2026 ASEE Annual Conference & Exposition

Daily Quizzes for Computing Competency: Strengthening Fundamentals and Workforce Readiness in Senior Capstone

Presented at CIT Technical Session 6: Experiential Learning and Capstone.

Senior capstone courses are built to be the culminating experience in a computing degree, yet their project-focused structure rarely asks students to look back across the curriculum they are about to leave behind. This study examines a simple response to that gap: short, low-stakes daily quizzes integrated into a senior computing capstone course, prompting retrieval of foundational concepts spanning algorithms, data structures, operating systems, software engineering, and professional practice, running alongside project work rather than replacing it.

Drawing on qualitative content analysis of 148 coded student responses across multiple semesters, and grounded in Retrieval Practice Theory, Formative Assessment Theory, and Cognitive Load Theory, this study finds that students experienced the quizzes as surfacing forgotten material, normalizing shared knowledge gaps among peers, and building the confidence and articulation needed for professional practice. Students also identified clear design conditions under which the intervention worked best, including immediate feedback and content transparency. Rather than measuring causal learning gains, this study contributes practice-based evidence illustrating how retrieval-based formative assessment can complement project-based learning in advanced computing courses. The findings offer actionable guidance for educators seeking to strengthen disciplinary coherence and workforce readiness, and raise timely questions about retrieval fluency in an era where generative AI can surface facts on demand but cannot substitute for the judgment to evaluate them.

Authors

Dr. Tracy Anne Hammond http://orcid.org/https://0000-0001-7272-0507 Texas A&M University [biography]

Dr. Tracy Anne Hammond is a Professor of Computer Science and Engineering at Texas A&M University and Director of the Sketch Recognition Lab. She earned her Ph.D. in Electrical Engineering and Computer Science from the MIT Computer Science and Artificial Intelligence Laboratory at Massachusetts Institute of Technology, along with additional degrees from Columbia University in computer science, mathematics, applied physics, and anthropology.

Her research focuses on artificial intelligence, sketch recognition, intelligent user interfaces, haptics, and engineering education, with applications in education, health, accessibility, and related domains. She contributes to research, teaching, and professional service in AI and engineering education, with an emphasis on responsible and inclusive design.
Jobin Varughese http://orcid.org/https://0009-0002-9322-4179 Texas A&M University [biography]

Jobin Varughese is a doctoral student in the College of Engineering at Texas A&M University, where he also serves as Senior Educational Data Analyst at the Center for Teaching Excellence. He holds an M.S. in Management Information Systems with an emphasis in Data Science from Oklahoma State University and a B.S. in Electronics and Communication Engineering from Christ University. His research draws on learning analytics, AI in education, and human-computer interaction to observe, build, and study systems that learn how people learn. In this work, he partners closely with faculty, instructional staff, and students — believing that the most meaningful scholarship emerges not from research alone, but from collaborations with the people closest to the learning experience.
LaTasha Taylor Starr Texas A&M University [biography]

LaTasha graduated with a bachelor’s degree in Aeronautics from Tennessee State University. At the University of Washington (Seattle), LaTasha earned her first Engineering Master’s degree followed by a second Master’s in Industrial, Manufacturing and Systems Engineering from the University of Texas at Arlington (UTA) in 2020. Her passion for STEM education is evident through her professorship at Dallas College and Texas A&M University, where she not only teaches Engineering, but also paves the way for student internship collaborations.

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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