Il-Hyun Jo

TL;DR: The Learning Analytics Dashboard is an application to show students' online behavior patterns in a virtual learning environment and lessons learned from the usability and pilot tests support that visualized information impacts on students' understanding level; and the overall satisfaction with dashboard plays as a covariant that impacts on both the degree of understanding and students' perceived change of behavior.

TL;DR: Latent Class Analysis method as a clustering approach of educational data mining was employed to extract common activity features of 612 courses in a large private university located in South Korea by using online behavior data tracked from Learning Management System and institution's course database.

TL;DR: The Learning Analytics Dashboard (LAD) as mentioned in this paper is a learning support tool for virtual classrooms that is believed to allow students to review their online learning behavior patterns intuitively through the provision of visual information.

TL;DR: The aim of this study is to suggest more meaningful components for learning analytics in order to help learners improving their learning achievement continuously through an educational technology approach.

TL;DR: In this article, the authors applied learning analytics to analyze log data from 284 undergraduate students enrolled in an asynchronous online statistics course, and identified student SRL profiles, and examined the actual student learning patterns.