NSF Award
2432014
This project transforms engineering education by leveraging "meaningful failure" as a promising approach to learning and teaching. Failure is an inherent part of human life and learning processes, and early failure is often prerequisite step on the path to successful learning. However, typical engineering education currently punishes failure, which disincentivizes innovation, exploration, and risk-taking, ultimately resulting in engineers who are less prepared to tackle complex global challenges. By understanding students’ unique experiences during moments of academic failure, this project supports students taking risks and learning from setbacks, developing the skills and mindsets to embrace failure as a meaningful experience in their learning. Our research involves the use of biometric data, observations of classroom dynamics, and psychosocial assessments to better understand how each student experiences failure on a physiological, cognitive, and social level. We will use these data to develop new educational tools and strategies that will provide immediate, tailored interventions connected to individual student needs and experiences. This research will support the development of a workforce ready to persist past ubiquitous failure experiences in engineering to address tomorrow’s challenging engineering problems. Further, this research aligns with the goal of creating inclusive and equitable learning environments that can adapt to the diverse needs of all students.<br/><br/>The project will explore meaningful failure in engineering education contexts by developing personalized learning strategies and pedagogical tools. The proposed research has three goals: identifying real-time failure profile signals, understanding how learners' responses to failure are individualized, and determining necessary changes in pedagogy and assessment to support personalized responses tolearning from failure. The research involves a multi-pronged data collection approach, including laboratory experiments using video and biosensing modalities (EEG, EDA, ECG), classroom observations, surveys, and interviews with educators and administrators. A convergent team from five institutions, with expertise in cognitive neuroscience, learning sciences, AI, and psychosocial theories of learning and development collaborate to create individualized failure profiles. These profiles will integrate multi-modal data sources to formally represent each learner’s unique cognitive, affective, and behavioral responses to failure. The project will culminate in the development of pedagogical tools and strategies to support personalized learning and resilience – increasing retention and success rates in engineering fields and pioneering a shift in engineering education towards valuing learning from failure.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
