Group items tagged

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.

Hilary Mason presents the history of machine learning covering some of the most significant developments taking place over the last two decades, especially the fundamental math and algorithmic tools employed. She also exemplifies how machine learning is used by bit.ly to discover various statistical information about users.

Papamitsiou, Z., & Economides, A. (2014). Learning Analytics and Educational Data Mining in Practice: A Systematic Literature Review of Empirical Evidence. Educational Technology & Society, 17 (4), 49-64. This paper aims to provide the reader with a comprehensive background for understanding current knowledge on Learning Analytics (LA) and Educational Data Mining (EDM) and its impact on adaptive learning. It constitutes an overview of empirical evidence behind key objectives of the potential adoption of LA/EDM in generic educational strategic planning. We examined the literature on experimental case studies conducted in the domain during the past six years (2008-2013). Search terms identified 209 mature pieces of research work, but inclusion criteria limited the key studies to 40. We analyzed the research questions, methodology and findings of these published papers and categorized them accordingly. We used non-statistical methods to evaluate and interpret findings of the collected studies. The results have highlighted four distinct major directions of the LA/EDM empirical research. We discuss on the emerged added value of LA/EDM research and highlight the significance of further implications. Finally, we set our thoughts on possible uncharted key questions to investigate both from pedagogical and technical considerations.

. I think the interesting thing about Learning Analytics is it's one of those areas we think will be important, but we're not quite sure what it is yet, so there's room to explore

Evaluating training: some alternatives to the Kirkpatrick method

My goal with practical learning analytics is to provide access to data in ways that an average teacher, with no special training, can leverage in order to help her students succeed. This is, of course, an extremely tall order

Data analytics is shorthand for the method of warehousing, organizing, and interpreting the massive amounts of data accrued by online learning platforms and student information systems - now as elemental to higher education as classrooms and filing cabinets - in hopes of learning more about what makes students successful, then giving instructors (and the platforms themselves) the chance to nudge those students accordingly.

Social and technological networks don't have a centre. When we learn in a classroom or in a learning management system (LMS), a central place exists where we can go for readings and

The first impressions I have of a venture like this are positive but not without hesitation. I won't conceal it from you that it is less the topic of "learning analytics" that's of interest to me (although I am ready to learn something about this too), but the course itself. This is also where my hesitation lies, but we shall talk more about this later in the course.

I think there is a potential to inject a feedback mechanism in this course, and any MOOC for that matter, with regard to the helpfulness of reading material in the Syllabus.  I think that would especially suit the Learning & Knowledge Analytics course.

Slides from Feb 18, 2011 web conference Learning Analytics: Notes on the Future Simon Buckingham Shum, Knowledge Media Institute Open University UK

One of the less successful experiments seems to be attempts to integrate VLEs, especially Moodle, within MOOCs.(was My experience with LAK11)

Wikipedia page on learning analytics. Note: "please help improve this article by expanding it"

Is Goodhart's law relevant when thinking about Learning Analytics

My take on this week's readings and webinar

I've been following developments in intelligent tutoring systems for a while,  and find it interesting to see how researchers are combining artificial intelligence, learning theory, affective computing, and sensor networks to create applications that might prove to be useful and effective.

"The Effective Lifelong Learning Inventory (ELLI) research first identified, then devised a scientifically rigorous way of assessing the essential characteristics of effective lifelong learners." Shared during Feb 18, 2011 web conference with Simon Buckingham Shum