Session: DEC-02: Innovative Practices in Design Education

Paper Number: 193625

193625 - Designing a Multi-Modal Experimental Protocol for Examining Failure Experiences During Engineering Problem-Solving 

Traditionally, in academic settings, failure is framed as a negative outcome tied to poor performance. Even so, emerging research, such as the Productive Failure (PF) framework, frames failure as a productive learning mechanism capable of improving understanding and promoting resilience. The PF framework has demonstrated aggregate learning benefits of intentionally designed failure experiences in groups working on well-structured mathematics problems. However, it has not been extended to engineering education with well- or ill-structured problems, nor does it account for the personalized, continuous nature of failure.
In this paper, we propose a multi-modal experimental protocol
to examine: i) individual students’ real-time failure experiences
and associated intensities in an engineering context, and ii) the
influence of the structure of the engineering problems on student
failure experiences.
The proposed experimental protocol will involve undergraduate engineering students solving both well- and ill-structured
engineering statics problems, with physiological and behavioral data such as electroencephalography (EEG), electrodermal activity (EDA), heart rate variability (HRV), and facial expressions being captured continuously. Failure will be operationalized at two levels: outcome-based, reflecting the correctness of final responses, and expectation-based, capturing the mismatch between student performance and their self-defined success threshold. Failure intensity is measured by examining changes in an individual’s baseline psychophysiological signal levels to determine how strong each failure episode is. Collectively, these measures are aimed at constructing individualized failure profiles that capture when, how intensely, and in what cognitive and affective form students experience failure. The findings from this protocol
will inform improved experiment designs and guide the development of personalized, real-time learning support that encourages meaningful failure practice in engineering education.

Presenting Author: Runu Proma Das UNIVERSITY OF GEORGIA

Presenting Author Biography: Runu Proma Das is a Ph.D. student with an emphasis on mechanical engineering under the supervision of Dr. Beshoy Morkos at the University of Georgia. She is also a graduate researcher in the MODEL Group lab. Her current research interest is in Engineering Education with a design emphasis on neuroscience, and she is also interested in exploring Brain-Computer Interface (BCI). Currently, she is exploring the student failure profile to develop a resilient intervention system. She wants to be a dedicated researcher with sincerity and persistence in her field.