The core proposition is that with the unprecedented amounts of digital data now becoming
available about learners' activities and interests, from educational institutions and elsewhere
online, there is significant potential to make better use of this data to improve learning
outcomes.
By this autumn, every university in England will have published a new set of information about every undergraduate course on offer. These Key Information Sets will include data on areas such as contact hours, graduate salaries and student satisfaction.
But with little fanfare, one institution has already put itself ahead of the game by displaying information about its graduates in a way that could set a benchmark for the sector.
The University of Oxford has created an online tool for comparing data about its graduates' careers and salaries. Tucked away on its main careers website and organised into a set of user-friendly tables, it allows immediate comparisons of the salary and employment status of its alumni from 2008-09 and 2009-10 - undergraduate and postgraduate - sorted by subject area, individual course and even constituent college.
"Meta-data contains a great deal of information, and when gathered together it forms a startlingly clear picture of the person it comes from. A point that Professor César Hidalgo and graduate students Daniel Smilkov and Deepak Jagdish of MIT are trying to get across.
They have created a new program called Immersion. It works by signing you into your Gmail account and collecting only the meta-data from your account usage history. From there you can get a picture of your emailing habits from that single account, and you will be shocked at what you see."
This study is an exploratory case study aimed at analysing one academic's teaching in terms of conceptions of teaching and its effect on student involvement or engagement. The research has been done by drawing on Gonzalez' dimensions of online teaching and data generated by the LMS and data analytics in general. There is growing interest in the use of academic analytics. However, most of the reported work is being done at the level of institutions/groupings of courses. Improving teaching can only be done through changing the conceptions of teaching/learning held by the academics. Can individual teaching staff, reflecting on their courses, learn anything important from examining their courses through analytics? How can this be done effectively? What do they find? This study uses an academic's approach to teaching + use as an indicator of involvement, therefore, an improvement of teaching.
Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
"Google revealed Wednesday that it always requires a search warrant whenever authorities seek access to the content of a user's emails or documents stored in Google's cloud, Wired reported."
Incredible visualisation of the power of metadata and our digital footprint / slimetrail. Zoom in at times to see the level of detail that triangulated phone masts give for location.