The First Adaptive MOOC: A Case Study on Pedagogy Framework and Scalable Cloud Architecture—Part I

Abstract

The opportunity to learn from the best educators of the top universities at no cost has captured the imagination of millions who have registered for MOOCs across the United States and abroad. As MOOCs have gained momentum, critical debate is brewing on the pedagogical effectiveness of MOOCs. The high attrition rate of students who register at the beginning of a MOOC is a major cause of concern regarding the long-term success, impact, and sustainability of MOOCs. Having conducted many experiments and studies on the application of adaptive learning in personalized online learning, Synaptic Global Learning set out to develop the first adaptive MOOC (aMOOC) platform, providing a strong pedagogical framework and a personalized learning experience in a MOOC learning environment. In partnership with the Center for Innovation and Excellence in eLearning of the College of Advancing and Continued Studies, University of Massachusetts Boston, Synaptic Global Learning developed the first aMOOC in the area of computational molecular dynamics (CMD). This article describes the design, development, and deployment of this aMOOC. Part I of this case-study is focused on the pedagogical framework that allows four dimensions of learning and dynamic rendering of the content to accommodate five distinct learning strategies using the adaptive mobile learning (AMOL) platform. The AMOL platform is then implemented on the Amazon Web Services (AWS) cloud architecture and load-tested for the use of aMOOCs. The results indicate that even with dynamic rendering of the fine learning strategies and real-time feedback, the AWS-based scalable architecture is sufficient to provide high throughput and acceptable response time.