ABSTRACT
This paper will present the general goal of and inspiration for our work on learning analytics, that relies on attention metadata for visualization and recommendation. Through information visualization techniques, we can provide a dashboard for learners and teachers, so that they no longer need to "drive blind". Moreover, recommendation can help to deal with the "paradox of choice" and turn abundance from a problem into an asset for learning.
- C. Anderson. The End of Theory: The Data Deluge Makes the Scientific Method Obsolete. Wired Magazine, 16(7), 2008.Google Scholar
- G. Bell and J. Gemmel. Your life, uploaded. Plume, 2010.Google Scholar
- J. Biehl, M. Czerwinski, G. Smith, and G. Robertson. FASTDash: a visual dashboard for fostering awareness in software teams. In Proceedings of the SIGCHI conference on Human factors in computing systems, pages 1313--1322. ACM, 2007. Google ScholarDigital Library
- D. Boyd. Facebook's Privacy Trainwreck: Exposure, Invasion, and Social Convergence. Convergence: The International Journal of Research into New Media Technologies, 14(1):13--20, 2008.Google Scholar
- C.-H. Chang, M. Kayed, M. R. Girgis, and K. F. Shaalan. A Survey of Web Information Extraction Systems. IEEE Transactions on Knowledge and Data Engineering, 18:1411--1428, 2006. Google ScholarDigital Library
- N. Corthaut, S. Lippens, S. Govaerts, E. Duval, and J.-P. Martens. The integration of a metadata generation framework in a music annotation workflow. Oct. 2009.Google Scholar
- A. Croll and S. Power. Complete Web Monitoring. O'Reilly Media, Inc., 2009.Google ScholarDigital Library
- E. Duval and K. Verbert. On the role of technical standards for learning technologies. IEEE Transactions on Learning Technologies, 1(4):229--234, Oct. 2008. Google ScholarDigital Library
- J. Fry, R. Schroeder, and M. den Besten. Open science in e-science: contingency or policy? JOURNAL OF DOCUMENTATION, 65(1):6--32, 2009.Google ScholarCross Ref
- M. H. Goldhaber. The Attention Economy and the Net. First Monday, 2(4), Apr. 1997.Google Scholar
- S. Govaerts, S. E. Helou, E. Duval, and D. Gillet. A Federated Search and Social Recommendation Widget. In Proceedings of the 2nd International Workshop on Social Recommender Systems (SRS 2011) in conjunction with the 2011 ACM Conference on Computer Supported Cooperative Work (CSCW 2011), pages 1--8, 2011.Google Scholar
- S. Govaerts, K. Verbert, D. Dahrendorf, C. Ullrich, S. Manuel, M. Werkle, A. Chatterjee, A. Nussbaumer, D. Renzel, M. Scheffel, M. Friedrich, J. L. Santos, E. Duval, and E. L.-c. Law. Towards Responsive Open Learning Environments: the ROLE Interoperability Framework. In ECTEL11: European Conference on Technology Enhanced Learning, Lecture Notes in Computer Science, 2011. Google ScholarDigital Library
- S. Govaerts, K. Verbert, J. Klerkx, and E. Duval. Visualizing Activities for Self-reflection and Awareness. In Proceedings of the 9th international conference on Web-based Learning, pages 91--100. Springer, 2010.Google ScholarCross Ref
- T. Hey and A. E. Trefethen. Cyberinfrastructure for e-Science. Science, 308(5723):817--821, 2005.Google ScholarCross Ref
- U. Kirschenmann, M. Scheffel, M. Friedrich, K. Niemann, and M. Wolpers. Demands of Modern PLEs and the ROLE Approach. In M. Wolpers, P. Kirschner, M. Scheffel, S. Lindstaedt, and V. Dimitrova, editors, Sustaining TEL: From Innovation to Learning and Practice, volume 6383 of Lecture Notes in Computer Science, pages 167--182. Springer, 2010. Google ScholarDigital Library
- X. Ma, G. Chen, and J. Xiao. Analysis of An Online Health Social Network. In Proceedings of the 1st ACM International Health Informatics Symposium, pages 297--306. ACM, 2010. Google ScholarDigital Library
- N. Manouselis, H. Drachsler, R. Vuorikari, H. Hummel, and R. Koper. Recommender Systems in Technology Enhanced Learning. In F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, editors, Recommender Systems Handbook, pages 387--415. Springer US, 2011. Google ScholarDigital Library
