2025 ASEE Annual Conference & Exposition

Understanding Academic Resilience Through Motivational Profiles and Self-Efficacy: A Cluster and Logistic Regression Analysis

Presented at ERM Technical Session: Examining Undergraduate Recruitment & Retention

Understanding Academic Resilience Through Motivational Profiles and Self-Efficacy: A Cluster and Logistic Regression Analysis

Academic resilience, defined as the capacity to persist and succeed in the face of academic challenges, is crucial for student success. Although decades of research have identified various cognitive and motivational factors, as key factors influencing resilience, there remains a limited understanding of how achievement goals, critical thinking, and task value interact to shape resilience outcomes. This study addresses this gap by exploring the role of these factors in forming distinct motivational profiles that predict academic resilience.

This study aims to explore the interaction between distinct motivational profiles and self-efficacy in predicting academic resilience. Specifically, it investigates whether these profiles can reliably differentiate students with high versus low resilience and how they contribute to resilience beyond individual variables. By examining the integration of cognitive and motivational factors, this research provides insight into the mechanisms that drive resilience, informing targeted interventions to support student success.

Data were collected from 151 undergraduate engineering students, measuring variables such as mastery goals, performance goals, task value, critical thinking, self-efficacy, and resilience. K-means clustering was used, and three motivational profiles were identified: "High Achievers," "Moderate Performers," and "Task-Focused Learners." These profiles, along with self-efficacy scores, were included in a logistic regression model to predict resilience, with accuracy, precision, recall, and AUC scores used to evaluate the model.

Preliminary analysis revealed that students classified as "Achievement-Oriented Learners" with high self-efficacy were significantly more likely to demonstrate resilience. The logistic regression model achieved an overall accuracy of 76%, with an AUC of 0.83. These findings suggest that enhancing achievement goals, fostering critical thinking skills, and increasing the perceived value of academic tasks can play a pivotal role in supporting academic resilience.

These findings suggest that enhancing self-efficacy and aligning students’ motivational goals can play a pivotal role in fostering academic resilience. Educators and academic advisors could apply these insights to design interventions that specifically target students' motivational profiles and self-beliefs to better support their ability to overcome academic challenges.

Authors

VINCENT OLUWASETO FAKIYESI University of Georgia [biography]

Vincent Oluwaseto Fakiyesi received the B.Tech. degree in chemical engineering from the
Ladoke Akintola University of Technology, Ogbomosho, Oyo State, , Nigeria in 2015, and He is presently a Doctoral Students at Engineering Education Transformative Institute at the University of Georgia College of Engineering.
ISAAC DAMILARE DUNMOYE University of Georgia [biography]

Isaac Dunmoye
PhD in Engineering (in view), University of Georgia, USA,
M.Sc. in Electrical Engineering, University of Cape Town, South Africa, 2022.
B.Eng. in Agricultural and Biosystems Engineering, University of Ilorin, Nigeria, 2016.
VARUN KATHPALIA University of Georgia [biography]

Varun Kathpalia, born and raised in northern part of India, joined EETI as a PhD student in the Spring of 2024.
He completed his undergraduate degree in Mechanical Engineering from Chitkara Institute of Engineering and Technology (Punjab Technical University, India) and master’s degree in Mechanical Engineering, specializing in Manufacturing & Materials Science Engineering, from the Indian Institute of Technology, Kanpur, India. He has over 4 years of corporate experience with companies such as Hindustan Coca-Cola Beverages Pvt. Ltd. and Saint-Gobain India Pvt. Ltd. (Research & Development). His interest in areas such as improvement in instructional techniques, faculty perspectives and teaching methodologies, drove him towards the domain of Engineering Education. Specifically, the question of how engineering education can be made more effective and engaging fascinated and motivated him to pursue research in this domain.

He is working with his major professor on an NSF funded project dealing with communities and relationships that enable and empower faculty and students in engineering.
Deborah Moyaki http://orcid.org/0009-0005-7441-0306 University of Georgia [biography]

Deborah Moyaki is a doctoral candidate in the Engineering Education and Transformative Practice program at the University of Georgia. She holds a bachelor’s degree in Educational Technology and is excited about the possibilities technology offers to the learning experience beyond the formal classroom setting. Her research focuses on enhancing the educational experience of engineering students by leveraging emerging technologies, including virtual reality and artificial intelligence.
Mr. Animesh Paul University of Georgia [biography]

Animesh (he/they) is a Ph.D. student at the Engineering Education Transformation Institute at the University of Georgia. Their research explores user experience and the transition of engineering students into the workforce.
Dr. Nathaniel Hunsu University of Georgia [biography]

Nathaniel Hunsu is an assistant professor of Engineering Education. He is affiliated with the Engineering Education Transformational Institute and the school of electrical and computer engineering at the university. His interest is at the nexus of the res

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

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