Group items tagged

Knowledge Cartography: Software Tools and Mapping Techniques. (Eds.) Okada, A., Buckingham Shum, S. and Sherborne, T. Springer: Advanced Information and Knowledge Processing Series. ISBN: 978-1-84800-148-0"

Along with about 400 or so others world-wide, I've signed up for the LAK11 (Learning and Knowledge Analytics) MOOC run by George Siemens and colleagues at the Technology Enhanced Knowledge Research Institute (TEKRI) at Athabasca University. We're now into week 2, and I think I'm just about getting into the swing of things.

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.

Social network analysis [SNA] is the mapping and measuring of relationships and flows between people, groups, organizations, computers, URLs, and other connected information/knowledge entities. The nodes in the network are the people and groups while the links show relationships or flows between the nodes. SNA provides both a visual and a mathematical analysis of human relationships. Management consultants use this methodology with their business clients and call it Organizational Network Analysis [ONA].

Stephen Wolfram, creator of Mathematica, talks about his quest to make all knowledge computational -- able to be searched, processed and manipulated. His new search engine, Wolfram Alpha, has no lesser goal than to model and explain the physics underlying the universe.

For the past several years, EDUCAUSE publications have described the emergence of two complementary forces: (1) the growth of "academic analytics" in higher education and the knowledge services needed to support seamless sharing and leveraging of contextualized data/information; and (2) the escalating accountability demands that are driving performance measurement and improvement initiatives. These forces converged in the July/August 2007 issue of EDUCAUSE Review, which showcased their potentially transformative impacts on higher education

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

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.

A solid explanation of learning in a connectivist mindset.

LAK course website.

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 syllabus for the course.

Syllabus of LAK11.

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.

My take on this week's readings and webinar

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