Leverage Intrinsic Motivation to Teach Effectively in a World Permeated by AI
What Dan Pink’s Motivation 3.0 framework can teach us about effective education in the wake of the disruption of artificial intelligence
To say that there has been consternation in the world of education since ChatGPT burst onto the scene with great fanfare at the end of October of last year is an understatement. Since being released, AI tools like ChatGPT have quickly become the most talked about topic among the educators I know, with opinions running the gamut from terror and concern to excitement and curiosity.
While there are legitimate reasons behind both reactions, the more I think about it, the more I am convinced that the right response to AI is to double down on pedagogical practices that we know help students to learn: building strong relationships of trust between students and teachers, designing course material with clear learning objectives, engaging students in active learning, and emphasizing the underlying cognitive skills that we hope our students will master through our courses.
While I am in no way suggesting that there aren’t real challenges that AI brings to bear on the world of education and the myriad of ways that it can undermine the learning of our students, I think that we already have many tools in our pedagogical toolboxes to address these challenges. And, with the capabilities of AI, there are in fact many new ways that we can use AI to help us make our pedagogy more effective.
Effective teaching in an AI world must embrace motivation 3.0 thinking
My recent thoughts on AI and education were sparked by
’s book Drive. In it, Pink makes an argument for the fundamental needs which motivate human behavior and how those needs have appeared in different ways throughout history.He charts the development of human motivation using the analogy of operating system updates. Motivation 1.0 was our initial framework which was largely powered by biological impulses like hunger and thirst and was designed to help us survive. Motivation 1.0 was followed by Motivation 2.0 which was built around carrots and sticks; promoting certain behaviors and discouraging others through external rewards and punishments.
He argues that while external rewards and punishments were sufficient for the routine tasks of industrialization in the twentieth century, this framework is incompatible with the type of work that dominates twenty-first century life. A new framework is needed.
The Pillars of Motivation 3.0: Autonomy, Mastery, and Purpose
Motivation 3.0, as Pink calls this needed update, is focused on three main elements: autonomy, mastery, and purpose. This framework aligns with intrinsic, or what Pink calls Type I behavior. This is in contrast, to the extrinsically motivated Type X (for eXtrinsic) behavior of Motivation 2.0.
The Type I framework of Motivation 3.0 is a playbook that educators should liberally reference as we seek to find ways to respond to the permeation of AI into the classroom. As AI tools like ChatGPT seep into every corner and crevice of our courses and our students’ lives, we need to make sure that the way we are asking them to learn is clearly designed and communicated to help them learn and grow. Using these three pillars of motivation 3.0 as a rubric can help us to assess whether we are doing that and identify ways for us to redesign our courses to be more valuable to students.
Pillar #1: Building trust with our students in order to allow them to leverage autonomy
Autonomy, as Pink points out, is our default setting as humans. Unfortunately, this slowly ebbs away over time as we age. Little kids, as I’m all too aware these days as the dad of two kiddos under the age of four, have no problem coming up with many inventive, if perhaps disruptive, things to do on their own.
Finding ways to promote autonomy means giving freedom over what is done, when it done, who it is done with, and how it is accomplished. While we may make specific choices to limit one or more of these variables (e.g., perhaps by choosing the task for students to do), we may be able to do more to explicitly tell our students that we are intentionally designing their coursework to promote their ability to leverage their autonomy.
I’ve spent some time this last weekend thinking about how I might incorporate some of these ideas into my teaching, focusing in particular on the embedded systems course that I teach each fall. The idea of autonomy helped give me language for things that are already working well in the course and why it is generally popular among students.
During the first half of the class students are given seven mini design projects. Each exercise has stated specifications that the design must meet, but very few requirement on how the design must meet those specifications. While students are often frustrated at first by the relative lack of guidance compared to other labs from previous classes, I often hear on course evaluations that this open-ended format is one of their favorite aspects of the course.
I’ve also been thinking about new ways that I might give students even more autonomy over various elements of the course. One option is to offer a menu of potential projects that students could choose from. These would be selected in order to achieve similar learning outcomes, but would give students the freedom to choose which project they were most interested in pursuing. Or going even further, I’ve considered allowing students to develop their own new designs based on a specification they develop and then submit that to be included as part of their design portfolio and contribute to their grade. This was part of what I enjoyed in a senior electronics design lab that I took in undergrad since it gave me the freedom to explore and build new projects within the context of a course.
Pillar #2: Designing assignments which are aimed at developing mastery
The second pillar supporting Type I behavior is mastery. As Pink defines it, embracing mastery—becoming better at something that matters—must start with understanding engagement or flow. The experience of flow is defined by finding ourselves in the growth zone. This sweet spot is where the challenges we face are neither too easy nor too overwhelming
I often liken this to the analogy of progressive overload in physical training. When you’re lifting weights, you need to gradually increase the difficulty of the training over time in order to grow. If you continue to lift the same amount of weight each workout you won’t give your body the needed stress to trigger muscle growth. On the other extreme, if you try to lift more weight than you can safely handle, you’ll end up in the panic zone and likely end up injuring yourself.
This is a topic which is being discussed within the pedagogy literature, specifically in the context of mastery-based grading. The basic idea is to design assessment strategies to align with the goal of developing mastery by offering students descriptive feedback on their work and giving them the opportunity to improve on their areas of weakness.
