NotesFAQContact Us
Search Tips
Peer reviewed Peer reviewed
PDF on ERIC Download full text
ERIC Number: EJ1062785
Record Type: Journal
Publication Date: 2014
Pages: 9
Abstractor: As Provided
ISSN: EISSN-2161-4210
Technology for Mining the Big Data of MOOCs
O'Reilly, Una-May; Veeramachaneni, Kalyan
Research & Practice in Assessment, v9 p29-37 Win 2014
Because MOOCs bring big data to the forefront, they confront learning science with technology challenges. We describe an agenda for developing technology that enables MOOC analytics. Such an agenda needs to efficiently address the detailed, low level, high volume nature of MOOC data. It also needs to help exploit the data's capacity to reveal, in detail, how students behave and how learning takes place. We chart an agenda that starts with data standardization. It identifies crowd sourcing as a means to speed up data analysis of forum data or predictive analytics of student behavior. It also points to open source platforms that allow software to be shared and visualization analytics to be discussed.
Virginia Assessment Group. Tel: 504-314-2898; Fax: 504-247-1232; e-mail:; Web site:
Publication Type: Journal Articles; Reports - Descriptive
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A