Using newly released detailed data on absence from school, we find a 'Friday effect'--children are much less likely to attend schools in England on Fridays. We use daily level data across the whole of England and find that this pattern holds for different schools and for different types of absence, including illness-related authorised and…

Interactive learning environments can generate massive learning behavior data and the support of learning behavior big data can ensure the completeness of data analysis and robustness of relationship verification. In this study, learning behaviors are divided into training set and testing set, BP neural network and recurrent Elman network are…

Purpose: This paper aims to investigate the relationship between the students' digital activities and their academic performance through two stages. In the first stage, students' digital activities were studied and clustered based on the attributes of their activity log of learning management system (LMS) data set. In the second stage, the…

In this article, we reveal the nature and effects of data infrastructures on the authorisation of data that represent students and educational practitioners, including how such data can misrepresent and govern educational policy and practices in sometimes problematic ways. To better understand the governance capacities of data infrastructures, we…

Understanding how students with low socioeconomic status finance their tuition over time can help us comprehend the impact of students' decisions on their subsequent curricular progress, graduation, or dropout. This work presents a curricular analytics approach using process mining techniques to study educational funding trajectories as processes.…

The current study provides an integrated comprehensive analysis of mediation-moderation models to understand 567 tourism and hospitality students' viewpoints by exploring multidisciplinary contributions relevant to the big data and new technology application bodies of literature. The results show that self-efficacy was the primary motivation…

With the increased emphasis on the benefits of self-regulated learning (SRL), it is important to make use of the huge amounts of educational data generated from online learning environments to identify the appropriate educational data mining (EDM) techniques that can help explore and understand online learners' behavioral patterns. Understanding…

Online learning systems allow learners to freely access learning contents and record their interactions throughout their engagement with the content. By using data mining techniques on the student log data of those systems, it is possible to examine learning behavior and reveal navigation patterns through learning contents. This study was aimed at…

Purpose: This report highlights ways in which race-based data can be used to combat systemic racism in matters relating to academic and non-academic and student misconduct. Methods: Information synthesis of available information relating to race-based data and student conduct. Results: A summary and synthesis of how and why race-based data can be…

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…

These pages aim to explain and interpret why the late Mika Seppälä, a conformal geometer, proposed to model student study behaviour using concepts from conformal geometry, such as Riemann surfaces and Strebel differentials. Over many years Mika Seppälä taught online calculus courses to students at Florida State University in the United States, as…

Computer-based assessments allow practitioners to collect rich process data by logging students' interactions with assessment tasks. In addition to providing final responses to test questions, computer-based assessments promise to furnish more evidence to support claims about what a student knows and can do through logging process data in log…

The current study uncovers secondary school students' actual use of text-learning strategies during an individual learning task by means of a concurrent self-reported thinking aloud procedure. Think-aloud data of 51 participants with different learning strategy profiles, distinguished based on a retrospective self-report questionnaire (i.e., 15…

Discussion forums are used to support socio-collaborative learning processes among students in online courses. However, complex forum structures and lengthy discourse require that students spend their limited time searching and filtering through posts to find those that are relevant to them rather than spending that time engaged in other…

This study aims to apply a sequential analysis to explore the effect of learning motivation on online reading behavioral patterns. The study's participants consisted of 160 graduate students who were classified into three group types: low reading duration with low motivation, low reading duration with high motivation, and high reading duration…