National institutes of outstanding engineers serve as an innovative platform for the cultivation of outstanding engineers and play a crucial role in building a new workforce. To elucidate the complex characteristics and operational mechanisms of the outstanding engineer cultivation system, a structured multi-case study was conducted on four national institutes of outstanding engineers. The analysis revealed that China’s outstanding engineer cultivation system exhibited complex characteristics of aggregation, diversity, flows, and nonlinearity. Higher education institutions (HEIs) and enterprises implemented self-adaptive internal reforms to adapt to external environmental stimuli, including interdisciplinary curriculum reforms, the establishment of authentic training, practice, and internship systems, and expanded investments in university‒enterprise cooperation. They constructed innovative and standardized structures, including the whole-process collaboration and consultation system for talent cultivation, the university‒enterprise supervisor group collaboration mechanism, and the education model driven by industrial research projects. This study proposes a series of optimization paths from conceptual consensus, resource sharing, and joint construction by agents to achieve high-quality construction and operation of national institutes of outstanding engineers.

To address core issues such as the insufficient foundation of artificial intelligence (AI) education in the development of new engineering disciplines and its disconnection from industrial and research applications, this study proposed an approach to building an AI+ curriculum system driven by industry‒education and research‒education integration. By deeply integrating resources from leading enterprises and cutting-edge research projects, real industry needs and scientific research challenges were transformed into modular teaching cases. A course cluster blending general and specialized knowledge and integrating undergraduate and postgraduate education was developed, alongside the innovative implementation of a teaching model featuring project-driven approaches and course‒competition integration. The results demonstrated that the system significantly enhanced the AI innovation and practical competencies of non-information major students, providing a replicable and generalizable new educational paradigm for empowering the intelligent transformation of traditional industries.

Drawing upon evolutionary game theory, this study constructs a four-party evolutionary game model involving the government, industry, universities, and research institutes. By analyzing the game process of collaborative cultivation of high-level outstanding engineers and identifying the key factors influencing game stakeholders’ strategy choices through simulation, this study provides a decision-making basis for multi-stakeholder collaborative cultivation. The findings indicate that the evolution of the collaborative cultivation system exhibits stage-based dynamic transition, with the transition efficiency influenced by government regulation costs. In addition, there exists a positive feedback mechanism based on shared benefits among industry, universities, and research institutes where stable total collaborative benefits and a reasonable distribution structure are essential for sustaining this positive feedback loop. Moreover, the long-term stability of the collaborative cultivation system depends on the relative relationship between collaborative benefits and opportunity costs, with government reward and punishment intensity serving as a critical variable in balancing this relationship. Based on these findings, this study recommends that the government, industry, universities, and research institutes actively fulfill their respective responsibilities. The government needs to establish a sound regulatory framework. Enterprises are expected to actively assume their industrial responsibility. Universities can proactively seek cooperation opportunities. Research institutes are advised to enthusiastically provide research support. Collectively, these efforts are expected to improve the quality and efficiency of collaborative cultivation of high-level outstanding engineers.

Digital literacy is a vital component of the comprehensive qualities of talents in the digital era. Students’ digital literacy cultivation serves as an essential path to developing high-quality talent that meets the demands of the digital era. Nevertheless, the concept of students’ digital literacy cultivation has overly emphasized the operational use of technical tools, neglecting the human‒AI collaborative autonomous learning advocated in the intelligent era. This has become a bottleneck that restrains students’ digital literacy cultivation. Generative artificial intelligence (GenAI) holds immense potential in creating flexible, open, inclusive, and shared human‒AI collaborative environments. These environments could guide students toward self-organized learning, offering a new opportunity to overcome the aforementioned challenges. Accordingly, this study constructed a students’ digital literacy cultivation model based on self-organized learning theory and proposed the generative artificial-intelligence fusion in self-organized learning environments (GAiSOLEs) teaching model aimed at fostering students’ digital literacy. Moreover, this study performed a quasi-experiment in the information science and technology curriculum, aiming to verify the impact of the GAiSOLEs teaching model on students’ digital literacy cultivation. The results showed that the GAiSOLEs teaching model could significantly improve students’ overall digital literacy level, as well as enhance their information awareness, computational thinking, and digital learning and innovation skills. However, its effect on improving information social responsibility was not statistically significant. In light of this, this study suggests that attention should be paid to technological ethics and security, the construction of controllable educational large language models, and the cultivation of students’ digital knowledge and skills to avoid cognitive traps. Furthermore, it is advised to provide GenAI teaching training to enhance teachers’ digital literacy.

Reforming traditional teaching and promoting innovation in teaching content, models, technology, and other aspects is regarded as an effective approach to cultivating primary and secondary school student creativity. However, there is inconsistency in empirical research conclusions. This study conducted a meta-analysis of 67 quasi-experimental studies. The findings showed that compared with traditional teaching, teaching innovation could promote the development of student overall creativity, with a medium effect. Specifically, the impact on subject/course creative thinking yielded a large effect; the impact on creative products and general-domain creative thinking was a medium effect; and the impact on creative personality was a small effect. The moderation analysis found that the impact of teaching innovation on student creativity development was moderated by factors such as educational stage, cultural sphere, teaching innovation type, creativity course format, and teaching experimental duration. Four practical suggestions are put forward accordingly. First, attention should be paid to the phased characteristics of creativity cultivation. Second, creativity-integrated courses are suggested to be adopted as the primary course form. Third, teaching model innovation ought to serve as the core implementation path. Fourth, teaching technology innovation should be leveraged to empower creativity cultivation.