Digital Learning Empowering Sustainable Education: Evidence from the Determinants of Chinese College Students’ Knowledge Innovation Capability

With the rapid advancement of artificial intelligence technology, the role of Artificial Intelligence Generated Content (AIGC) applications within digital learning communities has become increasingly significant. Enhancing the level of knowledge innovation through the integration of human and artificial intelligence has emerged as a critical issue. Grounded in social cognitive theory, this study utilizes a sample of 407 Super Star Learn community learners as a case study. It applies the Fuzzy Set Qualitative Comparative Analysis (fsQCA) method to investigate the synergistic effects of technological environment, cultural context, and individual cognitive factors in promoting learners’ knowledge innovation capabilities. The results show the following: (1) No single condition constitutes a prerequisite for learners to achieve high-level knowledge innovation when acting in isolation. However, enhancing technical capabilities has a relatively universal impact on promoting learners to achieve these results. (2) The multiple concurrency of the technological environment, cultural environment, and individual cognitive conditions has generated multiple configuration patterns that promote knowledge innovation, indicating that the paths leading to learners’ high-level innovation exhibit the characteristic of numerous concurrency. Therefore, it is suggested that digital learning communities actively explore new paths for sustainable knowledge innovation and development driven by generative artificial intelligence technology, thereby injecting sustainable impetus into the development and innovation process of learners, contributing to the goals of sustainable education.