learning analytics

In my Palo Alto neighborhood, tech companies spring up (and, often, disappear) frequently. Not too long ago, Junyo appeared around the corner from my house, and now the sign on the door has been expanded to

Junyo Learning Analytics

Ah, learning analytics is a technical term, one that I hadn’t encountered before. It’s a N + N compound glossable as ‘analytics having to do with learning’. So that drives things back to analytics.

The Wikipedia entry for analytics tells us:

Analytics is the application of computer technology, operational research, and statistics to solve problems in business and industry. Analytics is carried out within an information system: while, in the past, statistics and mathematics could be studied without computers and software, analytics has evolved from the application of computers to the analysis of data and this takes place within an information system or software environment. Mathematics underpins the algorithms used in analytics – the science of analytics is concerned with extracting useful properties of data using computable functions (see Church-Turing thesis), and typically will involve extracting properties from large data bases (see data mining). Analytics therefore bridges the disciplines of computer science, statistics, and mathematics.

You can sort of get a feel for the field from this.

Then learning analytics, which deals with education, both learning and teaching:

Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs. A related field is educational data mining. (Wikipedia link)

In more detail, from the Elearnspace site:

Learning analytics is the use of intelligent data, learner-produced data, and analysis models to discover information and social connections, and to predict and advise on learning. EDUCAUSE’s Next Generation learning initiative offers a slightly different definition “the use of data and models to predict student progress and performance, and the ability to act on that information”. Their definition is cleaner than the one I offer, but, as I’ll detail below, is intended to work within the existing educational system, rather than to modify it. I’m interested in how learning analytics can restructure the process of teaching, learning, and administration.

LA relies on some of the concepts employed in web analysis, through tools like Google Analytics, as well as those involved in data mining (see educational data mining). These analytic approaches try to make sense of learner activity (through clicks, attention/focus heat maps, social network analysis, recommender systems, and so on). Learning analytics is broader, however, in that it is concerned not only with analytics but also with action, curriculum mapping, personalization and adaptation, prediction, intervention, and competency determination.

Though the field grows out of several earlier disciplines and research areas, its appearance as a self-aware area seems to be recent; the 1st International Conference on Learning Analytics & Knowledge took place only last year.

Finally, to Junyo, whose motto on the website is:

We make learning data actionable and fun to improve each student’s achievement.

In more detail, but still in earnest prospectusese:

We strive to deliver an experience that is easy, enjoyable, and requires no training. Visualizations, intelligent insights, and recommendations empower educators to make smart decisions and help students learn more every day.

We partner with schools, publishers, and online learning providers that are eager to use data to improve student outcomes, and to enlighten and inspire young minds.

The location, next to the Gordon Biersch brew restaurant, has been rented to a series of businesses. Before Junyo, two shoe stores in succession.


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