New Metrics Providers Help Keep Libraries in the Research-Tracking Game Chronicle of Higher Education (subscription) He is one of the founders of Plum Analytics, a service that tracks different measures of research impact, including altmetrics.
Desire2Learn has introduced new functionality to its learning management suite, including new predictive analytics tools, improvements on the mobile and e-portfolio fronts, and an important addition in the area of accessibility.
I chose “data” as one of the top trends of 2011, and the opening line of that article reads “If data was an important trend for 2011, I predict it will be even more so in 2012.” Indeed. There’s a great deal that happened in 2012 that’s a continuation of what we saw last year — enough that I could probably just copy-and-paste from the article I wrote back then:
Via Kim Flintoff
Predictive analytics encompasses a variety of statistical techniques from modeling, machine learning, data mining and game theory that analyze current and historical facts to make predictions about future events.
Do you want to learn more about how to use the library and the internet effectively to do research? Do you want your students to learn more about how to use the library and the internet effectively to do research?
This guide has been designed to provide an overview of resources available for study and research in epidemiology and statistics. Information on data analysis and data visualization tools are provided.
‘Open data’ is the belief that information should be freely and easily available for everyone to use and re-use as they wish without the need to comply with complex licensing requirements.
Governments around the world have been investing heavily in opening up data in this way – the data.gov.uk portal was launched in 2009, and at the start of 2013 the European Union (EU) Commission began the rollout of its own open data portal. Rachel Bruce, director of digital infrastructure innovation at Jisc says: “For government bodies, opening up access to data allows them to be seen as transparent in their decision-making and dealings. It also helps to engage their citizens and speed up innovative processes.”
The message boards on the data.gov.uk website show that not-for-profit organisations and commercial operations are using open data to develop products and services – it’s being used in data modelling for insurance purposes, to spot and analyse public health trends, and to map crime and accident blackspots.
The use of big data and analytics to predict student success presents unique ethical questions for higher education administrators relating to the nature of knowledge; in education, "to know" entails an obligation to act on behalf of the student. The Potter Box framework can help administrators address these questions and provide a framework for action.
So where will online growth come from? A report last week from Moody’s indicated that massive open online courses (MOOCs) represent a “pivotal development” in higher education and could revolutionize the industry.
A ton of educational innovations are coming down the pike as a result of big data, which effectively turns “learning” – heretofore somewhat ineffable – into a living, breathing body that can be monitored: closer to medicine than education has ever been.
It is for this reason – the “massive” element – that MOOCs may prove to be important. With mass comes big data. And with big data comes better product and engagement of traditional age students. But massive courses aren’t the only path to big data. Smaller courses with much higher completion rates could prove to be a better source of data.
Regardless, in the coming years education research will allow us to check the two hard boxes: product and engagement of traditional age students. Real growth for online education – what we call Online Education 2.0 – will come when we’re firing on all four cylinders, not just two.
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