This article examines the work of predictive analytics in shaping the social worlds in which they thrive, and in particular the world of the first year of Great State University's student success initiative. Specifically, this article investigates the following research paradox: predictive analytics, as driven by a logic premised on predicting the…

Background: Providing feedback in massive open online courses (MOOCs) is challenging due to the massiveness and heterogeneity of learners' population. Learning analytics (LA) solutions aim at scaling up feedback interventions and supporting instructors in this endeavour. Paper Objectives: This paper focuses on instructor-led feedback mediated by…

Engagement is critical in learning, including computer-supported collaborative learning (CSCL). Previous studies have mainly measured engagement using students' self-reports which usually do not capture the learning process or the interactions between group members. Therefore, researchers advocated developing new and innovative engagement…

Learning analytics is an emerging trend in American community colleges brought about by technological advancements, institutional accountability, and external pressure on institutions to substantiate and improve learning. Learning analytics can potentially improve student engagement, retention, and success but also possess inherent ethical and…

Actionability is a critical issue in learning analytics for driving impact in learning, bridging the gap between insights and improvement. This dissertation places actionability at the forefront, integrating it throughout the learning analytics process to fully leverage its potential. The study involves designing, developing, and implementing…

The purpose of this study is to analyze which behaviors are or are not helpful for debugging when a novice is in a state of unproductive persistence. Further, this project will exploratorily use a variety of analytical techniques -- including association rule mining, process mining, frequent sequence mining, and machine learning-- in order to…

The effective use of self-regulation strategies has been considered significant in online learning environments. It is known that learners must be supported in this context. Academic help-seeking (AHS), as one of the main self-regulated learning strategies, is associated with academic success. However, learners may avoid seeking help for…

Learning analytics research presents challenges for researchers embracing the principles of open science. Protecting student privacy is paramount, but progress in increasing scientific understanding and improving educational outcomes depends upon open, scalable and replicable research. Findings have repeatedly been shown to be contextually…

With Big Data revolution, the education sector is being reshaped. The current data-driven education system provides many opportunities to utilize the enormous amount of collected data about students' activities and performance for personalized education, adapting teaching methods, and decision making. On the other hand, such benefits come at a…

Drawn from the SQELT Erasmus+ project, this article explores how learning analytics is implemented at a set of six European universities in the context of their performance data management models, including its multiple functions and ethical issues. It further identifies possible good practice and policy recommendations at decision-making level.…

As students in online courses usually show differences in their cognitive levels and lack communication with teachers, it is difficult for teachers to grasp student perceptions of the importance of knowledgepoints and to develop personalized teaching. Though recent studies have paid attention to this topic, existing methods fail to calculate the…

Wearable devices are an emerging technological tool in the field of learning analytics. With the help of wearable technologies, an increasing number of scholars have a strong interest in studying the associations between student data and learning outcomes in different learning environments. This systematic review examines 120 articles published…

There is growing interest in applying gamification to adaptive learning systems to motivate and engage students during the learning process. However, previous studies have reported unexpected results about student outcomes in these systems. One of the causes of these unfavorable effects is the lack of monitoring and adaptation of gamification…

As educators turn to technology to supplement classroom instruction, the integration of natural language processing (NLP) into educational technologies is vital for increasing student success. NLP involves the use of computers to analyze and respond to human language, including students' responses to a variety of assignments and tasks. While NLP…

Algorithmic decision-making systems such as Learning Analytics (LA) are widely used in an educational setting ranging from kindergarten to university. Most research focuses on how LA is used and adopted by teachers. However, the perspective of students and parents who experience the (in)direct consequences of these systems is underexplored. This…