skip to main content
10.1145/2567574.2576773acmotherconferencesArticle/Chapter ViewAbstractPublication PageslakConference Proceedingsconference-collections
research-article

Learning analytics for the social media age

Published:24 March 2014Publication History

ABSTRACT

In just a short period of time, social media have altered many aspects of our daily lives, from how we form and maintain social relationships to how we discover, access and share information online. Now social media are also beginning to affect how we teach and learn in this increasingly interconnected and information-rich world. The panelists will discuss their ongoing work that seeks to understand the affordances and potential roles of social media in learning, as well as to determine and provide methods that can help researchers and educators evaluate the use of social media for teaching and learning based on automated analyses of social media texts and networks. The panel will focus on the first phase of this five-year research initiative "Learning Analytics for the Social Media Age" funded by the Social Science and Humanites Research Council of Canada (2013--2018).

References

  1. Cho, H., Gay, G., Davidson, B. and Ingraffea, A. 2007. Social Networks, Communication Styles, and Learning Performance in a CSCL Community. Computers and Education, 49, 2, 309--329. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Ebner, M., Lienhardt, C., Rohs, M., and Meyer, I. 2010. Microblogs in Higher Education -- A chance to facilitate informal and process-oriented learning? Computers and Education, 55, 1, 92--100. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Gruzd, A. 2009. Studying Collaborative Learning Using Name Networks. Journal of Education for Library and Information Science, 50, 4, 243--253.Google ScholarGoogle Scholar
  4. Gruzd, A. 2011. Exploring Virtual Communities with the Internet Community Text Analyzer (ICTA). In Ben Kei Daniel (Ed.), Handbook of Research on Methods and Techniques for Studying Virtual Communities: Paradigms and Phenomena. IGI Global, 205--223.Google ScholarGoogle Scholar
  5. Gruzd, A. and Sedo, D. R. 2012. #1b1t: Investigating Reading Practices at the Turn of the Twenty-first Century. Journal of Studies in Book Culture/Mémoires du Livre 3, 2.Google ScholarGoogle Scholar
  6. Gruzd, A., Wellman, B., and Takhteyev, Y. 2011. Imagining Twitter as an Imagined Community. American Behavioral Scientist, 55, 10, 1294--1318. http://abs.sagepub.com/content/early/2011/07/23/0002764211409378.abstractGoogle ScholarGoogle ScholarCross RefCross Ref
  7. Haythornthwaite, C. 1998. A Social Network Study of the Growth of Community among Distance Learners. Information Research, 4, 1, 4--1.Google ScholarGoogle Scholar
  8. Haythornthwaite, C. 1999. Collaborative Work Networks among Distributed Learners. Proceedings of the 32nd Hawaii International Conference on System Sciences. Los Alamitos, CA: IEEE Computer Society. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Haythornthwaite, C. 2001. Exploring Multiplexity: Social Network Structures in a Computer-Supported Distance Learning Class. The Information Society, 17, 3, 211--226.Google ScholarGoogle ScholarCross RefCross Ref
  10. Haythornthwaite, C. (forthcoming). Learning Networks. Encyclopedia of Social Networks and Data Mining. Springer.Google ScholarGoogle Scholar
  11. Haythornthwaite, C. and de Laat, M. 2011. Social Network Informed Design for Learning with Educational Technology. In A. D. Olofsson and J. O. Lindberg, (Eds.) Informed Design of Educational Technologies in Higher Education: Enhanced Learning and Teaching. IGI Global, 352--374.Google ScholarGoogle Scholar
  12. Haythornthwaite, C., de Laat, M. and Dawson, S. (Eds.) 2013. Learning Analytics. American Behavioral Scientist, whole issue.Google ScholarGoogle Scholar
  13. Junco, R., Elavsky, C. M., and Heiberger, G. 2012. Putting Twitter to the Test: Assessing Outcomes for Student Collaboration, Engagement and Success. British Journal of Educational Technology.Google ScholarGoogle Scholar
  14. Lange, D. D., Agneessens, F. and Waege, H. 2004. Asking Social Network Questions: A Quality Assessment of Different Measures. MetodološkiZvezki, 1, 2, 351--378.Google ScholarGoogle Scholar
  15. Moran, M., Seaman, J., and Tinti-Kane, H. 2010. Teaching, Learning and Sharing: How Today's Higher Education Faculty Use Social Media. Pearson Learning Solutions. Retrieved May 10, 2011 from http://www.pearsonlearningsolutions.com/educators/pearson-social-media-survey-2011-color.pdfGoogle ScholarGoogle Scholar
  16. Reyes, P. and Tchounikine, P. 2005. Mining Learning Groups' Activities in Forum-Type Tools. Proceedings of the 2005 Conference on Computer Support for Collaborative Learning: Learning 2005: the Next 10 Years! International Society of the Learning Sciences, 509--513. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Schroeder, A., Minocha, S., and Schneider, C. 2010. The Strengths, Weaknesses, Opportunities and Threats of Using Social Software in Higher and Further Education Teaching and Learning. Journal of Computer Assisted Learning, 26, 3, 159--174.Google ScholarGoogle ScholarCross RefCross Ref
  18. Siemens, G. 2010. What are Learning Analytics? Retrieved October 6, 2012 from http://www.elearnspace.org/blog/2010/08/25/what-are-learning-analytics/Google ScholarGoogle Scholar

Index Terms

  1. Learning analytics for the social media age

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      LAK '14: Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
      March 2014
      301 pages
      ISBN:9781450326643
      DOI:10.1145/2567574

      Copyright © 2014 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 24 March 2014

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      LAK '14 Paper Acceptance Rate13of44submissions,30%Overall Acceptance Rate236of782submissions,30%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader