This paper describes a method to collect data of which section of pages learners were browsing in digital textbooks without eye-tracking technologies. In previous researches on digital textbook systems, it was difficult to collect such data without using eye-tackers. However, eye-trackers cost a massive budget. Our proposed system automatically…

The last two decades have witnessed a quick shift from pen-and-paper writing to computer keyboard writing. Corresponding to this shift in the writing medium are vigorous research efforts to understand new features of writing in computer keyboard settings. Using Inputlog7.0, this study investigated the writing process of 60 Chinese English as a…

As online learning platforms and computerized testing become more common, an increasing amount of data are collected about users. These data include, but are not limited to, response time, keystroke logs, and raw text. The desire to observe these features of the response process reflect an underlying interest in the cognitive processes and…

Expectations of big data across various fields, including education, are increasing. However, uncovering valuable insights from big data is like locating a needle in a haystack, and it is difficult for teachers to use educational big data on their own. This study aimed to understand changes in student participation rates during classes and…

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…

The study compared two survey datasets from higher education students in Germany and Ghana regarding access to digital devices; perceived value of digital media, tools, and services used for learning; gap analysis of the actual and desired use of digital teaching and learning formats; and types of media usage profiles among students. The findings…

Bias may be introduced in survey data collection when participants answer questions differently depending on interviewer gender. This could affect the validity of collected data, especially sensitive data. Using sexual behavior data collected in a 2017-2018 cross-sectional survey of Haitian women (n = 304), we evaluated the associations between…

In the current context of distance learning, learning management systems (LMSs) make it possible to store large volumes of data on web browsing and completed assignments. To understand student behavior patterns in this type of environment, educators and managers must rethink conventional approaches to the analysis of these data and use appropriate…

The development and improvement of effective tools for predicting human behavior in real life through the features of its virtual activity opens up broad prospects for psychological support of the individual. The presence of such tools can be used by psychologists in educational, professional and other areas in the formation of trajectories of…

Amid the pandemic of coronavirus diseases, virtual conferences have become an alternative way to maintain the prosperity of the research community. This study investigated attendees' participatory behavior in a virtual academic conference (TWELF2020, Taiwan) and studied the interrelationship among their mastery experience, competence, and…

The widespread adoption of online courses opens opportunities for analysing learner behaviour and optimising web-based learning adapted to observed usage. Here, we introduce a mathematical framework for the analysis of time-series of online learner engagement, which allows the identification of clusters of learners with similar online temporal…

Most research into second language (L2) writing has focused on the products of writing tasks; much less empirical work has examined the behaviours in which L2 writers engage and the cognitive processes that underlie writing behaviours. We aimed to fill this gap by investigating the extent to which writing speed fluency, pausing, eye-gaze…

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…

Using mobile technology and experience sampling in junior high school, real-time motivation and engagement were explored at four-levels: between lessons (up to 2 lessons per day; Level 1), between days (5 days per week; L2), between weeks (4 weeks; L3), and between students (113 students; L4). Findings for a 'random effects' model revealed…