A Problem‐to‐Code Teaching Framework for Technology‐Enhanced Database Programming in Engineering Education: A Mixed‐Methods Study

ABSTRACT In engineering education contexts, students in database programming courses within the College of Informatics and Engineering often encounter challenges when transforming problem statements into executable code in technology‐enhanced programming environments, which often diminishes their self‐efficacy. To address this issue, this study introduces the Problem‐to‐Code Teaching Framework (PCTF), an instructional model that integrates the Function/Pattern‐Oriented Teaching Method with supporting scaffolding activities. The PCTF was implemented in an 18‐week PL/SQL course with 45 undergraduates at a university of science and technology in Taiwan, conducted in a technology‐enhanced environment using Oracle 19c databases and SQL IDE tools. Using a convergent mixed‐methods design, programming self‐efficacy was measured at three time points and analyzed with linear mixed‐effects regression, while 16 semi‐structured interviews captured students' perceptions of conceptual, procedural, and feedback scaffolds. Results indicated a steady increase in programming self‐efficacy across the semester, with the compensatory effect among students starting at lower levels. Deep learning approaches showed a strong, positive association, whereas the surface approach was not reliably associated. Qualitative findings indicated that multilayered scaffolds were perceived as supporting confidence and persistence by clarifying problem abstraction and solution modeling, structuring the problem‐to‐code conversion process, and providing timely feedback. Overall, the PCTF represents a context‐bounded yet structurally transferable, technology‐enhanced instructional framework that bridges problem analysis and code implementation, contributing to technology‐integrated data‐centric engineering programming education.