Elearnspace

New MOOC: Data, Analytics, & Learning

I’ve run a range of open courses on a fairly broad range of platforms: D2L, Moodle, Instructure, a mess of social media tools, and (most frequently) with Stephen Downes’ gRSShopper.
This fall, together with colleagues, I’ll be offering an open course on edX: Data, Analytics, and Learning. From the description:

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MOOCs: Scaling Corporate Learning

While MOOCs have gained the interest and attention of higher education, they have failed to make much of an impact on corporate learning. That is starting to change. Over the past year, organizations such as Google, GE, Cisco, McAfee, Bank of America, AXA, and AT&T have started to experiment with MOOCs. Non-profits and NGOs such as Linux Foundation, WEF, OECD, Red Cross, and others have also started experimenting with large scale online learning.

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MOOCs: Expectations and Reality

In spite of (because of?) significant media attention, the dialogue around MOOCs has been more theoretical than informed. Research is lagging well behind rhetoric. Fortunately, that is starting to change. Fiona Hollands and Devayani Tirthali from Teachers College, Columbia University, have released what is the most informed analysis of MOOCs that I have read to date: MOOCs: Expectations and Reality (.pdf).

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Personal Learner Knowledge Graph

The entire education system is focused on content/curriculum. Content drives almost all academic conversations. Content is the work of designers (how should we structure this), academics (what and how should I teach), administrators (how can we prove [to some random agency] that we taught students stuff that matters), and employers (this is the content I want potential employees to master).

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Multiple pathways: Blending xMOOCs & cMOOCs

I’m running a MOOC on edX in fall on Data Analytics & Learning (registration will be open soon). As part of this process, we organized a designjam recently bringing together 20 or so folks to think through the design process. I’ll post separately on this event. For now, I just want to highlight one aspect of the meeting: the difference between xMOOCs & cMOOCs and possible ways to blend them.

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Journal of Learning Analytics

Interest in learning analytics is growing. It’s a data centric world and will only become more so in the future. From my biased view, it is critical that educators are aware of the role of analytics in education because of the heaving influence algorithms, data, and analytics have on teaching, learning, and decision making in schools, colleges/universities, and corporate settings.

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Thoughts on Connectivism

Stephen Downes has posted some thoughts on connectivism.
David Wiley replies, saying while interesting, connectivism is incomplete (which I think is great – if it’s complete, we can stop working on it).
In 2008, I posted a short presentation on the various ways in which learning is networked: neural, conceptual, and external.

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Open Learning Analytics

The future of systems such as business, government, and education will be data centric. Historically, humanity has made sense of the world through discourse, dialogue, artifacts, myth, story, and metaphor. While those sensemaking approaches won’t disappear, they will be augmented by data and analytics.

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What will universities monetize in the future?

Universities do more than teach. Research is one of the most important activities of higher education. From the lens of students and society, however, the teaching and learning process and what it costs, is the primary focus.

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University of Texas at Arlington

This is likely not news to most readers as it has been posted in various blogs, forums, and announced at the MOOC Research conference in December, but I have applied, and received approval, for a leave of absence from Athabasca University to establish and set up a digital learning research lab at University of Texas at Arlington. I will be based in Arlington, but will continue to work with my AU doctoral students.

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