Anne Sales, PhD RN and Professor, Systems Leadership and Effectiveness Science,
School of Nursing
Starting a new course from scratch is never easy. It’s particularly difficult when the course has content that’s never been taught in the school before, needs to be taught to a large class, and must be taught in a web-blended format, in which class participants only meet face to face once a month for 3 hours.
The web-blended format of the course makes it essential to take a curating approach to content. Much of the material has to be assimilated by students without a great deal of contact with the instructor. Being able to use existing content, rather than creating content de novo was very important.
I decided to use existing case studies (from Harvard Business Publishing) as a core component of the class, and to have students work in groups to support learning. Systems and models are core concepts in this course, which focused on optimal systems and models for healthcare delivery. While there is a lot of information and content about systems in both online and print media, finding compelling material that supports learning from the ground up to recognize systems in the world around you is not always easy.
However, I was aware of the different Massive Open Online Course (MOOC) offerings from the University of Michigan (as well as many other universities) on the Coursera platform, and had already checked out a number of courses focusing on systems thinking and analysis. One of these, the first UM MOOC offering, is Model Thinking offered by Scott E. Page, Leonid Hurwicz Collegiate Professor of Complex Systems, Political Science, and Economics at the University of Michigan.
Scott’s course opens with several introductory videos that explain thinking in terms of models and systems, and provides an overview of what can be quite complicated and complex issues. While the students in my class don’t need to know technical details of systems analysis, they do need to recognize the ubiquity of systems, and the relationship between models and systems in describing and analyzing what we experience.
Being able to reuse digital content created for one purpose in a different course with an entirely different group of learners than those for whom it was initially intended, to support learning objectives in a very different context, has been invaluable. There is a lot of content out there in all kinds of forms, increasingly in the digital and online worlds—but discerning the good from the mediocre or, worse, the bad (as in misleading or outright incorrect)—is critical for learners, and an important function of teaching or supporting learning.
Issues this raises: how did I know that this material existed? How did I decide that it was good rather than mediocre, and how did I judge that it could be used in a context other than its original MOOC? The answer to the first question is largely serendipity—I happened to have served on the UM committee that approves MOOCs, so I have more awareness of what’s out there than many faculty. I also happened to be interested in this area personally, so I had initially signed up for Scott’s MOOC (twice, actually!), although I was one of the vast number of enrollees who never complete a course (twice). So I’d had a chance to judge it for myself, and found the content interesting, engaging, and relevant. That made me confident that it was a good idea to use it. But we need better ways to let everyone know what’s out there, and give people some idea of the quality of offerings. This will take some creative thinking and input—great things about living in the digital age!