AI-Powered Skill Assessment and Credentialing System for Interactive Digital Applications

Interactive digital applications like video games, simulations, and virtual training environments are valuable tools for learning and professional development, offering dynamic environments that facilitate complex problem-solving and collaboration in dynamic, unstructured situations. However, effectively measuring the knowledge acquired within these experiences is difficult, as current evaluation systems are inadequate. Adapting these applications for assessment is often impossible or impractical, especially when dealing with proprietary software lacking available source code. As a result, assessment is typically limited to specialized educational tools that use pre-existing logging mechanisms, rather than broader, immersive environments

 

Researchers at Arizona State University have created a novel AI-based assessment and credentialling system that captures and analyzes user interaction data, including video and audio, from games or simulations without requiring source code access. It employs computer vision and natural language processing to interpret user inputs and application events, mapping demonstrated competencies to skill tags within a personalized knowledge graph. Credentials are issued when skills are verified, enabling integration with external platforms while ensuring privacy through anonymization and encryption. The system supports both real-time and post-activity assessments across diverse domains.

 

This technology offers an innovative AI-based system to evaluate learning by analyzing user interactions with unmodified digital applications to generate skill credentials.