Penetrating the fog: analytics in learning and education
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Published
Dec 31, 2014
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Abstract
In the era of Internet, mobile technologies and open education, the need for changes to improve the efficiency and quality of higher education has become crucial.
Big data and analytics can contribute to these changes and reshape the future of higher education. Basing decisions on data and evidence seems stunningly obvious. However, higher education, a field that gathers an astonishing array of data about its “customers,” has traditionally been inefficient in its data use, often operating with substantial delays in analyzing readily evident data and feedback. In this paper, the value of Analytics for Higher Education is discussed, and a model of learning analytics development is presented. The main pedagogical and ethical issues about the use of learning analytics are also pointed out, since learning is messy, and using analytics to describe learning is not easy. Nevertheless, Learning Analytics can penetrate the fog of uncertainty around the future of higher education, and shed light on how to allocate resources, develop competitive advantages, and most important, improve the quality and value of the learning experience.
Big data and analytics can contribute to these changes and reshape the future of higher education. Basing decisions on data and evidence seems stunningly obvious. However, higher education, a field that gathers an astonishing array of data about its “customers,” has traditionally been inefficient in its data use, often operating with substantial delays in analyzing readily evident data and feedback. In this paper, the value of Analytics for Higher Education is discussed, and a model of learning analytics development is presented. The main pedagogical and ethical issues about the use of learning analytics are also pointed out, since learning is messy, and using analytics to describe learning is not easy. Nevertheless, Learning Analytics can penetrate the fog of uncertainty around the future of higher education, and shed light on how to allocate resources, develop competitive advantages, and most important, improve the quality and value of the learning experience.
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Articles - Special Issue
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References
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Morris, L. V., Finnegan, C., & Wu, S. (2005). Tracking Student Behavior, Persistence, and Achievement in Online Courses. The Internet and Higher Education, 8(3), 221-231.
Scism, L., & Maremont, M. (2010, November 19). Insurers Test Data Profiles to Identify Risky Clients. The Wall Street Journal. Retrieved from http://online.wsj.com/article/SB 10001424052748704648604575620750998072986.html
Thompson, C. (2011, July 15). How Khan Academy Is Changing the Rules of Education. Wired. Retrieved from http://www.wired. com/magazine/2011/07/ff_khan/all/1
Anderson, P. W. (1972). More Is Different. Science, 177(4047), 393-396. doi: 10.1126/science.177.4047.393
Brynjolfsson, E., Hitt, L. M., & Heekyung, H. K. (2011). Strength in Numbers: How Does Data-Driven Decision making Affect Firm Performance? Social Science Research Network - Working Paper Series. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_ id=1819486
Campbell, J. P., DeBlois, P. B., & Oblinger, D. G. (2007). Academic Analytics: A New Tool for a New Era. EDUCAUSE Review, 42(4), 40-57.
Gelernter, D. (1999, December 31). The Second Coming: A Manifesto. Edge.org. Retrieved from http://edge.org/conversation/ the-second-coming-a-manifesto
Gross, W. H. (2011, July). School Daze, School Daze, Good Old Golden Rule Days. Pimco, All Investment Outlook. Retrieved from http://www.pimco.com/EN/Insights/Pages/ School-Daze- School-Daze-Good-Old-Golden-Rule-Days.aspx
Head, S. (2011, January 13). The Grim Threat to British Universities. New York Review of Books. Retrieved from http://www.nybooks.com/articles/archives/2011/jan/13/gri m-threat-british-universities/?page=1
Kirkpatrick, M. (2010, August 12). China Moves to Dominate the Next Stage of the Web. Readwrite. Retrieved from http:// www.readwriteweb.com/archives/china_moves_to_dominate_ the_next_stage_of_the_web_internet_of_things.php
Lacy, S. (2011, April 10). Peter Thiel: We’re in a Bubble and It’s Not the Internet, It’s Higher Education. Retrieved from http://techcrunch.com/2011/04/10/peter-thiel-were-in-abubble- and-its-not-the-internet-its-higher-education/
Macfadyen, L. P., & Dawson, S. (2010). Mining LMS data to develop an “early warning system” for educators: A proof of concept. Computers & Education, 54(2), 588-599.
Manyika, J. (2011). Big Data: The Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute. Insights & Publications. Retrieved from http://www.mckinsey. com/insights/business_technology/big_data_the_next _frontier_for_innovation
Mayer, M. (2010, May 4). Innovation at Google: the physics of data [video]. Retrieved from http://www.slideshare.net/PARCInc/ innovation-at-google-the-physics-of-data
Morris, L. V., Finnegan, C., & Wu, S. (2005). Tracking Student Behavior, Persistence, and Achievement in Online Courses. The Internet and Higher Education, 8(3), 221-231.
Scism, L., & Maremont, M. (2010, November 19). Insurers Test Data Profiles to Identify Risky Clients. The Wall Street Journal. Retrieved from http://online.wsj.com/article/SB 10001424052748704648604575620750998072986.html
Thompson, C. (2011, July 15). How Khan Academy Is Changing the Rules of Education. Wired. Retrieved from http://www.wired. com/magazine/2011/07/ff_khan/all/1