Learning style recognition is an indispensable part of achieving personalized learning in online learning systems. The traditional inventory method for learning style identification faces the limitations such as subject and static characteristics. Therefore, an automatic and reliable learning style recognition mechanism is designed in this…

This research investigated the potential of learning analytics (LA) as a tool for identifying and evaluating K-12 student behaviors associated with active learning when using video learning objects within an online learning environment (OLE). The study focused on the application of LA for evaluating K-12 student engagement in videobased…

This study conducted a systematic literature review of articles on learning analytics published between 2004 and January 2024. A total of 1,064 articles, identified using the keyword "learning analytic*" in the Scopus database, were analyzed. The study integrated systematic literature review and bibliometric analysis approaches to…

Behavioural engagement as a predictor of academic success hinges on the interplay between effort and time. Exploring the longitudinal development of engagement is vital for understanding adaptations in learning behaviour and informing educational interventions. However, person-oriented longitudinal studies on student engagement are scarce.…

The concept of ubiquitous learning has emerged as a pedagogical approach in response to the advancements made in mobile, wireless communication, and sensing technologies. The domain of ubiquitous learning is distinguished by swift progression, thereby presenting a difficulty in maintaining current knowledge of its developments. The implementation…

Student emotions influence assessment task behaviour and performance but are difficult to study empirically. The study combined qualitative data from focus group interviews with 22 students and 4 teachers, with quantitative real-time learning analytics (facial expression, mouse click and keyboard strokes) to examine student emotional engagement in…

Purpose: The purpose of this study is to set up an evaluation model to predict massive open online courses (MOOC) learning performance by analyzing MOOC learners' online learning behaviors, and comparing three algorithms -- multiple linear regression (MLR), multilayer perceptron (MLP) and classification and regression tree (CART).…

Individual differences exist among learners. Among various individual differences, cognitive styles can strongly predict learners' learning behavior. Therefore, cognitive styles are essential for the design of online learning. There are a variety of cognitive style dimensions and overlaps exist among these dimensions. In particular, Witkin's field…

Understanding students' emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging to disentangle individual performance from group-based deliverables. This study introduces new learning…

Pre-service teacher training is research intensive in Finland. Additionally, teaching as a profession is highly valued among young people. However, quantitative methods courses are challenging for teacher students from many reasons. Particularly, this is due to previous negative experiences and emotions (among other things). Thus, novel approaches…

Learning analytics needs to pay more attention to the temporal aspect of learning processes, especially in self-regulated learning (SRL) research. In doing so, learning analytics models should incorporate both the duration and frequency of learning activities, the passage of time, and the temporal order of learning activities. However, where this…

Background: Deep discussions play an important role in students' online learning. However, researchers have largely focused on engaging students in deep discussions in online asynchronous forums. Few studies have investigated how to promote deep discussion via mobile instant messaging (MIM). Objectives: In this study, we applied learning…

Learning Analytics tools are employed to assess student engagement with the Virtual Campus in an undergraduate Fluid Mechanics course at university level in Spain. This is aimed at obtaining a diagnosis of the course problematics which include low attendance rates, poor performance on activity tests and exams and a high number of re-enrolments. A…

The future of university learning in Sub-Saharan Africa has become increasingly digitally transformed by both e-Learning, and learning analytics, post-COVID-19 pandemic. Learning analytics intervention is critical for effective support of socially-shared regulated learning skills, which are crucial for twenty-first-century e-Learners.…

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…