Overcoming Barriers to Cross-Disciplinary Education: A Productive Failure Framework

Attrition rates for dedicated computational biology and bioinformatics (CBB) majors is higher than expected given the rate of attrition in computer science and biology, respectively. This observation is even higher in historically underserved student populations. One reason this may be is that CBB, like many intersectional and cross-disciplinary areas of study, requires of its learners to learn the standards of evidence, terms of art, and modes of knowledge production of multiple fields simultaneously. In the case of CBB, minimally students are required to reach proficiency in both computing and biological sciences, with variation in mathematics, chemistry, and physics depending on the degree program. Students with appropriate support, institutional knowledge, and prior exposure are more likely to complete their training in bioinformatics. Those without these benefits may be able to navigate the hidden curriculum and adapt to the norms of one field in charge of teaching constituent classes for their program of study, but not two simultaneously. Here, we present a framework for teaching and mentoring students in CBB programs centering student metacognition in discipline-specific modes of failure to improve both resilience and expert-like thinking. We find preliminary evidence that the drastically different ways that biology and programming classes prompt, explicitly or implicitly, students to respond and reflect to failure is a major challenge to student success. We additionally propose instruments for assessing student response to failure and interventions to foster growth mindset in ways effective cross-discipline.