- M. McKeon. Harnessing the web information ecosystem with wiki-based visualization dashboards. IEEE transactions on visualization and computer graphics, 15(6):1081--8, 2009. Google ScholarDigital Library
- J. Najjar, M. Wolpers, and E. Duval. Contextualized attention metadata. D-Lib Magazine, 13(9/10), Sept. 2007.Google ScholarCross Ref
- X. Ochoa and E. Duval. Use of contextualized attention metadata for ranking and recommending learning objects. In CAMA06: Proceedings of the 1st international workshop on Contextualized attention metadata: collecting, managing and exploiting of rich usage information, pages 9--16, 2006. Google ScholarDigital Library
- H. Põldoja. EduFeedr-following and supporting learners in open blog-based courses. In Proceedings of OpenEd2010, number 2010. Universitat Oberta de Catalunya, 2010.Google Scholar
- E. Pariser. The Filter Bubble: What the Internet Is Hiding from You. Penguin Press, 2011. Google ScholarDigital Library
- K. Popper. The Logic of Scientific Discovery. Routledge, 1959.Google Scholar
- A. S. Rath, D. Devaurs, and S. Lindstaedt. UICO: an ontology-based user interaction context model for automatic task detection on the computer desktop. In Proceedings of the 1st Workshop on Context, Information and Ontologies, CIAO '09, pages 8:1--8:10, New York, NY, USA, 2009. ACM. Google ScholarDigital Library
- C. Romero and S. Ventura. Educational data mining: A survey from 1995 to 2005. Expert Systems with Applications, 33(1):135--146, July 2007. Google ScholarDigital Library
- S. S. Sahoo, A. Sheth, and C. Henson. Semantic provenance for eScience - Managing the deluge of scientific data. IEEE INTERNET COMPUTING, 12(4):46--54, 2008. Google ScholarDigital Library
- J. L. Santos, K. Verbert, S. Govaerts, and E. Duval. Visualizing PLE Usage. In Proceedings of EFEPLE11: 1st Workshop on Exploring the Fitness and Evolvability of Personal Learning Environments. CEUR workshop proceedings, 2011.Google Scholar
- H. Schmitz, M. Scheffel, M. Friedrich, M. Jahn, K. Niemann, and M. Wolpers. CAMera for PLE. In U. Cress, V. Dimitrova, and M. Specht, editors, Learning in the Synergy of Multiple Disciplines, volume 5794 of Lecture Notes in Computer Science, pages 507--520. Springer, 2009. Google ScholarDigital Library
- B. Schwartz. The paradox of choice - Why more is less. HarperCollins, 2007.Google Scholar
- C. Shirky. Here Comes Everybody: The Power of Organizing Without Organizations. Penguin Press, 2008.Google Scholar
- E. Singer. The Measured Life. Technology Review, 2011.Google Scholar
- M. Swan. Emerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-tracking. International journal of environmental research and public health, 6(2):492--525, Feb. 2009.Google ScholarCross Ref
- S. Ternier, K. Verbert, G. Parra, B. Vandeputte, J. Klerkx, E. Duval, V. Ordonez, and X. Ochoa. The Ariadne Infrastructure for Managing and Storing Metadata. IEEE Internet Computing, 13(4):18--25, July 2009. Google ScholarDigital Library
- K. Verbert, E. Duval, H. Drachsler, N. Manouselis, M. Wolpers, R. Vuorikari, and G. Beham. Dataset-driven Research for Improving TEL Recommender Systems. In 1st International Conference on Learning Analytics and Knowledge, Banff, Canada, 2011. Google ScholarDigital Library
- M. Wolpers, J. Najjar, and E. Duval. Workshop report on the international {ACM} workshop on contextualized attention metadata: collecting, managing and exploiting rich usage information (cama 2006), June 2007.Google Scholar
- M. Wolpers, J. Najjar, K. Verbert, and E. Duval. Tracking actual usage: the attention metadata approach. Educational Technology and Society, 10(3):106--121, 2007.Google Scholar
Index Terms
- Attention please!: learning analytics for visualization and recommendation
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