This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…

On e-learning platforms, most e-learners didn't complete the course successfully. It means that reducing dropout is a critical problem for the sustainability of e-learning. This paper aims to establish a predictive model to describe e-learners' dropout behavior, which can help the commercial e-learning platforms to make appropriate interventions…

The temporal sequence of learning behavior is multidimensional and continuous in MOOCs. On the one hand, it supports personalized learning methods, achieves flexible time and space. On the other hand, it also makes MOOCs produce a large number of dropouts and incomplete learning behaviors. Dropout prediction and decision feedback have become an…

Studies with an explicit focus on dropouts in blended language learning (BLL) are rare and non-existent in the Asian context. This study replicates the early qualitative interview study by Stracke (2007), who explored why foreign language learners drop out of a BLL class. While the 2007 study was carried out in the German higher education context,…

Dating back to 1998, researchers established that adults learn differently than younger, recent high school graduates. Even with decades of research on the topic, approximately 39 million American adults have attended college but left school without obtaining a degree. The research questions addressed the purpose of this qualitative exploratory…

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…

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…

The current longitudinal case study investigated emotional and motivational states in a self-directed and mobile-assisted language learning environment. The participant of the study was a highly motivated language learner who used the Busuu application for a period of one year to learn German. Tracing the participant's emotional and motivational…

This article provides evidence of critical factors of student retention in Language Massive Open Online Courses (LMOOCs). The study used multiple sources: tracked retention data (n=43,000), survey data in correlation with tracking data (n=400), and qualitative data (174 informants) from a survey (Friðriksdóttir, 2018, 2021a, 2021b). The data came…

Churn in e-learning refers to learners who gradually perform less and become lethargic and may potentially drop out from the course. Churn prediction is a highly sensitive and critical task in an e-learning system because inaccurate predictions might cause undesired consequences. A lot of approaches proposed in the literature analyzed and modeled…

In many countries with apprenticeship-based vocational education and training (VET), dropout from apprenticeship training is a major concern. Leaving an apprenticeship early can be problematic, particularly for young people who do not continue their training at another company or in another occupation, and drop out of the education system without…

Distance Learning has enabled educational practices based on digital platforms, generating massive amounts of data. Several initiatives use this data to identify dropout contexts, mainly providing teacher support about student behavior. Approaches such as Active Methodologies are known as having good potential to involve and motivate students.…

Teenagers coming from low socioeconomic backgrounds are at a disadvantage when they are accepted to study at an EMI university in terms of their foreign language readiness. Thus, most of them cannot persist in their endeavor and drop out of university. In this mixed-methods design study, we implemented the Technology Enhanced Active Learning Model…

As the COVID-19 pandemic was spreading rapidly throughout the world, the most widespread reaction in many countries to curtail the disease was lockdown. As a result, educational institutions had to find an alternative to face-to-face learning. The most obvious solution was e-learning. Conventional tertiary institutions with little virtual learning…

The aim of this study is to conduct a situational analysis of the benefits and drawbacks of returning to face-to-face courses in the Leveling Courses of the Universidad de las Fuerzas Armadas ESPE Sede Latacunga during the post-COVID-19 era. This will be done by comparing the virtual study mode in 2022 to the face-to-face mode in 2023. The results…