Motivation was just one of a few topics included in the reading for my instructional design and technology course, yet it was one of the most popular on the discussion board. Some common questions and themes:
- How can instructional designers harness motivation? (which somewhat suggests via “harness” that motivation is a tangible and unchanging thing)
- The importance of making instruction relevant to encourage motivation
- Determining the carrot-to-stick ratio
- Who is ultimately responsible for providing the motivation to learn: the instructor, the student, or the designer?
One peer shared this fantastic metaphor:
I almost imagine the student as residing in a house. The content initiates from outside. While the teacher can try to make the scenery more interesting, learners are the only ones who can open the door. I think the secret is to get the learners peek through the windows and discover a need or reason for learning. Then, the student will come out and interact with the information, building their own understandings of the world. While this motivation may come from the fact that the information is personally interesting (“I love rain showers!”), it may be that it is simply in the learner’s best interest to acquire the information (“If I don’t come out and upgrade my roof, it’s going to leak with all this rain.”).
My own interest with motivation began the balance between extrinsic motivation and intrinsic motivation, and how ed-tech frequently designs with the former in mind, but researchers and writers frequently focus on the latter.
Keep reading for my thoughts…
What I appreciated the most in this week’s reading was Keller and Deimann’s chapter “Motivation, Volition, and Performance” in Trends and Issues in Instructional Design and Technology. Often in general education, teachers and administrators discuss motivational techniques, like reward systems or positive feedback, or instructional strategies that fostering students’ curiosity, like project-based learning and inquiry. While I haven’t seen a specific chart, it seems each approach is diametrically opposed to another approach, and after enough book studies (Drive, Grit, Mindsets) it feels a little like playing Operation with a forklift.
Keller and Diamann offer another way: a holistic approach that draws on the multiple studies of motivation and volition. To explain what I mean, take one issue within the study of motivation: intrinsic versus extrinsic motivation.
In education, balancing strategies that extrinsically motivate students and intrinsically motivate them is incredibly difficult. Classroom management techniques frequently use reward systems and positive feedback to encourage good behavior, and educational websites and games frequently use leader boards or badges to motivate students to work. Going further, there are tips to include gamification during instruction. Going even further, schools will post class averages on tests to encourage competition.
During planning, however, many professional development discussions will start with Daniel Pink’s Drive TEDTalk or a quote from Carol Dweck of Mindsets fame. And we all know our students need more Grit. These authors focus on techniques to foster intrinsic motivation. While some of their advice can co-exist with the external motivational techniques, not all do and definitely not the loudest. Take this quote from Daniel Pink’s TEDTalk:
If you want people to perform better, you reward them. Right? Bonuses, commissions, their own reality show. Incentivize them. That’s how business works. But that’s not happening here. You’ve got an incentive designed to sharpen thinking and accelerate creativity, and it does just the opposite. It dulls thinking and blocks creativity.
If you look at the science, there is a mismatch between what science knows and what business does.
With any of these approaches, I feel teachers must pick one and then focus on the instruction. Instructional design does the opposite.
Near the end of the chapter, Keller shares two holistic motivational designs: Wlodkowski’s Motivational Framework and his own ten step model of motivational design.
Keller clearly favors his own model, but either is an improvement from needing to choose a singular approach. What appeals most to me is how Keller’s model conducts a learner analysis before choosing motivational tactics. Instructional designers who are writing courses for specific needs and audiences should always conduct a learner analysis, and this is just another reason why.
But what happens when the course or lesson is delivered virtually to an unknown audience? How does one choose which motivational tactics to include and which to leave out? Daniel Pink argues against reward systems a.k.a. gamification, yet take the popularity of Khan Academy that uses badges and points. How can designers still make use of Keller’s framework while developing a course for a global audience?
One response gets me thinking more about how one measures motivation levels in a digital environment. What metrics should designers use? How does a motivated learner use which tools how frequently compared to an unmotivated learner?
Keller’s design approach is simple: assessing learner motivation – provide adaptive motivational interventions – evaluate the impacts of these interventions. It is a typical model of adaptive instruction applied to the domain, learner motivation. As you may know, it is my interest to design adaptive learning technologies. In my literature review so far, unfortunately, there is few motivation assessment methods except for self-reported surveys or truly nothing. For an online course having many and diverse students, assessing individuals’ motivation is critical. However as I said, feasible methods are very limited, neither do motivational scaffolds and feedback strategies aligned with different learner motivation.