Development of Learning Analytics Dashboard based on Moodle Learning Management System

Abstract

Digitalization catalyzes drastic changes to a particular subject or area. Digitalization is an operational structure transformation process, such as in the educational domain. Digitalization in the academic field has brought the classroom to the users' fingertips with the prevalence of elearning applications, learning management systems, etc. However, with the increasing number of digital learning platform users, educators find it hard to monitor their students' progress. Analytics that analyze data generated from the usage pattern of the users contribute to giving the educators an insight regarding the performance of their students. With that, they can apply early intervention and modification of their delivery method to suit the students' needs and, at the same time, increase the quality of the content. This study illustrates the development of a learning analytics dashboard that can improve learning outcomes for educators and students.

Critical Determinants for Learning Analytics Adoption in Higher Education

“…Learning analytics, and the application of data analytics in higher education institutions, have led to various benefits, including detecting at-risk students, tracking students' progress, predicting specific learning needs for an individual student, and revealing possible causes of students' academic achievement (Clark et al, 2020;El Alfy et al, 2019). Learning analytics obtains their data from Learning management systems (LMS) such as Moodle, Canvas, and Blackboard (Xin & Singh, 2021).…”

“…The LMS is developed to administer, track, report, and deliver educational courses and content. The software applications are accessible on a range of internet-enabled devices, including personal computers, laptops, iPads, Tablets, and smartphones (Xin & Singh, 2021). The high proliferation of LMS in higher education has led to the creation of massive datasets; however, obtaining relevant and accurate data from these data sets using applicable data analytics techniques has become more critical for lecturers to monitor and support students' learning (De Laet et al, 2020;Xin & Singh, 2021).…”

“…Data analytics analyses raw data to provide valuable insights to assist users in planning and implementing suitable interventions (Gutiérrez et al, 2020;Xin & Singh, 2021). There are four classifications of data analytics that can be implemented into LMS: descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics (Xin & Singh, 2021).…”

“…Descriptive analytics provides measured metrics and the activities in a certain period (Xin & Singh, 2021). In learning analytics, descriptive analytics enable lecturers to understand student performance patterns better and identify potential risk issues (Xin & Singh, 2021). Diagnostic analytics provide deeper insights that explain the causes of a problem under scrutiny.…”

“…Diagnostic analytics provide deeper insights that explain the causes of a problem under scrutiny. Diagnostic analytics are narrow and more specific than descriptive analytics (Xin & Singh, 2021).…”