This winter I spent many weekends traveling with my son and in doing so ended up with a number of rental cars. What struck me is the fact that every car you get in is set up just a little differently. For example, the wiper controls aren’t in the same place, or perhaps the lights get turned on/off differently. It struck me that just like cars, Learning Management Systems (LMSs) are also set up just a little differently each time we upgrade (full disclosure we also were doing a major system upgrade to our Desire2Learn system during this time).
During these travels, my son and I had quite an adventure in the wee hours of the morning while picking up a car at the Salt Lake City airport. When we got to the car (at 12:30 a.m. MTD, 1:30 a.m. CST) I realized it was a keyless start. Having never used a keyless start before, I wasn’t sure that we would ever make it out of the parking garage. Needless to say after a few failed attempts at starting the car, we finally figured out the trick (in case you were wondering, your foot needs to be on the brake pedal for the car to start) and were happily on our way. In this situation there was no one in the garage whom I could ask for help, but there was never any question that we would continue to try things (including reading the manual, if necessary) until we started the car.
This experience started me thinking about why we tend to show persistence in certain tasks, like figuring out how to start a keyless ignition, while with other tasks, like learning the University’s new deployment of the LMS, we are more likely to throw our hands in the air and quit, claiming the task is too difficult or not worth the effort.
Of course, the obvious answer is that if I ever wanted to leave the airport, I had to figure out how to make the car start. A colleague suggested that if we made learning the LMS a stipulation for leaving the airport everyone would learn it. Perhaps he is correct. However, one could argue that if you are a student or an instructor that requires the use of an LMS to either deliver or participate in course work, isn’t that also a pretty strong need? Albeit not as strong as the desire to not live at the airport!
This got me to wondering if there was a stronger underlying behavioral issue, and if so, is there was a way to change the way we design or train computer systems (or design course delivery) to make our users want to persist. Turns out there are many psychological theories that relate to persistence. One of the theories I think we can learn the most from is Eisenberger’s (1992) model of learned industriousness1. Essentially, this theory states that a user’s task persistence is based on their having received previous positive reinforcement on similar tasks.
Seems simple enough, right? If we try something and fail, and have no positive reinforcement or support, the likelihood that we will try again will be lower. I mean who really wants to feel like a failure? Whereas, if we try something and fail, but are provided with positive reinforcement, that allows us to eventually become successful, and we are more likely to try in the future and persist through failure. So how can we apply these lessons to teaching, and online systems and instructions in particular?
In my mind, this theory reinforces two ideas that I communicate to the faculty I work with:
1) When first learning the LMS, pick 1 or 2 tools that you are going to use and learn to use them well. Don’t try to learn everything at once. If you learn one thing and are successful, the likelihood that you will try another new thing is higher than if you try to do everything and feel overwhelmed the entire time.
2) For your students: build in early low stakes activities that are highly structured and supported so they have early success with the activities you eventually will be assessing them on. This would include not only academic tasks but also technical ones like uploading a file or posting to a discussion.
While these two pieces of advice are a good place to start, I believe, as system designers, we can look at other ways to assist the learner through the process and encourage them to be successful and thus to persist. As systems become “smarter,” building in non-human reinforcement is going to become increasingly more important. For example, after having failed to do a particular task, instead of relying on the person to persist, the system can/should provide a hint. These system supplied “hints” are actually how we made it out of the airport that night. After unsuccessfully attempting to start the car by pushing the start button a number of times, a message came up on the dashboard that told me to put my foot on the brake. This hint served as positive reinforcement, letting me know I was on the right track and provided encouragement to continue to persist through the task.
Think about how similar supports could be built into classes, for example, scaffolding larger projects to help students persist through their learning or how the idea of “hints” can be built into the systems we use to facilitate learning. These systems already track user behavior, why then can’t they provide contextual clues when a user is unsuccessful at a particular system task, say uploading a file? Without these contextual clues, we see that users repeat the same behavior over and over again, hoping for a different result each time, until they become so frustrated they ultimately give up. We should do what we can to build systems that provide opportunities to be successful. After all, everyone should feel the success of getting to leave the airport.
1 Eisenberger, R. (1992). Learned industriousness. Psychological Review, 99(2), 248-267. doi:10.1037/0033-295X.99.2.248 (note link will only work with DePaul user credentials)