SNAPP

SNAPP publications:

1. Bakharia, A. & Dawson, S. (2011). SNAPP: A Bird’s-Eye View of Temporal Participant Interaction. Learning Analytics and Knowledge 2011, Banff, Canada
2. Dawson, S., Macfadyen, L., Lockyer, L., & Mazzochi-Jones, D. (2011). Using Social Network Metrics to Assess the Effectiveness of Broad-Based Admission Practices. Australasian Journal of Educational Technology, 27(1), 16-27.
3. Dawson, S., Bakharia, A., & Heathcote, E. (2010). SNAPP: Realising the affordances of real-time SNA within networked learning environments. Networked Learning – Seventh International Conference, Aalborg, Denmark
4. Macfadyen, L., & Dawson, S. (2010). Mining LMS data to develop an “early warning system” for educators: A proof of concept. Computers & Education, 54(2), 588-599.
5. Dawson, S., Bakharia, A., Lockyer, L., & Heathcote, E. (2010). ‘Seeing’ Networks: Visualising and evaluating student learning networks. Australian Learning and Teaching Council, Canberra, Australia.
6. Dawson, S. (2009). ‘Seeing’ the learning community: An exploration of the development of a resource for monitoring online student networking. British Journal of Educational Technology, 41(5), 736-752.
7. Dawson, S., Macfadyen, L., & Lockyer, L. (2009). Learning or performance: Predicting drivers of student motivation. Same places, different spaces. Proceedings ascilite 2009., Auckland, NZ.
8. Dawson, S. (2008). A study of the relationship betweeen student social networks and sense of community. Educational Technology and Society, 11(3), 224–238.
9. Dawson, S., & McWilliam, E. (2008). Investigating the application of IT generated data as an indicator of learning and teaching performance. Canberra: Australian Learning and Teaching Council.
10. Dawson, S., McWilliam, E., & Tan, J. (2008). Teaching Smarter: How mining ICT data can inform and improve learning and teaching practice. Hello where are you in the landscape of educational technology. ASCILITE 2008, Melbourne, Australia.

Other publications about social networks and learning analytics

1. Brown, J.S. and Adler, A.P., (2008). Minds on fire: Open education, the long tail, and learning 2.0. EDUCAUSE Review, 43(1): p. 16-32.
2. Campbell, J., De Blois, P.B., and Oblinger, D., (2007). Academic analytics: A new tool for a new era. EDUCAUSE Review, 42(4): p. 42-57.
3. Campbell, J. and Oblinger, D., (2007). Academic analytics, EDUCAUSE.
4. Cho, H., et al., (2007). Social networks, communication styles, and learning performance in a CSCL community. Computers and Education, 49(2): p. 309-329.
5. Cho, Y.H., Kim, J.K. and Kim, S.H. (2002). A personalized recommender system based on web usage mining and decision tree induction. Expert Systems with Applications 23 (3), pp. 329-42.
6. Cho, Y. H. and Kim, J.K. (2004). Application of web usage mining and product taxonomy to collaborative recommendations in e-commerce, Expert System with Applications 26, pp. 233-246
7. Corbitt, T. (2003). Business intelligence and data mining. Management Services. Nov 2003, p. 18
8. Eckerson, W. W. (2006). Performance dashboards: Measuring, monitoring, and managing your business. Hoboken, New Jersey: John Wiley & Sons
9. Educause, 2010. 7 Things you should know about analytics, EDUCAUSE 7 things you should know series. http://www.educause.edu/ir/library/pdf/ELI7059.pdf
10. Fritz, J.(2010), Classroom walls that talk: Using online course activity data of successful students to raise self-awareness of underperforming peers, Internet and Higher Education doi:10.1016/j.iheduc.2010.07.007
11. Goldstein, P.J. and Katz, R.N., (2005). Academic analytics: The uses of management information and technology in higher education, EDUCAUSE Centre for Applied Research.
12. Haythornthwaite, C., (2006). Learning and knowledge networks in interdisciplinary collaborations. Journal of the American Society for Information Science and Technology, 57(8): p. 1079-1092
13. Mazza R., and Dimitrova, V. (2004). Visualising student tracking data to support instructors in web-based distance education, WWW Alt. ‘04: Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters. New York: ACM Press, pp. 154-161. http://www.iw3c2.org/WWW2004/docs/2p154.pdf
14. Mazza, R. and Dimitrova, V., (2007). CourseVis: A graphical student monitoring tool for supporting instructors in web-based distance courses. International Journal of Human-Computer Studies, 65(2): p. 125-139.Norris, D., Baer, L., Leonard, J., Pugliese, L. and Lefrere, P. (2008). Action Analytics: Measuring and Improving Performance That Matters in Higher Education, EDUCAUSE Review 43(1). http://www.educause.edu/EDUCAUSE+Review/EDUCAUSEReviewMagazineVolume43/ActionAnalyticsMeasuringandImp/162422
15. Norris, D., Baer, L., Leonard, J., Pugliese, L. and Lefrere, P. (2008). Framing Action Analytics and Putting Them to Work, EDUCAUSE Review 43(1). http://www.educause.edu/EDUCAUSE+Review/EDUCAUSEReviewMagazineVolume43/FramingActionAnalyticsandPutti/162423
16. Oblinger, D. G. and Campbell, J. P. (2007). Academic Analytics, EDUCAUSE White Paper. http://www.educause.edu/ir/library/pdf/PUB6101.pdf.
17. Phillips, R.A. (2006). Tools used in Learning Management Systems: analysis of WebCT usage logs. In proceedings for, 23rd Annual Conference of the Australasian Society for Computers in Learning in Tertiary Education: Who’s Learning? Whose Technology? Sydney: Sydney University Press.Reffay, C. and Chanier, T. (2003). How social network analysis can help to measure cohesion in collaborative distance-learning. In proceedings for, Computer Support for Collaborative Learning. Dordrecht, Netherlands: Kluwer Academic Publishers.Wang, A.Y. and Newlin, M.H. ( 2002). Predictors of Performance in the Virtual Classroom, The Journal. http://www.thejournal.com/articles/15973
18. Wang, T. and Ren, Y. (2009). Research on Personalized Recommendation Based on Web Usage Mining Using Collaborative Filtering Technique, WSEAS TRANSACTIONS on INFORMATION SCIENCE and APPLICATIONS 1(6).