Big data in computer science education research

Orit Hazzan, Clifford A. Shaffer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Recent years have seen the emergence of applications and concepts that rely on the involvement of the general public (the "crowd")and, consequently, create big data (e.g., MOOCs, search engines, crowd sourcing, crowd funding, citizen/crowd science, and more). Education in particular is changing dramatically with the use of online resources and courses that generate large streams of data. In this special session, we ask: What research questions in computer science education can be explored using big data? And how can computer science education researchers apply big data analysis to support education in other disciplines? To answer these and related questions, we focus in this special interactive session on how computer science education research can be promoted by integrating big data into the research process.

Original languageEnglish
Title of host publicationSIGCSE 2015 - Proceedings of the 46th ACM Technical Symposium on Computer Science Education
EditorsAdrienne Decker, Kurt Eiselt, Jodi Tims, Carl Alphonce
Pages591-592
Number of pages2
ISBN (Electronic)9781450329668
DOIs
StatePublished - 24 Feb 2015
Event46th SIGCSE Technical Symposium on Computer Science Education, SIGCSE 2015 - Kansas City, United States
Duration: 4 Mar 20157 Mar 2015

Publication series

NameSIGCSE 2015 - Proceedings of the 46th ACM Technical Symposium on Computer Science Education

Conference

Conference46th SIGCSE Technical Symposium on Computer Science Education, SIGCSE 2015
Country/TerritoryUnited States
CityKansas City
Period4/03/157/03/15

Keywords

  • Big data
  • Citizen science
  • Computer science education
  • Research in computer science education

All Science Journal Classification (ASJC) codes

  • Education
  • Computer Science (miscellaneous)

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