Using Learning Analytics to Improve MOOC Instructional Design

Nurbiha A Shukor,Zaleha Abdullah

doi:10.3991/ijet.v14i24.12185

Abstract

Massive Open Online Courses (MOOC) allows teaching and learning for everyone. This means that people from any learning background can join any of the courses offered through MOOC platforms. Although learning materials are offered for free, learning retention and learning engagement were found to be consistently low alt-hough some MOOC are offered by well-known instructors. Many recent studies tried to understand the suitable instructional design in MOOC to improve learning en-gagement and retention. This study is an exploratory study to evaluate the potential of using learning analytics to improve instructional design in MOOC. Data were col-lected from a MOOC offered for two consequent years in a public university in Ma-laysia. The impact of learning analytics on MOOC instructional design was also dis-cussed.

Highlights

Students drop out rate in Massive Open Online Courses (MOOC) is often discussed in many studies yet the real solution to this problem remains scarce
In this study we attempted to study instructional design for MOOC using learning analytics looking at MOOC as artefacts and collecting data from field serve as an important foundation of this study on using learning analytics
This study found that Home Pages in both MOOCs were frequently viewed

Summary

Introduction

Students drop out rate in MOOC is often discussed in many studies yet the real solution to this problem remains scarce. Among the reasons that the students drop out in MOOCs are, no real intention to complete the course, lack of time, course difficulty and lack of support, lack of digital skills and learning skills, bad experiences in previous MOOC participation, low expectation towards what they have to do in MOOC, starting late and the availability of peer review that is less favored by the students in MOOC (Onah, Sinclair & Boyatt, 2014) To address this issue many is concern about MOOC instructional design that can accommodate students‘ diversity yet allow personalized learning. Students in MOOC are sometimes active video viewers, passive video viewers, display active interaction in forum activity and are passive towards forum activity (Sinha, Li, Jermann & Dillenbourg, 2014)

Methods

Results

Conclusion