Development of an interactive educational game for early childhood education

Abstract

The integration of digital technologies into early childhood education has increased the demand for educational tools that are accessible, pedagogically grounded, and aligned with official curricular guidelines. In this context, educational and serious games have emerged as promising resources to support learning through playful and interactive experiences. This paper presents the design, implementation, and exploratory evaluation of a web-based educational game platform aimed at supporting early childhood education in accordance with the Brazilian Base Nacional Comum Curricular (BNCC). The proposed platform integrates pedagogical principles with game-based learning strategies and offers a set of interactive mini-games designed to stimulate fundamental competencies, including motor coordination, language development, emotional recognition, and logical reasoning. The system was developed using open-source technologies and follows a three-layer web architecture composed of frontend, backend, and data persistence layers, ensuring accessibility, scalability, and compatibility with multiple devices without requiring local installation. An exploratory qualitative evaluation was conducted focusing on functional performance, usability, accessibility, and pedagogical coherence. The results indicate that the platform operates reliably across different devices, provides an intuitive and age-appropriate interface, and demonstrates strong alignment between gameplay mechanics and intended learning objectives. The main contributions of this work include the explicit alignment of educational game design with BNCC competencies, the adoption of a modular and accessible web-based architecture, and the presentation of an educational game platform grounded in both pedagogical theory and applied computing. These findings support the viability of web-based serious games as scalable and inclusive tools for early childhood education and provide a foundation for future empirical studies and platform extensions.