Programming Languages for AI Readiness and Creativity Enhancement in Education: A Systematic Literature Review

Abstract Artificial intelligence (AI) readiness and creativity enhancement are central goals of 21st-century education, yet the research landscape regarding effective programming languages and learning approaches to achieve them remains fragmented. This systematic literature review, maps the empirical evidence from 24 peer-reviewed studies (2022-2025) selected from the Scopus and ERIC databases. The analysis reveals that the effectiveness of a programming language is not inherent but is critically determined by pedagogical design. These are particularly long-term intervention duration and an authentic project-based orientation. A complex relationship between the two outcomes was found, block-based environments in contextual projects emerge as an ideal nexus for fostering AI readiness while formally measuring creativity at the foundational level. Conversely, at the higher education level, a focus on deep AI readiness tends to be accompanied by more holistic and less measured reporting of creativity. The primary contribution of this review is a two-dimensional classification framework for programming languages and pedagogical approaches, which serves as a strategic map for educators and curriculum designers. This framework provides guidance for aligning tools and methods with specific learning goals. whether optimizing for measurable creativity or deep technical readiness, the guidance is more effectively prepare students for the AI era.