Setting Good (Behavioral) Defaults: How To Influence Student Expectations to Facilitate Better Learning Behaviors
Concurrent Session 4
Student behaviors are triggered in part by contextual cues embedded in the virtual, hybrid, and face-to-face classroom. In this interactive session, we facilitate a conversation about how instructors and instructional designers can manipulate those contextual cues through choice architecture and defaults to guide students toward more productive learning behaviors.
In this interactive session, we offer a brief introduction to choice architecture and defaults, and facilitate a conversation about how they can be best used in online, hybrid, or face-to-face courses to guide more productive learning behaviors.
Students come into the classroom with beliefs and expectations—scripts or schemata—that guide their behaviors. These are habitual and do the work of allowing us to quickly process and respond to our environments based on relatively little information. Nobel Prize-winning psychologist and economist Daniel Kahneman calls this System 1 thinking. It buffers us against the need to devote concerted attention to every decision we make. And in the classroom, it can inform choices as innocuous as picking a seat, as personally problematic as tuning out verbal directions for assignments, or as disruptive as talking over classmates or stealing their ideas.
Obviously, in or out of a learning context, deleterious scripts need to be disrupted and their resulting behaviors or outcomes need to be changed. But though they can be viewed as uniformly negative, these cognitive shortcuts actually important. And by setting productive expectations and defaults, we can put many of them to work in service of more effective learning.
This session focuses on how we can create more productive expectations and defaults for students. We begin by examining defaults in real time. A conference session is a lot like a class, and attendees will be asked to think through the kinds of expectations they had when they walked into the room, and how those expectations were molded by the setting of the conference, the set-up of the space, and the nature of the event. In other words, how does the architecture of a conference session interface with participants’ pre-existing scripts to set parameters for how they will behave?
Participants will then spend the rest of the session considering how their observations translate into a virtual, hybrid, or in-person classroom setting. In table groups, they will brainstorm ideas for setting positive behavioral defaults in one of two cases: expectations about student engagement, or expectations about grades. Groups will be encouraged to experiment with ways to set better defaults using their preferred LMS—for example, by including low-stakes practice activities or example assignments. And toward the end of the session, groups will be asked to report back, generating a list of possible strategies that all the participants can then take home.
As part of the session, we will provide a brief introduction to Systems 1 and 2 thinking, scripts and schemata, and some relevant research in other fields about creating effective defaults. Participants will receive a handout summarizing the theoretical framework with space to record their own ideas and takeaways. And participants will receive a brief bibliography that offers some starting points for a further exploration of behavioral economics and choice architecture.
The goal of this session is not for participants to learn specific course-building tricks or ‘nudges’ that trigger better classroom behavior. Behavioral interventions are not plug-and-play, and they cannot be mechanically applied. Instead, the main point is to help participants become more cognizant of the scripts students bring with them into courses, both for better and for worse. And it is to give participants tools to help students learn more effectively by managing the contextual cues—the defaults—that trigger certain scripts. In other words, participants should come away from this session with 1) the ability to analyze how environmental factors in the (virtual) classroom—at least in part—determine student behavior; and 2) a framework for how to architect their (virtual) classroom to encourage the types of student behavior they would like to see.