Despite the importance of academic counselling for student success, providing timely and personalized guidance can be challenging for higher education institutions. In this study, we investigate the impact of counselling instances supported by a learning analytics (LA) tool, called TrAC, which provides specific data about the curriculum and grades…

Lecture Capture (LC) material is accepted to be an available and accessible resource for students in universities across the world. This exploratory study investigates the "when viewing" LC material engagement of accounting undergraduate students. Three categories of engagement are defined, Near-Event-Viewing (NEV), Get-Round-to-Viewing…

The attribution of learning success or failure is crucial for students' learning and motivation. Effective attribution of their learning success or failure in the context of a small private online course (SPOC) could generate students' motivation toward learning success while an incorrect attribution would lead to a sense of helplessness. Based on…

Learning analytics researchers have been diligently integrating trace data to study Self-Regulated Learning (SRL). Compared to traditionally used survey data, trace data, such as log or clickstream data designed and interpreted to understand a certain SRL construct, are considered to be more effective in capturing dynamic SRL as fine-grained…

This study addresses the problems in traditional English literature teaching methods for Chinese English majors, proposing a new teaching approach based on smart education concepts to enhance learning effectiveness. An evaluation of a semester-long reform in teaching methods is conducted using a quantitative methodology. The findings reveal…

This paper leverages cluster analysis to provide insight into how traditionally underrepresented learners engage with entry-level massive open online courses (MOOCs) intended to lower the barrier to university enrolment, produced by a major research university in the United States. From an initial sample of 260,239 learners, we cluster analyze a…

Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…

Classifying educational forum posts is a longstanding task in the research of Learning Analytics and Educational Data Mining. Though this task has been tackled by applying both traditional Machine Learning (ML) approaches (e.g., Logistics Regression and Random Forest) and up-to-date Deep Learning (DL) approaches, there lacks a systematic…

Information is everywhere in a hidden and scattered way. It becomes useful when we apply Data mining to extracts the hidden, meaningful, and potentially useful patterns from these vast data resources. Educational data mining ensures a quality education by analyzing educational data based on various aspects. In this paper, we have analyzed the…

Student grade prediction is a popular task for learning analytics, given grades are the traditional form of student performance. However, no matter the learning environment, student background, or domain content, there are things in common across most experiences in learning. In most previous machine learning models, previous grades are considered…

Background: The substantial growth in gamification research has connected gamified learning to enhanced engagement, improved performance, and greater motivation. Similar to gamification, personalized learning analytics dashboards can enhance student engagement. Objectives: This study explores the student experiences and academic achievements using…

Small private online courses (SPOCs) have influenced teaching and learning in China's higher education. Learning management systems (LMSs) are important components in SPOCs. They can collect various data related to student behavior and support pedagogical interventions. This research used feature engineering and nearest neighbor smoothing models…

We examine the effects of disseminating academic performance data--either status, growth, or both--on parents' school choices and their implications for racial, ethnic, and economic segregation. We conduct an online survey experiment featuring a nationally representative sample of parents and caretakers of children age 0-12. Participants choose…

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…

The purpose of this evaluation was to examine the impact of i-Ready Personalized Instruction that met Curriculum Associates' recommended usage levels on ELA achievement, as measured by the Massachusetts Comprehensive Assessment System (MCAS) ELA assessment. This study compared the ELA achievement growth in the 2020-21 school year of students who…