On New Year’s Day 2006, I started jogging regularly. One of the many nice things about jogging (apart from the physical high, the being outdoors, the doing-something-with-your-body-rather-than-only-with-your-brains-heart-and-soul) is that you can really measure progress. A plethora of web sites are available that can help you set your goals (run more often, faster, longer, … ) and guide you through a scheme of intermediate steps to get you there.
For me, music is a big part of the running experience. And, as in so many other domains, technology is now really creating new opportunities to enhance the music-and-running experience. An iPod with the NikePlus sensor is one example where you can “snowflake” your runs (i.e. customize them for you, without any annoying overhead on your part). By “snowflake” I’m referring to the Snowflake Effect that Wayne and I have written about before..
Basically, the NikePlus sensor fits in your shoes and transmits its data to a connector on your iPod. The iPod records the data. When you dock the iPod, the data gets sent to a NikePlus web site and you get a nice overview of your runs.
More interestingly, you can set yourself one or more targets, like the distance you want to run, or how often, or how fast, etc. The Snowflake Effect works really well in this context: when you improve your personal best time, you get a nice message with kudos from Tiger Woods or Lance Armstrong. Yes, I know that this is a pre-recorded message, and that neither Tiger nor Lance knows me personally, nor are they interested in my very mediocre jogging results, but this kind of feedback works really well nevertheless! There is something quite addictive about improving yourself and getting the recognition and encouragement from others when you do.
My key point here, I think, besides this being another example of the Snowflake Effect (my goals, my music, my runs), is the directness and relevance of the feedback loops. Time and distance can be measured quite precisely and are essential characteristics when you run. (Oh yes, you can also measure how many calories you burn if your interest is more on that side of things!) What surprised me at the beginning is how well we understand how we can take someone from one level of running performance to another. From personal experience, I can tell you that running for a full hour seems completely out of reach when you start doing this—I literally ran out of breath after 3 minutes on my first run!—yet, if you follow simple running advice, everyone can achieve it after six months.
I think there is a lot that we can learn from the world of sports that can be directly transferred to the world of learning. How often do our learners (and we as learners!) set their targets explicitly? As a computer science professor, I have very few students who have a more or less precise idea of why they are taking a particular course and what they want to achieve. How often do we provide them with a clear schema that is already proven to take learners from where they are now to where they want to be? How well do we measure progress towards their goal? How often do we provide the feedback to keep them on target—even when they’re off course?
Of course, things aren’t always just about farther, higher or faster, and that makes measuring progress sometimes quite a bit harder. Not everything we learn can be reduced to meters, grams, or seconds. Still, sometimes measuring progress is easy (drill-and-practice, spelling errors, ...), sometimes it is kind of in-between (project work, sales, repair errors, ...) and sometimes it is downright difficult (moral education, longer-term career planning). This obviously relates to the fuzziness of the word “learning”, a word we use in all these and many other contexts.
So, here is your homework assignment: can you think of examples of how to measure progress in learning? Can you think of ways to exploit those measures to provide motivating feedback?
Incidentally, NikePlus also has a very strong social component:
- Runners can challenge one another to run faster or farther (today, there are about 100,000 runners in more than 30,000 challenges on the web site, and more than 37,000 runs were logged in the last 24 hours).
- They can share power songs and play lists that work well for them (which you can of course buy on iTunes J ).
- Forums are available for exchanging tips, etc.
This social component must sound very familiar to those of us involved with computer-supported collaborative learning—or should I say Learning 2.0?
Erik Duval is a computer science professor at the Katholieke Universiteit Leuven in Belgium. His research interests include metadata, and how they enable finding rather than searching, and a global learning infrastructure based on open standards. He teaches courses on Human-Computer Interaction, Multimedia, and problem solving and design. He serves as the president of the ARIADNE Foundation and the chair of the IEEE LTSC working group on Learning Object Metadata.