Recently, Professor Liu Sanya's team from the Faculty of Artificial Intelligence Education has achieved significant research progress by proposing a novel method for discovering learning patterns. This method offers an efficient and promising research tool for educational science. Their findings, titled "Automated discovery of symbolic laws governing skill acquisition from naturally occurring data," have been published in the Nature sub-journal Nature Computational Science.
This study pioneers AI-driven methods to automatically uncover fundamental learning patterns from large-scale, real-world data. It introduces a two-stage algorithm that accurately identifies core variables and reconstructs skill acquisition laws, surpassing traditional models in adaptability and fit metrics. Additionally, it discovers novel cognitive skill acquisition laws, validating and expanding existing research.
In recent years, Professor Liu Sanya has led his research team to systematically innovate in computational theories, methods, and applications in education. They have published a series of achievements in top journals and conferences in educational and information sciences, developing new paradigms in AI for Education Science (AI4EduSci) and computational education. Their work contributes to constructing China's distinctive educational science knowledge system and supporting the nation's educational development.
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