Enhancing Data Science Education: A Systematic Review of Gamified Learning Platforms for Decision-Making Skills Development

Data science is rapidly growing and impacting nearly every industry and research domain. As demand for skilled data scientists rises, data science education must prepare students not only with technical proficiency but also with the ability to make informed, data-driven decisions. Understanding the consequences of their decisions is crucial for data scientists. However, many data science students struggle to develop decision making skills due to insufficient practical experience and lack of exposure to real-world scenarios in their training. To address this gap, integrating realistic, interactive learning environments into educational platforms is essential. This paper presents a systematic literature review, conducted in accordance with PRISMA guidelines, to explore notable features of learning environments that enhance practical learning in data science education. The review identifies a significant need for platforms that enable students to engage with scenarios replicating real world decision-making complexities. Evidence from fields like business, healthcare, and engineering shows that gamification can enhance decision-making skills, suggesting similar approaches could be effective in data science education. By analyzing existing literature, this paper demonstrates the potential of gamified platforms to bridge the gap between theoretical knowledge and practical application, better preparing future data scientists with technical skills and informed decision-making abilities.