To support online learners at a large scale, extensive studies have adopted machine learning (ML) techniques to analyze students' artifacts and predict their learning outcomes automatically. However, limited attention has been paid to the fairness of prediction with ML in educational settings. This study intends to fill the gap by introducing a…

AI technology, which is becoming more widespread day by day, also affects education and training processes. The use of AI tools in educational environments provides many benefits to teachers and students. However, the use of AI in education also raises some ethical concerns. The aim of this study was to reveal the ethical issues arising from the…

Educational games help reinforce educational concepts. They help students learn through hypothesizing, probing, and reflecting upon the game environment. Understanding the impact of a game is important before deploying it in a class. Recent studies in learning analysis describe methodologies and approaches for analyzing educational games. However,…

Learning analytics (LA) provides insight into student performance and progress, allowing for targeted interventions and support to improve the student learning experience. Uses of LA are diverse, including measuring student engagement, retention, progression, student well-being and curriculum development. This article provides perspectives on the…

Group composition affects learning by individuals. Dialogic pedagogy approaches demonstrate that this is particularly true when each grouped student knows something others do not (i.e., "mutuality" grouping). Learning analytics can help grouping by providing teachers with data on students' content-specific learning. What are mathematics…

Formative assessment is considered to be helpful in students' learning support and teaching design. Following Aufschnaiter's and Alonzo's framework, formative assessment practices of teachers can be subdivided into three practices: eliciting evidence, interpreting evidence and responding. Since students' conceptions are judged to be important for…

As universities around the world have begun to use learning management systems (LMSs), more learning data have become available to gain deeper insights into students' learning processes and make data-driven decisions to improve student learning. With the availability of rich data extracted from the LMS, researchers have turned much of their…

Background: With increased use of artificial intelligence in the classroom, there is now a need to better understand the complementarity of intelligent learning technology and teachers to produce effective instruction. Objective: The paper reviews the current research on intelligent learning technology designed to make models of student learning…

In this study, we examined interaction behaviors between a small number of participants in two massive open online courses (MOOCs) and an FAQ chatbot, focusing on the participants' native language markers. We used a binary native language marker (non-native English user vs. native English user) to distinguish between two groups in this multiple…

In a massive open online courses (MOOCs) learning environment, it is essential to understand students' social knowledge constructs and critical thinking for instructors to design intervention strategies. The development of social knowledge constructs and critical thinking can be represented by cognitive presence, which is a primary component of…

An extraordinary amount of data is becoming available in educational settings, collected from a wide range of Educational Technology tools and services. This creates opportunities for using methods from Artificial Intelligence and Learning Analytics (LA) to improve learning and the environments in which it occurs. And yet, analytics results…

Higher education data mining and analytics, like learning analytics, may improve learning experiences and outcomes. However, such practices are rife with student privacy concerns and other ethics issues. It is crucial that student privacy expectations and preferences are considered in the design of educational data analytics. This study forefronts…

The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…

An in-depth understanding of student experiences and evaluations of learning analytics dashboards (LADs) is needed to develop supportive learning analytics tools. This study investigates how students (N = 140) evaluated two student-facing LADs as a support for academic path-level self-regulated learning (SRL) through the concrete processes of…

Experience, whether personal or vicarious, plays an influential role in shaping human knowledge. Through these experiences, one develops an understanding of the world, which leads to learning. The process of gaining knowledge in higher education transcends beyond the passive transmission of knowledge from an expert to a novice. Instead, students…