An Asynchronous, Personalized Learning Platform―Guided Learning Pathways (GLP)

Cole Shaw, Richard Larson, Soheil Sibdari

Charlton College of Business, University of Massachusetts, Dartmouth, MA, USA.
Engineering Systems Division, Massachusetts Institute of Technology, Cambridge, MA, USA.
Office of Digital Learning, Massachusetts Institute of Technology, Cambridge, MA, USA.

DOI: 10.4236/ce.2014.513135                

Abstract

The authors propose that personalized learning can be brought to traditional and non-traditional learners through a synchronous learning platform that recommends to individual learners the learning materials best suited for him or her. Such a platform would allow learners to advance towards individual learning goals at their own pace, with learning materials catered to each learner’s interests and motivations. This paper describes the authors’ vision and design for a modular, personalized learning platform called Guided Learning Pathways (GLP), and its characteristics and features. We provide detailed descriptions of and propose frameworks for critical modules like the Content Map, Learning Nuggets, and Recommendation Algorithms. A threaded user scenario is provided for each module to help the reader visualize different aspects of GLP. We discuss work done at MIT to support such a platform.

Keywords

Online Learning, Asynchronous Learning, Personalized Learning, Learning Styles, Pathways, Content Map, Instructional Technology, Recommendation Algorithm

Conflicts of Interest

The authors declare no conflicts of interest.

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