning techniques introduce innovative ways to capture classroom interactions and display data on analytics dashboards. Automated classroom analytics employ advanced data analysis, providing educators with comprehensive insights into student participation, engagement, and behavioral trends within…

Purpose: The purpose of this paper is to explore and establish the contours of trust in learning analytics and to establish steps that institutions might take to address the "trust deficit" in learning analytics. Design/methodology/approach: "Trust" has always been part and parcel of learning analytics research and practice,…

There is a small window of opportunity at the beginning of semester for a university to provide commencing students with timely and targeted support. However, there is limited information available on interventions that identify and support disengaged students from equity groups without using equity group status as the basis for the contact. The…

This work proposes Dynamic Linear Epsilon-Greedy, a novel contextual multi-armed bandit algorithm that can adaptively assign personalized content to users while enabling unbiased statistical analysis. Traditional A/B testing and reinforcement learning approaches have trade-offs between empirical investigation and maximal impact on users. Our…

Multimodal learning analytics, which is collection, analysis, and report of diverse learning traces to better understand and improve the learning process, has been producing a series of interesting prototypes to analyze learning activities that were previously hard to objectively evaluate. However, none of these prototypes have been taken out of…

Despite the ubiquity of learning in workplace and professional settings, the learning analytics (LA) community has paid significant attention to such settings only recently. This may be due to the focus on researching formal learning, as workplace learning is often informal, hard to grasp, and not unequivocally defined. This article summarizes the…

Predictive modeling in online education is a popular topic in learning analytics research and practice. This study proposes a novel predictive modeling method to improve model transferability over time within the same course and across different courses. The research gaps addressed are limited evidence showing whether a predictive model built on…

This paper is basic research focused on the analysis of scientific advances related to Smart Learning Environments (SLE). Our main objective is to single out the common aspects to propose a new definition which will constitute the starting point to design an innovative model which we can apply to the analysis of real cases and good practices. For…

How to choose the most appropriate courses to study throughout the learning process remains a question interested in by many students. Students often choose suitable courses according to their interests, needs, and advice from supporting staff, etc. This paper presents the results in developing a course recommendation system that will select…

Learning analytics (LA) collects, analyses, and reports big data about learners to optimise learning. LA ethics is an interdisciplinary field of study that addresses moral, legal, and social issues; therefore, institutions are responsible for implementing frameworks that integrate these topics. Many of the ethical issues raised apply equally to…

Multimodal data have the potential to explore emerging learning practices that extend human cognitive capacities. A critical issue stretching in many multimodal learning analytics (MLA) systems and studies is the current focus aimed at supporting researchers to model learner behaviours, rather than directly supporting learners. Moreover, many MLA…