Algoritmik sanat pratikleri aracılığıyla programlamayı bağlamsallaştırmak: Lisans öğrencileri üzerine bir vaka çalışması

This dissertation explores algorithmic art as a pedagogical foundation for contextualized programming education, aiming to enhance computational thinking (CT) skills and engagement among undergraduate students who often disengage from traditional programming courses. The research developed the Algorithmic Art Praxis (ALAP) framework through a two-phase methodology. Phase 1 created the ALAP database, categorizing historical algorithmic artworks (1920-2000) by their use of core programming concepts (e.g., loops, recursion) and visual tools, providing structured, visually-grounded teaching resources. Phase 2 integrated the De-scription/In-scription pedagogical method within a case study. Students first analyze artworks to deconstruct underlying code (De-scription), developing CT skills like decomposition. They then apply these findings in creative coding projects (In-scription), iterating for visual expression. Implemented in a four-week workshop for design students at Özyeğin University and evaluated via surveys, interviews, and quantitative measures, the integrated ALAP framework significantly increased engagement and comprehension. Students shifted to view programming as an empowering creative medium. The framework successfully bridges computational and artistic practices, offering accessible, relevant programming education for non-programmers by leveraging visual familiarity and iterative design.