Abstract
Massive Open Online Courses (MOOCs) allow students to study online courses without requiring previous experience or qualifications. This offers students the freedom to study a wide variety of topics, freed from the curriculum of a degree programme for example; however, it also poses a challenge for students in terms of making connections between individual courses. This paper examines the subjects which students at one MOOC platform (Coursera) choose to study. It uses a social network analysis based approach to create a network graph of co-studied subjects. The resulting network demonstrates a good deal of overlap between different disciplinary areas. Communities are identified within the graph and characterised. The results suggests that MOOC students may not be seeking to replicate degree-style courses in one specialist area, which may have implications for the future moves toward ‘MOOCs for credit’.
Highlights
In the past two years, massive open online courses (MOOCs) have entered the mainstream, attracting several million students [1] and garnering intense media attention.One of the key characteristics of massive open online courses is the removal of entry pre-requisites to courses [2], allowing students to formulate their own learning pathways, free of the constraints of a modular degree programme
This study seeks to explore the patterns in enrolment of MOOC students on different courses, through social network analysis of courses which Coursera students with public profiles are enrolled upon
In applying social network analysis to the MOOC courses which are co-studied by students with public profiles at Coursera, this study has identified communities of subjects which tend to be chosen together by students
Summary
One of the key characteristics of massive open online courses is the removal of entry pre-requisites to courses [2], allowing students to formulate their own learning pathways, free of the constraints of a modular degree programme. This may be liberating and potentially problematic for students in order to determine how to fit individual courses together into a coherent whole. Computing for Data Johns Hopkins Univer- Analysis sity 24/09/2012. Startup Engineering Stanford University 17/06/2013 431 Data Analysis. 685.5 to gain from participating in MOOCs is a subject for further research, and the implications in turn for formal curriculum design is an open question
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