This study addresses the global challenges of rapid technological evolution and complex problem-solving by investigating how project-based learning (PBL), through a structured multi-support system, can effectively cultivate self-directed learning (SDL) competencies among engineering students. Focusing on the Chinese higher education context, it seeks to answer the following questions: How do teachers, peers, and AI tools within PBL contribute to the development of multidimensional SDL by providing resource, cognitive, and emotional support? What are the key mechanisms underlying this process? And what design principles can be derived that hold universal relevance for the global engineering education community? The research aims to uncover the interactive relationships between support actors and core functions in PBL, construct an analytical framework for optimizing SDL development, and provide evidence-based insights for institutions worldwide grappling with large-scale education, industry-academia collaboration, and digital transformation. The theoretical framework integrates Activity Theory, which views PBL as a dynamic activity system; Situated Learning Theory, which emphasizes learning through participation in authentic practices; and Self-Determination Theory, which centers on fulfilling learners’ psychological needs for autonomy, competence, and relatedness. Together, these perspectives offer a comprehensive, cross-culturally comparable lens for understanding how PBL promotes SDL through systemic, contextual, and motivational dimensions.

A qualitative research approach was adopted to gain an in-depth understanding of students’ subjective experiences, meaning-making, and competency development during PBL. Data were collected through semi-structured interviews designed to explore participants’ PBL experiences, their perceptions of support from various actors, and their demonstrated SDL behaviors. The study involved 49 engineering students from a comprehensive Chinese university (“H University”) who were enrolled in PBL-integrated courses. Interview transcripts were analyzed using thematic analysis to identify patterns linking support actors, support functions, and SDL development. Adhering to rigorous international social science research standards, this study yields rich contextual data that provide a foundation for future cross-cultural comparative research. By focusing on the “teacher–peer–AI tool” support triad, the work directly engages with globally shared concerns in engineering education, such as blended learning support, collaborative learning quality, and technology-enabled empowerment, thereby facilitating scholarly dialogue with international peers and literature.

The analysis validates SDL as a multidimensional construct encompassing learning initiative, responsibility, persistence, and self-regulation. It further reveals that PBL fosters SDL through an interactive “multi-actor core-function” support system, wherein teachers provide expert scaffolding and guidance, peers contribute through collaborative co-construction and emotional support, and AI tools offer instant resource access and personalized assistance across three functional dimensions: resource support, cognitive support, and emotional support. The most significant SDL development occurs when these actors operate synergistically. Moreover, the progression of SDL requires dynamic adaptation in PBL design, meaning external support should be gradually reduced as learners advance, transitioning from highly structured assistance toward greater autonomy. This study concludes that a PBL design grounded in activity systems, situated practice, and psychological need satisfaction is essential for cultivating future engineers’ SDL competencies. The proposed “Multi-Actor Core-Function” Support System Framework not only offers a concrete pathway for engineering education reform in China but also contributes a universally relevant perspective on effectively integrating human and technological resources in digital-age learning environments. Furthermore, the empirical analysis of the multi-dimensionality of SDL provides specific teaching paths and evidence-based support for the graduate qualities emphasized by international certification systems (including lifelong learning, complex problem-solving, and teamwork), thereby promoting the improvement of global engineering education quality based on evidence.

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