One way that I am considering integrating this into my course this fall is by restructuring the assignments to allow for multiple attempts. In its current form, there is no credit given for late work. While I think that deadlines are a helpful tool to keep students on track, I have been wondering lately if there might be a middle ground where it would be advantageous to offer some credit to encourage students to address the feedback on areas where their designs did not meet the specifications. This would likely help students engage with learning the material more deeply by incentivizing them to revisit their work to address feedback on their design.
Pillar #3: Communicating the purpose of the content and structure of our courses
The final pillar of Dan Pink’s intrinsic motivation framework is purpose. He argues that understanding the why of what we are doing is vitally important. Traditionally this has been considered more of a “nice to have” but Pink argues that given the shift in twenty-first century jobs, purpose is critically important for motivating workers.
This really resonates with me as an educator. As I’ve written before, I’m really drawn to the framework of transparency in teaching. I learned of this framework from the work of Mary-Ann Winkelmes and her work with TILT Higher Ed.
The way I try to incorporate this into my course material is by being explicit not only about what I want students to do on a particular assignment, but why I want them to do it. This is especially important if I am asking them to do it in a particular way, for example, without referencing a certain resource or using a specific tool.
Transparent teaching is especially powerful in the context education with and around AI because the capabilities of AI are most dangerous when they are used to short circuit the intent of an assignment. A phrasing I have heard recently from my colleagues is that using AI in support of your work is permissible when it is aligned with the learning goals of the assignment. I think this it the right idea. Ultimately, this is what it means to use AI as a ladder and not a crutch.
So what?
Anytime a new technology bursts on the scene it is likely to disrupt the status quo. We’ve certainly been seeing this happen with AI and tools like ChatGPT, BingAI Chat, and the recent release of GPT-4. It’s unlikely to stop anytime soon. New tools will certainly create disruption and force us to adapt. However, these tools are here to stay and our time is best spent on learning how to teach ourselves and our students to use them with wisdom rather than trying to avoid or ban them.
While the best pedagogical practices vary across different disciplines, instructors, and students, I think Daniel Pink’s Motivation 3.0 framework is a helpful foundation for building curriculum that is robust to the disruption of AI. Leaning into the three pillars of autonomy, mastery, and purpose gives us a good shot to successfully navigate the challenges of teaching and learning in a world permeated with artificial intelligence and helping our colleagues and students to do the same.
The Book Nook
I read Drive on the recommendation of a friend who told me that he gives it to all his team leaders to read. I found this to be a very insightful read with lots to consider, especially for those who work in knowledge work. Finding ways to connect with autonomy, mastery, and purpose in our work seems to me to be a good roadmap for more productive and meaningful work.
A few quotes to highlight.
On the unintended side effects of extrinsic motivation on creative work.
Try to encourage a kid to learn math by paying her for each workbook page she completes—and she’ll almost certainly become more diligent in the short term and lose interest in math in the long term. Take an industrial designer who loves his work and try to get him to do better by making his pay contingent on a hit product—and he’ll almost certainly work like a maniac in the short term, but become less interested in his job in the long term. As one leading behavioral science textbook puts it, “People use rewards expecting to gain the benefit of increasing another person’s motivation and behavior, but in so doing, they often incur the unintentional and hidden cost of undermining that person’s intrinsic motivation toward the activity.”
Rewards and their impact on focus.
Rewards, by their very nature, narrow our focus. That’s helpful when there’s a clear path to a solution. They help us stare ahead and race faster. But “if-then” motivators are terrible for challenges like the candle problem. As this experiment shows, the rewards narrowed people’s focus and blinkered the wide view that might have allowed them to see new uses for old objects.
Flow states are more common at work than in leisure.
And one of Csikszentmihalyi’s more surprising findings is that people are much more likely to reach that flow state at work than in leisure. Work can often have the structure of other autotelic experiences: clear goals, immediate feedback, challenges well matched to our abilities.
The Professor Is In
This past week was Harvey Mudd’s spring break, so I took a much needed break from work at school. I’m looking forward to a slightly more laid back second half of the semester with the interviews for our faculty search process having wrapped up the week before break.
Next week I am looking forward to visiting the University of Notre Dame for a conference on Virtues & Vocations run by the Center for Social Concerns there. The conference is themed around integrating virtue into course materials, with a particular focus on syllabi. It promises to be a great conference and I’m looking forward to meeting the other attendees.
In a similar vein, a few weeks ago I listened to this excellent talk by Michael Lamb, who is a professor at Wake Forest, an author, and director of The Program for Leadership and Character. In it, Michael presents some great ideas on what it means to lead in the midst of our challenging times.
I would also recommend that you read a paper that Michael recently co-authored titled “Digital temperance: adapting an ancient virtue for a technological age” which I am looking forward to unpacking in a future newsletter. In it, Michael and his co-authors make the case that with some modifications, the wisdom of Aristotle and Aquinas can help us to find our way between deficiency and excess in our digital age, finding a wise path between what they call “digital insensibility” and “digital overindulgence.”
Leisure Line
For spring break we made a trip to Disneyland. It was the first time we took our kids and we all had a great time (despite being drenched by the rain on Tuesday). The kids particularly liked the Winnie the Pooh ride since they are really into the Winnie the Pooh books and shows these days.
Still Life
An impressive snail that we discovered on a recent outing. To give you a sense of scale, the shell is about the size of a quarter!