2026 ASEE Annual Conference & Exposition

Investigating Data Science Student Confidence and Competency in Kuwait

Presented at DSAI-Session 12: Data Science Projects, Datasets, and Real-World Applications

Data science has rapidly emerged as a critical global profession. Despite this growth, there is limited empirical research examining data science education within the Kuwaiti context, leaving significant gaps in understanding students’ self-efficacy and confidence in their professional competencies prior to graduation.

This paper presents a case study investigating data science students’ self-efficacy and confidence in Kuwait. It specifically attends to how cultural, educational, and socio-economic factors informed by the STEM Factors Influencing GCC Countries model influence their perceived ability to perform core data science tasks. The study employed the validated Data Science Self-Efficacy Survey to evaluate students' confidence as they engaged in coursework and projects, assessing their perceived competence in applying data science tools, techniques, and methodologies effectively.

Findings provide critical empirical insights into the challenges and opportunities for Kuwaiti students in developing data science competencies. The results offer a necessary foundation for improving curriculum design, pedagogical strategies, and institutional support systems, aiming to strategically strengthen student confidence and preparedness for high-demand data science careers in the region.

Authors

Dr. Zahraa Marafie http://orcid.org/0009-0005-0356-1537 Kuwait University
Safia Malallah Kansas State University [biography]

Dr. Safia Malallah is a teaching assistant professor at Kansas State University, where she completed her Ph.D. in Computer Science and early childhood. Her research is dedicated to advancing computer science and data science education across the PreK-12 and undergraduate levels. Dr. Malallah is particularly passionate about designing innovative and accessible learning experiences that cultivate essential computational skills in students
Dr. Ejiro U Osiobe http://orcid.org/https://0000-0002-1107-6620 [biography]

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Lior Shamir Kansas State University [biography]

Associate professor of computer science at Kansas State University.
Jorge L Valenzuela Kansas State University [biography]

Dr. Jorge L Valenzuela earned a bachelor’s degree in computer engineering from Monterrey Tech, Mexico, in 1990. He worked in the industry in Mexico developing embedded systems before coming to Kansas State University (K-State) in 1998 to pursue a master’s degree in software engineering. After completing his master’s, he worked for Motorola as a software engineer from 2000 to 2003. Dr. Valenzuela returned to K-State in 2004, earning a doctorate in computer science in 2014. He later worked as a systems programmer in the College of Education and served as an adjunct instructor in the Department of Computer Science Department, where he currently holds a Teaching Assistant Professor position.
Friday Emmanuel James Kansas State University [biography]

Friday James is a Teaching Assistant Professor at Kansas State University. He has a double-majored Bachelor's degree in Statistics/Computer Science from University of Agriculture, Makurdi - Nigeria. He got a Master's degree in Statistics and a Master's degree in Computer Science from University of Ilorin - Nigeria and Kansas State University - Kansas USA in 2015 and 2021 respectively. Following this, he bagged a PhD in Computer Science from Kansas State University in 2025 and joined as a teaching track Assistant Professor. His research interest cuts across the use of machine learning and data science in Computing Science Education to improve teaching and learning.

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