Insan AI: Integrated Artificial Intelligence Learning Platform

Автор: Winanti, Yoga Prihastomo, Yulius Denny Prabowo, Achmad Sidik, Penny Hendriyati

Журнал: International Journal of Information Engineering and Electronic Business @ijieeb

Статья в выпуске: 1 vol.18, 2026 года.

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The integration of artificial intelligence (AI) in education presents significant challenges, such as gaps in educators' digital adaptability, ethical considerations, and inconsistent infrastructure. This study details the development and validation of the Insan AI Platform, an integrated learning solution designed to address these obstacles through adaptive AI tools for both teachers and students. The platform was developed using a user-centered prototyping methodology, drawing on comprehensive literature analysis, Focus Group Discussions with 26 educational stakeholders, and expert interviews. Key features include an AI Content Generator, a Virtual Tutor, and a Learning Analytics dashboard, all intended to facilitate personalized learning experiences and enhance teaching efficiency. User Acceptance Testing with 20 teachers demonstrated the platform's functional robustness, with perfect pass rates on all core features and a high usability score (SUS: 84.0). The platform architecture integrates multiple AI application programming interfaces (APIs) while maintaining responsive performance under varied network conditions. These findings indicate that the Insan AI Platform effectively meets user requirements and provides a strong foundation for broader educational implementation. Future development will focus on incorporating multilingual support and advanced learning analytics capabilities. According to a questionnaire completed by 26 users, there was a score increase of 22.42 after using the Insan AI platform. This indicates that the application has successfully met user requirements.

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Learning Platform, Artificial Intelligence, AI Solution, Prototyping Model, Generative AI

Короткий адрес: https://sciup.org/15020168

IDR: 15020168   |   DOI: 10.5815/ijieeb.2026.01.09