Tag Archives: machine learning

#ALN13 Presentation – MOOC Cartography (A Literature Review)

I presented my dissertation literature review at the Sloan International Conference for Online Learning on Wednesday at 12:45pm at the Swan & Dolphin Resort at Walt Disney World.  Several technological glitches threw me off-point, and the topic was expansive by design (perhaps too much), but attendees were positive and responsive to the presentation.

Looking back over my literature review (I completed my oral defense in July of this year), I see not only a great deal of change in the field, but also a greater understanding within myself of the field and its tribulations.  There is a lot of news and hullabaloo about MOOC platforms, MOOC economics, MOOC battles on campuses, but there is still a significant lack of writing on MOOCs from the dominant ideology from a theoretical perspective.  The MOOC as we see it in everyday literature was built by computer scientists interested in artificial intelligence and machine learning.  AI and Machine Learning are byproducts of cognitive science, which has a sister learning theory, cognitive theory.  Obviously the 1960s and 1970s sent the psychologists and educators down one road where a human mind handled information and grew into education theories such as constructivism, social learning theory and activity theory…while the computer scientists went down another road with expert systems and intelligent agents.  But both constitute learning from a certain perspective.
The theoretical voice missing in this MOOC debate is the AI voice.  What is the learning theory behind the AI movement that helped usher MOOCs into existence?  Who are the seminal authors in the field?  Why is learning designed for machines considered applicable to humans? Once all sides have an understanding of these issues we can better engage in dialogue about MOOCs and their role in the future of higher education.
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