Examinando por Autor "Petrov-Valchev, Bozhidar"

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    Deep Neural Tower: A Game to Teach AI Concepts
    (Institute of Electrical and Electronics Engineers, 2024-12-10) Petrov-Valchev, Bozhidar; Núñez-Vidal, Esther; Hristov-Kalamov, Nikola; Zapata-Cáceres, María; Palacios-Alonso, Daniel
    This study explores the integration of innovative technologies, such as video games and artificial intelligence (AI), in education, focusing on the use of Deep Reinforcement Learning (DRL) to create engaging educational tools. The project “Deep Neural Tower” presents a video game designed to teach fundamental AI concepts to high school students through interactive gameplay. Developed using the Unity engine and ML-Agents toolkit, the game incorporates AI agents that learn and adapt through interaction with the environment. Students encounter challenges illustrating key AI concepts, such as agent-environment interaction, reward systems, and neural networks, which promote active learning and knowledge retention. Tested with 111 high school students, the game showed positive results in usability and engagement, enhancing understanding of complex AI concepts. This paper discusses the pedagogical benefits of using AI in education and concludes that combining advanced AI techniques with interactive gameplay has immense potential to transform STEM education.