DEBUGGING FAILURE

"One of the American midfielders,
I think it was Michael Bradley, made a bad pass.
A lazy, diagonal pass.
One of the Turkish players picked it off.
Now Turkey’s on the attack.
They’re moving down the left side, they’re moving the ball in.
I’m thinking to myself, This all began with a bad pass.”

— George Vecsey (quoted in Grantland)

 

When significant events happen, whether good or bad, we devote countless hours to understanding why they occurred. This happens publicly through newspapers, film, and television and personally through private thoughts and interpersonal dialogue. Gottschall‎ (2012), in his book, The Storytelling Animal, lightheartedly refers to this process as Sherlock Holmes Syndrome. We create stories that explain the outcomes in our lives, reasoning backwards. Studied under the umbrella of attribution theory in academia, these stories determine how hard we work, how much we persist, and what we do differently in the future—a suite of factors that influence motivation.

Debugging Failure in Computer Science

Through an NSF-funded collaboration between 9 Dots, UC Berkeley (Dor Abrahamson), and UCLA (Noel Enyedy and Francis Steen), the Debugging Failure project revolves around the design, implementation, and evaluation of a computer science education workshop aimed at fostering a culture of productive failure practices among elementary and middle school students. In order to learn how students can make the most of productive failure, we are studying how a community of teachers, students, software developers, and researchers understands and shapes its practices around telling stories, assigning fault, and fostering agency during the common experience of encountering bugs in computer code. Our team is implementing cycles of design-based research around four elements of the coding workshop: setting new norms around encountering, interrogating, and practicing expert debugging practices; designing arts-based inquiries into failure and success; leading instructor education workgroups focused on noticing the structure of failure stories and planning discourse-based responses; and building coding software that gives students metadata on their struggles and provides authentic debugging resources. Our data sources stretch across students' ways of participating in coding, their reflections on their coding experiences, and the artifacts they produce along the way. Through micro longitudinal case studies, content analyses, and ethnomethodological conversation analyses, we are making progress understanding how affect, storytelling, play, peer interactions, arts-based reflections, and instructor support carve out a generative debugging culture. 

DeLiema, D., Abrahamson, D., Enyedy, N., Steen, F., Dahn, M., Flood, V. J., Taylor, J., & Lee, L. (2018, April). Measuring debugging: How late elementary and middle school students handle broken code. In D. A.-L. Lui & Y. Kafai (Chairs & Organizers), Measuring making: Methods, tools, and strategies for capturing learning, participation, and engagement in maker activities. Symposium conducted at the annual meeting of the American Educational Research Association, New York City.

Flood, V. J., DeLiema, D., & Abrahamson, D. (in press). Bringing static code to life: The instructional work of animating computer programs with the body. In J. Kay & R. Luckin (Eds.), “Rethinking learning in the digital age: Making the Learning Sciences count,” Proceedings of the 13th International Conference of the Learning Sciences.

Flood, V. J., DeLiema, D., Harrer, B. W. & Abrahamson, D. (in press). Enskilment in the digital age: The interactional work of learning to debug. In J. Kay & R. Luckin (Eds.), “Rethinking learning in the digital age: Making the Learning Sciences count,” Proceedings of the 13th International Conference of the Learning Sciences.

Aalst, O. W-V., DeLiema, D., Flood, V., & Abrahamson, D. (2018, May). Peer conversations about refactoring computer code: Negotiating reflective abstraction through narrative, affect, and play. Paper presented at the Jean Piaget Society Annual Meeting, Amsterdam, The Netherlands.

Routing around moments of struggle in math tutoring

Some of my work focuses on what happens in natural conversation when students encounter and work though difficulties on math homework with the help of tutors. What do students blame, what chances do they think they have of succeeding, what do they try next, and how are these thoughts organized in sequences of conversation turns with tutors? Below, a tutor catches a mistake, points it out in the visual field, describes the flow of events up to the sticking point, and then hands the floor over to the student.

 

DeLiema, D. (2017). Co-constructed failure narratives in mathematics tutoring. Instructional Science. DOI: 10.1007/s11251-017-9424-2. (link to full article)

DeLiema, D. (2014, June). Attributions and epistemology in conversation: How math tutors and students co-construct accounts of failure and knowledge. For ICLS Doctoral Consortium. In proceedings of the International Conference of the Learning Sciences, Boulder, Colorado.

DeLiema, D. (May, 2013). How Do You Know You're Bad at Math? Epistemic Dialogues at an After-School Program. Talk given at the UCLA symposium on Global Transformative Learning: Building Institutions and Changing Minds.