2026 ASEE Annual Conference & Exposition

WIP: Tracking Cognitive Engagement via Micro-Facial Expressions during Engineering Problem-Solving

Presented at Computers in Education (CoED): Poster Session - Division Special Events (1 of 4) -- M208

This work-in-progress (WIP) study examines the relationship between students' micro facial expressions and their level of cognitive engagement while solving two mathematical problems of varying degrees of difficulty. Cognitive engagement during problem-solving is a complex, dynamic, and multidimensional construct. Grounded in a constructionist perspective, this study conceptualizes cognitive engagement as context-dependent and shaped by learners’ prior experiences and emotional responses. This mixed-methods study employed a participant-selection model to examine undergraduate engineering students’ cognitive engagement during problem-solving. Students from multiple disciplines at a public land-grant research university completed two think-aloud problem-solving tasks, including an easier (linear algebra) problem and a more difficult (geometry) problem. These think-aloud sessions were audio-video recorded. Audio data were transcribed for detailed analysis. The facial expressions were captured using the Morphcast Emotional Tracking tool based on the Russell Circumplex Model. Transcripts were segmented into five-second intervals, coded for emotional valence and arousal, and triangulated with facial-expression data to identify patterns indicative of cognitive engagement.
This study examined four undergraduate participants as part of a larger investigation into affective markers of cognitive engagement in engineering problem solving. Preliminary video and emotion‑tracking analyses showed that 3 of 4 participants who successfully solved the tasks exhibited predominantly positive affect, such as happiness, confidence, and curiosity despite brief moments of frustration. In contrast, the participant who struggled with both tasks displayed more frequent confusion and anxiety alongside intermittent positive states. Engagement‑over‑time visualizations revealed stable attention patterns among higher‑performing participants, while the lower‑performing participant demonstrated markedly variable attention. These early findings suggest that positive affect and curiosity, as reflected in facial expressions, may serve as preliminary indicators of higher cognitive engagement. This work contributes to ongoing efforts in affective computing for education and supports the development of real‑time metrics to inform adaptive learning systems and targeted pedagogical interventions in engineering education.

Authors

Dr. Talha Naqash Dickinson State University [biography]

Dr. Talha Naqash completed his doctoral studies in Engineering Education at Utah State University. With a diverse academic foundation, he also holds a Master’s degree in Telecommunication and Networking. He is currently serving as a faculty member at Dickinson State University in the School of Applied Sciences.
Dr. Naqash’s research focuses on cognitive engagement analysis, assessment methods in engineering education, and the role of facial expressions and emotions in the learning process. His scholarly contributions include numerous publications and presentations at prestigious venues such as IEEE, ASEE conferences, and leading Wiley and Springer journals. He is an active member of several technical committees and serves as a reviewer for reputable journals and international conferences, including the ASEE and IEEE Transactions on Education. Dr. Naqash’s dedication to advancing educational research, combined with his broad academic and professional experience, underscores his commitment to fostering innovation and excellence in engineering education.
Dr. Zain ul Abideen Utah State University [biography]

Zain ul Abideen holds a Ph.D. in Engineering Education from Utah State University, where he also served as a Graduate Researcher. He is a computer engineer and earned his bachelor’s degree in computer engineering and master’s degree in engineering, and brings over a decade of experience in teaching and research with undergraduate engineering students. He actively contributes to several technical committees and serves as a reviewer for leading journals and international conferences. His doctoral research focused on cognitive engagement, AI in education and engineering design, self-regulated learning, and mobile learning. His work seeks to deepen our understanding of how these elements influence learning and success in engineering education. With a strong commitment to educational advancement and a robust academic background, Zain is recognized as a dedicated and emerging scholar in the field of engineering education.
Waqas Ahmad http://orcid.org/0009-0004-7408-9201 Utah State University [biography]

Waqas Ahmad is a doctoral researcher at Utah State University whose scholarly work explores cognitive engagement, learning processes, and the sociopolitical aspects of education. With over 20 years of teaching experience at the college and university level in STEM disciplines and a strong academic background, he integrates practice-informed insight into his research. His approach uses innovative methods to analyze observable signs of engagement during engineering problem-solving, while advocating for equitable practices through Indigenous perspectives in data science education and student agency. By combining a thorough analysis of complex learning tasks with a focus on social justice, his work promotes creative, evidence-based pedagogical frameworks.
Dr. Assad Iqbal http://orcid.org/https://0000-0002-8060-7384 The Ohio State University [biography]

Assad Iqbal (Sid) is a Senior Lecturer at the Department of Engineering Education in the College of Engineering, Ohio State University. Assad has been working with the National Science Foundation (NSF) funded national collaboration research project, "Engineering For Us All (e4usa) since October 2022. The core mission of this project is to increase student and teacher access to engineering with a focus on reaching traditionally underrepresented populations in this field.

With a BS in Computer Information Systems Engineering, a Master of Science in Engineering Management, and a Ph.D. in Engineering Education, Assad's long-term research goal is to converge his varied research experiences and endeavors to explore the possibilities of an inclusive instructional design to promote self-directed, self-regulated, life-long learning among pre-college and undergraduate engineering students.
Mr. Rifatul Islam Himel http://orcid.org/0000-0002-0415-4774 Utah State University [biography]

Rifatul Islam Himel is a doctoral candidate in Engineering Education at Utah State University (USU), Logan, Utah, US. His doctoral research focuses on understanding human cognition in engineering problem-solving. He holds a Bachelor's degree in Electrical and Electronics Engineering and a Master's degree in Electronics and Telecommunication Engineering. With over six years of professional experience in the Information Technology industry and a strong background in teaching and research, Rifatul brings a unique interdisciplinary perspective to his work. His research interests include Human and Machine Cognition, Applied Artificial Intelligence in Engineering Education, Information Processing, and the study of Consciousness.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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