Enhancing Student Learning Through Computational Techniques: A Review Of Educational Technologies In Computer Science

Abstract

This paper presents a systematic literature review on the integration of computational techniques and educational technologies in computer science education. The study explores three main research questions: (1) Which computational techniques and educational technologies are most effective in enhancing student learning outcomes in computer science? (2) How do these technologies influence key aspects of learning, such as cognitive development, problem-solving abilities, and student engagement? (3) What are the main challenges and limitations associated with the implementation of these technologies, and how can they be addressed? Through an analysis of recent studies, we identify the most effective technologies, including virtual reality (VR), artificial intelligence (AI), learning analytics, and gamification. These tools significantly improve cognitive development, foster problem-solving skills, and boost student engagement. However, the findings also highlight several challenges, such as infrastructure limitations, lack of teacher training, and issues related to student accessibility and equity. To address these challenges, we propose recommendations focusing on infrastructure development, professional development for educators, and strategies to promote equitable access and integration. The paper concludes that while educational technologies offer significant potential to transform computer science education, addressing implementation barriers is critical to realizing their full impact.