The focus of this study was on identifying patterns of student behavior to support data-informed decision-making which would then improve the learning experience and learning outcomes of online English language courses. Learning analytics approach (or more specifically cluster analysis) was used to identify engagement patterns in online learning.…

With the rapid development of mobile devices and web-based technologies, it becomes common for students to switch between different tasks during study time. However, it remains unclear how the transition between on-task and off-task states happens and how digital devices affect the process. This study examines college students' independent study…

Academic procrastination has been a subject of particular interest in research due to its frequent association with heightened levels of anxiety, stress, and the long-term risk of emotional and behavioural vulnerability (Hoge et al., 2013). Our study tests the correlation between motivational persistence as a trait and academic procrastination, as…

Lecture capture videos, a popular type of instructional content used by instructors to share course recordings online, play a significant role in educational settings. Compared to other educational videos, these recordings require minimal time and effort to produce, making them a preferred choice for disseminating course materials. Despite their…

This study aims to track college students' on-task rate during the teaching process and to analyze the influence of instructional strategies on on-task rate through the aspects of observable and internal engagement indicators. Thirty-six undergraduate students at a higher education institution in China participated in the study. Students'…

One of the recognized ways to enhance teaching and learning is having insights into the behavior patterns of students. Studies that explore behavior patterns in online self-directed learning (OSDL) are scant though. In addition, the focus is lacking on how high-achieving (HA) students' behavior patterns affect the academic performance of…

As a supplement to face-to-face teaching, small private online courses (SPOCs) have become increasingly popular in higher education. Nevertheless, there is a lack of research on behavioral patterns in the university SPOC. This empirical study investigates the behavioral patterns of 306 undergraduate students taking a degree course partially taught…

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…

Background: Examinees may not make enough effort when responding to test items if the assessment has no consequence for them. These disengaged responses can be problematic in low-stakes, large-scale assessments because they can bias item parameter estimates. However, the amount of bias, and whether this bias is similar across administrations, is…

Academic boredom is a complex and underestimated problem in schools in many countries. The research on this phenomenon is mostly from Germany and Northern America. During the last two-three decades several studies have highlighted some aspects of academic boredom and its relationship to motivation and school-based learning behavior and outcomes.…

Online educational games have been widely used to support students' mathematics learning. However, their effects largely depend on student-related factors, the most prominent being their behavioral characteristics as they play the games. In this study, we applied a set of learning analytics methods (k-means clustering, data visualization) to…

Online educational games have been widely used to support students' mathematics learning. However, their effects largely depend on student-related factors, the most prominent being their behavioral characteristics as they play the games. In this study, we applied a set of learning analytics methods ("k"-means clustering, data…

This paper addresses a key challenge in Educational Data Mining, namely to model student behavioral trajectories in order to provide a means for identifying students most at risk, with the goal of providing supportive interventions. While many forms of data including clickstream data or data from sensors have been used extensively in time series…

Background: Urban Black adolescents' wellbeing in the early high school years can be negatively impacted by exposure to racial discrimination. These impacts may be buffered by supportive relationships with adults at school. We considered both the protective and promotive effects of culturally responsive teachers and caring school police on school…

In this paper, we argue that, where we measure student attendance, this creates an extrinsic motivator in the form of a reward for (apparent) engagement and can thus lead to undesirable behaviour and outcomes. We go on to consider a number of other mechanisms to assess or encourage student engagement -- such as interactions with a learning…