Learning analytics 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. For general audience introductions, see: The Educause Learning Initiative Briefing The Educause Review on Learning analytics And the UNESCO "Learning Analytics Policy Brief" (2012) What is Learning Analytics? The definition and aims of Learning Analytics are contested. But this definition has been criticised: "I somewhat disagree with this definition - it serves well as an introductory concept if we use analytics as a support structure for existing education models. A more holistic view than a mere definition is provided by the framework of learning analytics by Greller and Drachsler (2012). It uses a general morphological analysis (GMA) to divide the domain into six "critical dimensions". History Software
Adam Cooper’s Work Blog » A Seasonal Sociogram for Learning Analytics Research SoLAR, the Society for Learning Analytics Research has recently made available a dataset covering research publications in learning analytics and educational data mining and issued the LAK Data Challenge, challenging the community to use the dataset to answer the question: What do analytics on learning analytics tell us? How can we make sense of this emerging field’s historical roots, current state, and future trends, based on how its members report and debate their research? Thanks to too many repeats on the TV schedule I managed to re-learn a bit of novice-level SPARQL and manipulate the RDF/XML provided into a form I can handle with R. Now, I’ve had a bit of a pop at the sociograms – i.e. visualisations of social networks – in the past but they do have their uses and one of these is getting a feel for the shape of a dataset that deals with relations. And with it being the Christmas season, the colour scheme chose itself. So, what does it tell me? Am I any the wiser? Merry Christmas!
index Analytics Training JEDM - Journal of Educational Data Mining The Journal of Educational Data Mining (JEDM; ISSN 2157-2100 ) is an international and interdisciplinary forum of research on computational approaches for analysing electronic repositories of student data to answer educational questions. Educational Data Mining is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings in which they learn. The journal welcomes basic and applied papers describing mature work involving computational approaches of educational data mining. Specifically, it welcomes high-quality original work including but not limited to the following topics: From time to time, the journal also welcomes survey articles, theoretical articles, and position papers, in as much as these articles build on existing work and advance our understanding of the challenges and opportunities unique to this area of research. Associate Editors :
Etherpad MOOC and Mookies: The Connectivism & Connective Knowledge Online Co... Learning data visualization I listen to a lot of podcasts. They make my workouts much more enjoyable. For the most part though, I only listen to ones about sports and more general podcasts about design, technology, and working from home. Neither had experience producing podcasts before this, so it was rough around the edges at first. In the most recent episode, with Andy Kirk, they discuss the most common question from people new to the field: how to get started. One thing I'd add (that maybe I missed as cars drove past me) is that it's important to establish what you want to learn visualization for.