Dear friends - I recently read a good article in "Forbes" on "Ten ways big data is revolutionizing manufacturing" by Louis Columbus (see first link). As an academic, I am interested in knowing how Universities can use the big data analytics in its main goal namely education! Interestingly, this topic has been considered by researchers and I have enclosed the second link on this topic by Bill Schmarzo in EMC2.
Bill lists out a sample of big-data powered applications for higher education in Universities, namely:
- Student Acquisition
- Student Course Major Selection
- Student Performance Effectiveness
- Student Work Groups
- Student Retention
- Teacher Effectiveness
- Student Lifetime Value/Booster Effectiveness
- Student Advocacy
- Bookstore Effectiveness
etc.
In summary, Bill points out "There are a multitude of opportunities for universities and colleges to make use of Big Data to improve student and professor satisfaction and performance." As these are topics of pertinent interest to RG friends, I welcome your views on Big Data techniques for Universities. Thank you.
http://www.forbes.com/sites/louiscolumbus/2014/11/28/ten-ways-big-data-is-revolutionizing-manufacturing/
https://infocus.emc.com/william_schmarzo/what-universities-can-learn-from-big-data-higher-education-analytics/
There is increasing competition in the higher education (HE) sector to adopt practices to ensure organisational success at all levels by addressing questions about educating and retaining a larger and more diverse student population, admissions, fund raising and operational efficiency (van Barneveld, Arnold, & Campbell, 2012). In this competitive environment, Higher education institutions (HEIs) have entered the era of ‘big data’ and are collecting large volumes of data relating to their learners and the educational process. These vast amounts of data are stored in the student information systems (SIS); including learner interactions with various educational technologies such as learning/course management systems (LMS/CMS); and in various databases such as admissions files, library records and other systems (Tair & El-Halees, 2012). The extraction of the data derived from these technologies are potentially accessible for data mining, analysis (and interpretation) and has captured the attention of HE administrators, academics, researchers and government agencies.
http://www.ascilite.org/conferences/sydney13/program/papers/Atif.pdf
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