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There has been tons of learning going on for me after moving to Minnesota two months ago: getting used to the imperial unit system; finding out it’s impossible to purchase alcohol on Sundays; realizing we need to “import” our car; people actually can fly kites on lakes; and, of course, people don’t have the accent as in the movie Fargo :)… It has been an amazing experience so far to get accustomed to MPLS (I am not saying “Twin Cities” because local Minnesotans prefer MPLS – another lesson learned).

Learning also happens in the process of getting familiar with my new faculty life! It’s extremely exciting for me to join the Learning Technologies (LT) program and the LT Media Lab at UMN. A lot of “first times” have happened during the past three weeks since my official start date: the first program meeting, the first faculty meeting, the first writing group meetup, the first time I ran behind the University shuttle, and the first class meeting… Everything is still fresh!

Among all those excitements, I am especially excited about the course I am teaching this Spring: Learning Analytics in the Knowledge Age. It is currently offered as a special topics course in our program and may be offered as an ordinary course in the future. It is the first course I am teaching independently. In the first class meeting last week, I was glad to see a wonderful mix of graduate students bringing in unique expertise and interests from several areas, including educational psychology, STEM education, computer science, pharmacy, and LT. There will be a lot of fun!

Design of the course

This course is designed to be a Knowledge Building course. All participants are seen as equal contributors to the field of learning analytics. All students enrolled in the course become builders of the field! That’s one exciting thing of diving into such a new field.

Backgrounds and interests brought in by students will make the course extremely fun to teach. So I designed two types of groups in which they would shine!

  • Special Interest Groups (SIGs): I suggested five themes of learning analytics students could choose to specialize, such as knowledge modeling, social networks, and text mining. (The choice of themes was totally arbitrary and is subject to change.) Students gathering around one theme will be leading one class session. Over the course, each of us will be able to experience all five themes, but will also be able to dive deeper into a specialization theme.
  • Working Groups (WGs): Students will design group projects that they would work on through this course. Students working on one group project becomes a working group. They will make use of ideas from readings and in the community to advance their projects; in the meantime, their work in WGs will also contribute back to the community.

Knowledge Forum will be used as the course environment because it is still the most powerful tool I see to support flexible idea development. We will be able to try some analytic tools in Knowledge Forum – living and exploring the capacity of learning analytics in supporting growth in learning in different domains. We will see whether we could also advance some of the Knowledge Forum analytic tools.

How is this course different from others?

There have been a few awesome courses offered on this topic, mostly in the form of MOOCs:

These courses have been amazing resources for myself to learn the field as well as to design the current course. However, the course I am offering is designed to be quite different from them in the following two aspects.

  • First, because we would have much more time, we would have chance to explore more issues concerned with learning, rather than solely focusing on analytics. For instance, we would explore new competencies that are important in the so-called knowledge age while learning analytic techniques. We would also explore the linkages between analytics with pedagogy and epistemology.
  • Second, as mentioned above, students will be advancing projects in their WGs. So they are expected to produce new knowledge to solve real-world problems, rather than acquiring new knowledge and skills in this field. Of course, learning new analytic techniques will be an important component of taking this course.

I believe there are many lessons for me to learn – as a teacher, co-learner, and knowledge-builder in the class. If you are also interested in this course, feel free to check out its course materials. Suggestions are more than welcomed.

Week 1

(Photo credit: Lana Peterson)

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Bodong Chen


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Bodong Chen, University of Minnesota

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