Contribution: A competency assessment framework that enables learning analytics for course monitoring and continuous improvement. Our work fills the gap in systematic methods for competency assessment in higher education. Background: Many institutions are shifting toward competency-based education (CBE), thus encouraging their educators to start…

Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…

Monitoring students' academic progress is vital for ensuring timely completion of their studies and supporting at-risk students. Educational Data Mining (EDM) utilizes machine learning and feature selection to gain insights into student performance. However, many feature selection algorithms lack performance forecasting systems, limiting their…

Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…

An essential part of making dashboards more effective in motivating students and leading to desirable behavioural change is knowing what information to communicate to the student and how to frame and present it. Most of the research studying dashboards' impact on learning analyzes learning indicators of students as a group. Understanding how a…

Generic competence (GC) development is an integral part of higher education to provide holistic education and enhance student career development. It also plays a critical role in complementing the curriculum. Many tertiary institutions provide various GC development activities (GCDA). Moreover, institutions strongly need to further understand…

Learning Analytics Dashboards (LADs) are gaining popularity as a platform for providing students with insights into their learning behaviour patterns in online environments. Existing LAD studies are mainly centred on displaying students' online behaviours with simplistic descriptive insights. Only a few studies have integrated predictive…

Learning Analytics (LA) captures the digital footprint of students' online learning activity. This study describes students' navigational behavior in an e-learning setting by processing the LA data obtained from Blackboard LMS. This is an attempt to understand the navigational behavior of students and the relationship with learning performance.…

Predicting students' learning outcomes is one of the main topics of interest in the area of Educational Data Mining and Learning Analytics. To this end, a plethora of machine learning methods has been successfully applied for solving a variety of predictive problems. However, it is of utmost importance for both educators and data scientists to…

This systematic literature review investigates the fairness of machine learning algorithms in educational settings, focusing on recent studies and their proposed solutions to address biases. Applications analyzed include student dropout prediction, performance prediction, forum post classification, and recommender systems. We identify common…

Lecture capture is popular within Higher Education, but previous research suggests that students do not always optimally select content to review, nor do they make the most of specific functions. In the current study conducted in the 2019/20 academic year, we used a repeated-measures crossover design to establish the effects of transcripts with…

In this contribution to the Platform Studies in Education symposium, Luci Pangrazio, Amy Stornaiuolo, T. Philip Nichols, Antero Garcia, and Thomas M. Philip explore how digital platforms can be used to build knowledge and understanding of datafication processes among teachers and students. The essay responds to the turn toward data-driven teaching…

Language learner engagement, which is receiving increased attention, has predominantly focused on offline classroom contexts, while learner engagement in language Massive Open Online Courses (LMOOCs) remains under-explored. This study was conducted on a College English MOOC with the purpose of examining learner engagement and its relations with…

Lecture Capture (LC) material is accepted to be an available and accessible resource for students in universities across the world. This exploratory study investigates the "when viewing" LC material engagement of accounting undergraduate students. Three categories of engagement are defined, Near-Event-Viewing (NEV), Get-Round-to-Viewing…

The attribution of learning success or failure is crucial for students' learning and motivation. Effective attribution of their learning success or failure in the context of a small private online course (SPOC) could generate students' motivation toward learning success while an incorrect attribution would lead to a sense of helplessness. Based on…