Educational data mining and learning analytics have become a very important topic in the field of education technology. Many frameworks have been proposed for learning analytics which make it possible to identify learning behavior patterns or strategies. However, it is difficult to understand the reason why behavior patterns occur and why certain…

Personalized education--the systematic adaptation of instruction to individual learners--has been a long-striven goal. We review research on personalized education that has been conducted in the laboratory, in the classroom, and in digital learning environments. Across all learning environments, we find that personalization is most successful when…

This study investigates learner's reading behaviors in a critical reading task in humanities course using learning analytics techniques. "A Critical Analysis of Literature and Cinema" course was selected as a context. The course activities evolved over 10 years, and for this instance, some face-to-face classroom critical reading…

Purpose: The objective of this paper is to present a comprehensive review of the literature on learning analytics (LA) stakeholders' expectations to reveal the status of ongoing research in this area and to highlight gaps in research. Design/methodology/approach: Conducting a literature review is a well-known method to establish knowledge and…

Knowledge tracing (KT), the task of tracking the knowledge state of each student over time, has been assessed actively by artificial intelligence researchers. Recent reports have described that Deep-IRT, which combines Item Response Theory (IRT) with a deep learning model, provides superior performance. It can express the abilities of each student…

Higher education institutions (HEIs) implementing learning analytics (LA) use student data to improve the learning experience. The problem for LA implementation originates from individuals responsible for analytic programs from different institutional departments and the lack of a framework for communication and productive dialogue about usages of…

This study aims to determine the misconceptions of teacher candidates about the greenhouse effect concept by using Artificial Intelligence (AI) algorithm instead of human experts. The Knowledge Discovery from Data (KDD) process model was preferred in the study where the Analyse, Design, Develop, Implement, Evaluate (ADDIE) instructional design…

Collocations, a crucial component of language competence, remain a challenge for L2 learners across all proficiency levels. While the data-driven learning (DDL) approach has shown great potential for collocation learning from a shorter-term perspective, this study investigates its effectiveness in the long term, examining both linguistic gains and…

This study explores the application of the task-based teaching method in English education, particularly from the perspective of big data. Traditional English teaching models often fail to meet the diverse needs of students, with the task-based approach, despite being student-centered, encountering challenges such as task difficulty control and…

Understanding students' privacy concerns is an essential first step toward effective privacy-enhancing practices in learning analytics (LA). In this study, we develop and validate a model to explore the students' privacy concerns (SPICE) regarding LA practice in higher education. The SPICE model considers "privacy concerns" as a central…

Student engagement is consistently identified as a key predictor of learner outcomes within the online learning environment. However, there is limited guidance about using proactive strategies to improve engagement for low and non-engaged students: for example by specifically employing course learning analytics (CLA) and nudging strategies in…

Learning analytics dashboards have been developed to facilitate teacher guidance in computer-supported collaborative learning (CSCL). As yet, little is known about how teachers interpret dashboard information to facilitate guidance in their teaching practice. This study examined teachers' behavior patterns in interpreting information from…

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 paper, an empirical comparison of three state-of-the-art classifier methods (artificial immune recognition systems, Lazy-K Star, and random tree) to predict teachers' ability to adapt in a classroom environment is carried out. Two educational databases are used for this task. First, measures collected in an academic context, especially…

This commentary discusses how research approaches from Cognitive Network Science can be of relevance to research in the field of Learning Analytics, with a focus on modelling the knowledge representations of learners and students as a network of interrelated concepts. After providing a brief overview of research in Cognitive Network Science, I…