Managing data rather than systems
At RSC London we have become interested in developments in using data to improve education and streamline the business of running of colleges. Years ago when learning providers first replaced paper based processes and teaching resources with digital materials this was done from the point of view of systems. Systems are great but they are not necessarily attuned to the needs of the user. Colleges collected masses of data which was entered it into different systems. The data then lived in silos often synonymous with departments such as Finance, Human Resources, MIS, Estates, Examinations etc. This model probably sounds familiar to anyone working in a learning provider in 2012. However, times are changing. These traditional systems were designed with the data structure first and then the development of the application and then the queries (questions) to ask of the system. Today it is possible to ask a question and then design a data structure to answer that question. This difference is important because these questions are not limited to the data in one system or even the data in one organisation. There are now a range of technologies which are optimised for extracting information from the mass of data held by an organisation. There are now technologies which can pull in external data for both transaction processing and analysis. Furthermore, there is now the capability to identify patterns in the data extracted by machines (data mining), which both reduces the effort but also can identify relationships and trends which a human observer may miss.
Some of the key points to consider are:-
• We can do real time reporting
• We can use machines to mine data for us
• We can enable users to create data for us
• We can correlate and aggregate data from different sources
• The growth in e-learning had provided a rich source of raw data from which to develop analytics which in turn can be used to improve outcomes
• New data structures are available for big data sets and optimised for reporting
• Data can be personalised
• These new data structures will enhance rather than replace exisiting relational databases
This means that learning providers can use analytics and data mining to answer questions like what pathways do learners take through on line resources, what are the group characteristics of at risk learners, what learning activities are key to successful outcomes, what learning activities are popular with learners?, are different learning styles evident in learner interaction with resources?, what are the key attributes of success?
The key questions for us at RSC London are:-
• are these initiatives relevant to what colleges in London are currently planning?
• can FE and HE learning providers utilise big data, data mining and learning analytics?
• are there elements of this approach that would be useful?
• what are the barriers to using data more effectively in colleges?
• what would a good cross organisational data strategy look like?
• how can an effective data strategy support the organisational business objectives?
In order to address these questions RSC London is holding a series of forum meetings this academic year (2012/2013) to gather intelligence from a wide range of post 16 learning providers.
We aim to discuss the issues in detail and produce a template strategy for the effective use of data in a modern educational organisation.
We will use this blog to keep you updated on this project.
Martin Sepion and Julian Bream are advisers at JISC RSC London
For more information contact Martin Sepion (firstname.lastname@example.org) or Julian Bream (email@example.com)
Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics. US Department of Education, October 2012. http://www.ed.gov/edblogs/technology/research/
How Colleges Improve. Ofsted, September 2012.
http://www.ofsted.gov.uk/resources/how-colleges-improve (see section Using Management Information on page 35)
Innovating Pedagogy 2012. Open University Innovation Report 1. July 2012.
Preparing for Data-driven Infrastructure. JISC Observatory Tech Watch Report. Max Hammond. September 2012.
The State of learning Analytics in 2012: A Review and Future Challenges. Rebecca Ferguson. Knowledge Media Institute, The Open University, March 2012. http://kmi.open.ac.uk/publications/pdf/kmi-12-01.pdf