Gibin Raju | Quantitative Hypothesis | Research Excellence Award

Published on by Research Hypothesis

Dr. Gibin Raju | Quantitative Hypothesis | Research Excellence Award

Dr. Gibin Raju | Quantitative Hypothesis | Research Excellence Award | Postdoctoral Researcher | Texas A&M University | United States

Dr. Gibin Raju is a dedicated engineering education researcher whose academic journey spans aerospace engineering, educational studies, and engineering education, shaping him into a multidisciplinary scholar committed to advancing STEM learning and research excellence. Dr. Gibin Raju completed his Ph.D. in Engineering Education at the University of Cincinnati, supported by a strong academic foundation that includes a Master’s in Educational Studies, a Master’s in Aerospace Engineering & Engineering Mechanics, and a Bachelor’s in Aerospace Engineering. His professional experience encompasses postdoctoral research at Texas A&M University, where he contributes to mixed-methods and multimodal studies, instructional innovation, grant development, and interdisciplinary collaborations advancing engineering design cognition, spatial visualization, AI-enhanced learning, and K–12 STEM education. Dr. Gibin Raju has served in multiple academic and community-centered roles, including STEM instructor, adjunct faculty, data researcher, and project collaborator on NSF- and IES-funded initiatives involving spatial skills, problem-solving behaviors, cognitive load measures, transformative learning, and inclusive STEM workforce development. His research interests include spatial visualization, engineering design processes, multimodal analytics, transformative learning, universal design for learning, teaming effectiveness, and STEM motivation, contributing to publications across Scopus-indexed journals and flagship conferences such as ASEE, FIE, CoNECD, and ICERI. Dr. Gibin Raju’s research skills span quantitative, qualitative, and mixed-methods analysis using advanced tools such as R, SPSS, SAS, MATLAB, and NVivo, supported by proficiency in experimental techniques such as eye-tracking, EEG, and think-aloud protocols. His awards and honors reflect academic excellence and leadership, including the Apprentice Faculty Grant from ASEE, the Presidential Medal for Graduate Student Excellence, the CEAS Graduate Student Engineer Award, the Graduate Leadership Award, the Innovation & Entrepreneurship Leadership Fellowship, and multiple graduate recognition awards. His service to academic communities includes developing innovative curricula, mentoring students, leading STEM outreach, designing AI-integrated instructional strategies, and contributing to proposal-writing efforts for federal grants supporting engineering education reform and workforce development. Dr. Gibin Raju continues to contribute meaningfully to research, teaching, and professional service, driven by a strong commitment to creating accessible, evidence-based learning environments and advancing global engineering education. With a rapidly expanding publication record, growing research collaborations, demonstrated leadership, and a clear vision for impactful scholarship, Dr. Gibin Raju is positioned to become a significant contributor and future leader in engineering education research.

Profile: Scopus | ORCID | Google Scholar

Featured Publications 

  1. Raju, G., Sorby, S., & Reid, C. (2025). Spatial skill impact on engineering design process: A comparative study of first- and final-year engineering students.

  2. Agarwal, J., & Raju, G. (2025). Establishing quality standards for empirical studies using mixed-methods designs in engineering education research.

  3. Raju, G. M., Feldkamp, P., & Gaskins, W. (2024). Factors shaping students’ attitude and persistence after participating in a summer physics course – A mixed methods study.

  4. Raju, G., Balart, T., Ligler, G., Shryock, K. J., & Brumbelow, K. (2025). Engineering the unexpected: Faculty strategies for navigating academic disruptions.

  5. Dogga, B., Raju, G., Louw, W., & Cohen, K. (2025). Fuzzy decisions on fluid instabilities: Autoencoder-based reconstruction meets rule-based anomaly classification.

  6. Raju, G., & Sorby, S. (2025). Exploring the impact of think-aloud protocol in engineering design problem solving.

  7. White, L. L. A., Raju, G., Watson, K., & Shryock, K. J. (2025). Critical thinking (mis)conceptions of first-year engineering students.