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MOOC Research Learning Curves

03 Dec

By Marshall Thomas

MOOCs are at an interesting phase in their evolution. With MOOC mania subsiding somewhat, the field is coalescing around aspirational goals to make MOOCs more engaging, interactive, personalized, and sustainable.

Some thought leaders are calling it MOOC 2.0. Just as MOOC 1.0 research stimulated a healthy debate about the market for free online courses, MOOC 2.0 is motivating a debate about best practices in teaching and learning at a massive scale. Studies on retention rates and the unique MOOC audience of lifelong learners reshaped our thinking, and now we have a bit more data to go on when it comes to bringing teaching back to the fore in higher ed (yes, ed stands for education)!

At HarvardX we’re increasingly interested in how MOOC data can guide us towards better teaching. In fact, we aim to learn from research on every MOOC that we build to continuously improve our teaching on campus and online. But to understand what helps students learn and what doesn’t, to get a handle on cause and effect, we have to shift from observational studies to building experimentation into the very DNA of our courses.

This necessitates increasing collaboration between the faculty, professional learning researchers, and instructional designers. For course teams and professors with little experience in educational research, the task seems daunting: Where do I even begin?

Having ruminated on this myself, this is what I’ve learned so far.

Learn to ask the big questions. You should aim to do work that addresses one or more of salient questions such as: How much are MOOC students actually learning? What makes a course the most engaging? What assessment types promote learning? Do different disciplines benefit from different styles of online teaching? How does the type of content (e.g. text vs. video) affect learning? How does user experience and the production value of videos impact student retention and learning? What types of student interactions promote learning and retention? Can instruction be personalized in a way that promotes learning? A recent study of student learning in a physics MOOC is a good example of research that addresses one of these questions.

Don’t reinvent the wheel. There is a rich history of pedagogical research that predates MOOCs and online learning in general. Reading summaries of evidence-based best practices is a great way to learn about this prior literature. It is also a great way to improve your practice. HarvardX research fellow Joseph Williams has assembled a comprehensive list of introductions, reviews and overviews. I’ve learned a great deal from my own sampling of these readings. There is also a substantial body of discipline-based educational research (DBER), particularly in STEM fields. It is worth spending some time familiarizing yourself with that literature. It will help you learn about best practices in your field and give you a sense for pre-existing resources that you can use in your course and research project.

[ Full article available at Inside Higher Ed: https://www.insidehighered.com/blogs/higher-ed-beta/mooc-research-learning-curves ]

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Posted by on December 3, 2014 in MOOCs in the News

 

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