Gomes, João PedroMonteiro, RedneyMoreira, AndréPinho, AnabelaMendonça, VítorCunha, Carlos R.2026-05-202026-05-202026Gomes, J.P.; Monteiro, R.; Moreira, A.; Mendonça, V.; Pinho, A. R.; Cunha, C. (2026). Programming Language Choices for Introductory Computer Science Courses: Global Trends from the 2023 Shanghai Ranking. In Rocha, A.; Adeli, H.; Poniszewska-Marańda, A.; Moreira, F.; Bianchi, I. (Eds.) Emerging Trends in Information Systems and Technologies. WorldCIST 2025. Springer. Vol.1578, p. 281-294. ISBN 9783032007001978303200700197830320070182367-33702367-3389http://hdl.handle.net/10198/36748This study examines the selection of programming languages in the first two introductory computer science courses at top universities globally, emphasizing their distribution, progression, and regional variations. Data were gathered from 150 programming courses across 83 institutions ranked in the Shanghai 2023 Global Ranking of Academic Subjects for Computer Science and Engineering. The analysis reveals that Python is the primary language used in CS1 (32.5%), while Java dominates CS2 (56.7%), collectively accounting for over half of the offerings. Additionally, Java remains a common choice when a single language is used across both courses. Regional preferences exhibit significant diversity: Asian institutions favor lower-level languages like C and C++, whereas European universities explore functional programming languages like Haskell. Common transitions between courses include moves from Python to Java and from C to Java, indicating a preference for more robust languages at advanced levels. These findings offer valuable insights into global programming education trends adopted by leading universities and provide references for curriculum design and pedagogical strategies in introductory programming courses. Limitations include incomplete data from some institutions and variability in information accessibility, suggesting opportunities for future research.engProgramming languagesComputer scienceHigher educationCurriculum designRegional analysisconference paper10.1007/978-3-032-00701-8_24