Advancements, Challenges, and Emerging Trends in Computer Science Education: A Systematic Literature Review of Academic and Professional Learning

The changing job market requires an educational system that can adapt to the evolving skills that are required, ensuring that the teaching methods are aligned with the preferences of young learners. The aim of this paper is to investigate various learning perspectives from students, teachers, and adult learners, as well as to examine industry challenges and opportunities. It emphasizes the need for a flexible and dynamic educational approach to prepare students for current and future labor markets and technological advancements. This paper is also an editorial paper, summarizing submitted papers to the workshop. A Systematic Literature Review (SLR) was used to search and select the latest research in the field of computer science education, focusing on the use of Artificial Intelligence (AI) to improve learning. Six research questions were addressed, considering not only the three perspectives (student, teacher, and practitioner), but also topics such as skills and tools. Key topics highlight the importance of integrating soft skills and ethics in computer science education, increasing the use of AI in teaching/learning, developing new online/collaborative technology-enabled teaching models, and increasing interest in teacher and practitioner continuous training. In the learning process, both the teacher and the student have reciprocal influence, and the teacher plays the role of facilitator, allowing students to learn at their own pace. In industry settings, the need to develop soft skills in recent computer science graduates and align these skills with the rapidly evolving requirements of the labor market was acknowledged.