2025 ASEE Annual Conference & Exposition

This study aims to examine how varying levels of cognitive dissonance affect innovation self-efficacy in students enrolled in an Innovation-Based Learning (IBL) biomedical engineering program. By exploring the relationship between these variables, the research aims to contribute to understanding how cognitive dissonance can be leveraged to enhance innovation skills in engineering education.
IBL emphasizes applying engineering principles to solve real-world problems, identify technical challenges, inefficiencies, and knowledge gaps, and create impactful solutions. Unlike traditional project-based learning, IBL focuses on generating innovative outcomes that provide value beyond the classroom. IBL fosters creativity, critical thinking, and problem-solving skills through complex, open-ended projects, promoting collaboration, iterative development, and real-world application. This approach cultivates an innovation-driven mindset and leadership skills, crucial for success in STEM fields, such as biomedical engineering.
Cognitive dissonance, the psychological discomfort from encountering conflicting ideas or challenges that contradict one’s knowledge, is common in innovation-driven learning. Transitioning to an IBL classroom, where classroom norms are different from traditional education, initially amplifies cognitive dissonance in students, particularly those accustomed to structured learning environments. IBL’s focus on open-ended problem-solving and real-world applications contrasts with more traditional linear educational approaches. This disruption can challenge students' existing learning strategies and expectations, increasing cognitive dissonance. When managed effectively, this phenomenon fosters deeper understanding, enhances problem-solving skills, and strengthens innovation self-efficacy—confidence in one's ability to handle innovation tasks. On the other hand, unresolved dissonance can impede innovation success.
This study was conducted within a biomedical engineering program that employed an IBL framework. The participants included undergraduate and graduate students who completed surveys at the beginning and end of the semester to capture changes in cognitive dissonance and innovation self-efficacy. The cognitive dissonance survey was adapted from a validated scale to reflect IBL-specific scenarios, assessing students' psychological discomfort when confronting conflicting ideas or ambiguous challenges. Innovation self-efficacy was measured using a scale established by Gerber et al. (2012), which evaluates confidence in completing innovation-related tasks such as generating creative solutions and addressing complex problems. Data collection was facilitated through the MOOCIBL platform to ensure consistency. Spearman’s rank correlation was used to explore initial relationships between the variables, while logistic regression modeling was implemented to predict innovation self-efficacy based on cognitive dissonance scores. These statistical approaches provided insights into the interplay between these constructs.
The results revealed a relationship between cognitive dissonance and innovation self-efficacy, with findings suggesting that as students resolved cognitive dissonance over the semester, their innovation self-efficacy increased. Logistic regression analysis further demonstrated that decreases in cognitive dissonance levels strongly predicted higher innovation efficacy scores. These results suggest that as students adapted to the IBL framework's open-ended, problem-solving approach, their ability to manage cognitive dissonance improved, enhancing their confidence in innovation tasks. This highlights the critical role of managing cognitive dissonance effectively to foster the development of innovation self-efficacy within an IBL environment.
These findings contribute to STEM and engineering education by providing insight into how cognitive dissonance influences students' innovation skills. The predictive model offers valuable implications for pedagogical strategies to enhance innovation self-efficacy through effective management of cognitive dissonance.