Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…

This article introduces the evolution of themes and ideas related to the history, theory, and practice of learning analytics within the learning, design, and technology field through four eras. This review provides researchers with a fundamental understanding of the origin of learning analytics from a historical perspective and distinguishes…

Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…

Despite efforts to implement innovative approaches such as flipped learning leveraging computer technology, the challenge of student failure persists. Understanding the factors that contribute to student success in flipped engineering courses remains a critical issue. This study addresses this issue by investigating the impact of student…

Educators and researchers have analyzed various image data acquired from teaching and learning, such as images of learning materials, classroom dynamics, students' drawings, etc. However, this approach is labour-intensive and time-consuming, limiting its scalability and efficiency. The recent development in the Visual Question Answering (VQA)…

Dashboards have become a crucial element of contemporary business operation and management; therefore, it is desirable for business students to acquire knowledge of them. This article investigates the effectiveness of designing learning activities around investment dashboards in the context of introductory business analytics (IBA) courses. We…

With various digital technologies increasingly integrated into higher education, understanding how students engage with such technologies has become vital. There are different ways to measure student engagement; however, self-reported measures such as questionnaires are predominantly used to understand student engagement. In contrast, this study…

Public Internet Data Mining methods enable studying educational institutions' public-facing communication. Multiple online data sources can illuminate differences in how different audiences are addressed online, opening the door for critical inquiry into emerging issues of representation and targeted advertising. The present study presents a case…