Current research on the construction of an autonomous knowledge system in the Chinese education discipline has entered a plateau stage or fallen into a bottleneck. To achieve breakthroughs while maintaining the correctness of research directions, it is essential to strictly follow the internal logic of knowledge production. Further in-depth research can be conducted from the perspectives of ontology, epistemology, axiology, and praxeology. Ontology addresses the question of what constitutes an autonomous knowledge system in the Chinese education discipline. The understanding of “autonomy” should not be generalized but should focus on the relationship between China and the world, adhering to the principle of taking China as the mainstay and using knowledge for China’s own purposes. Autonomy is neither self-isolation nor a return to antiquity. Since the introduction of Western learning into China, after more than a century of effort, China has established an autonomous knowledge system in the education discipline; however, its quality remains insufficient. The objective evaluation of China’s current autonomous knowledge system in the education discipline can be described as “existing but not excellent”. It is necessary to establish “thresholds” for educational knowledge: not all written expressions about education can be regarded as educational knowledge. Educational knowledge belongs to the domain of social science knowledge and should possess the functions of describing, explaining, and predicting educational phenomena. Epistemology mainly focuses on the production and validation of educational knowledge. Concepts should be proposed with caution to prevent conceptual inflation. The quality of educational knowledge largely depends on the quality of propositions, and middle-range theories can be regarded as a future direction for the construction of the educational knowledge system. The construction of an educational knowledge system cannot avoid value-related issues. Value involvement does not undermine the objectivity and universality of educational knowledge. Values should be treated as an important research object, with inquiry into which value orientations guiding educational practices are most conducive to students’ holistic development, individual development, and sustainable development. Universal human values such as fairness, justice, democracy, and freedom should be upheld, while traditional Chinese educational knowledge should undergo value-based evaluation and selection. Educational knowledge emerges from practice and is tested through practice. Researchers should engage deeply with practice and employ diverse methods to investigate genuine questions arising in practice, collaboratively producing knowledge with practitioners. Practical knowledge should be fully explored, generalized, and abstracted, and then elevated into theoretical knowledge with a higher level of abstraction.

Through a dialogue with Professor Gary McCulloch from the UCL Institute of Education, this study examines the developmental trajectory, institutional foundations, and practical challenges of constructing an autonomous knowledge system within British educational research. Since the 1950s, the study of British education has shifted from a multidisciplinary structure of “educational studies” toward an “educational research” model that explores interdisciplinary pathways, accompanied by transformations in knowledge organization and research methodologies. Focusing on the positioning of British education as a “field” rather than a “discipline,” this study investigates the construction of its discourse on “autonomy,” the role of institutional spaces, and debates around disciplinary identity. Drawing from these dimensions, it reflects on the construction of an autonomous Chinese educational knowledge system under the intertwined pressures of cultural subjectivity and institutional challenges in the new era, offering multidimensional insights and references.

Classroom teaching serves as the primary channel for talent cultivation. Against the backdrop of rapid intelligent technology development, large-scale pre-trained language models have gradually permeated educational scenarios, becoming a key technological variable driving the transformation of teaching paradigms. However, the current application effectiveness of large models in education exhibits significant heterogeneity, with evaluation dimensions mostly limited to technical performance aspects, while their pedagogical appropriateness and goal attainment urgently require empirical verification. This study constructs a three-dimensional evaluation model of “value guidance-knowledge construction-cognitive development,” adopting a comparative experimental design to systematically evaluate teaching texts generated by six mainstream large models (including three domestic and three international) across multiple K-12 subjects (Chinese, mathematics, foreign languages, integrated sciences, and integrated humanities), and conducts comparative analysis with expert teachers’ parallel lesson teaching records. The findings reveal that, first, in the value guidance dimension, teacher-led teaching demonstrates significant moral education-dominant characteristics, domestic models exhibit balanced value guidance with consistent performance across core value dimensions, while international models show differentiated value orientation—excelling in dimensions like social responsibility but displaying structural deficiencies in national identity and cultural inheritance. Second, in knowledge construction, teachers demonstrate high curriculum content focus, whereas large models exhibit stronger knowledge extensibility, particularly showing significant advantages in constructing interdisciplinary knowledge networks. Finally, in cognitive development, large models prove significantly more effective in promoting higher-order thinking (including complex problem-solving, knowledge transfer, and innovative thinking), while teacher-led teaching excels in declarative knowledge mastery and situated learning experiences but risks cognitive fixation. The study aims to provide references for educational practitioners to scientifically and rationally apply large models to empower classroom teaching improvement, offering important empirical evidence for reconstructing a new “human-machine collaborative” educational paradigm and promoting high-quality educational development in the AI era.

Learners’ perceived learning effectiveness in VR environments is influenced by teaching presence and need for cognition; however, the mechanisms underlying these relationships remain insufficiently understood. Guided by the Community of Inquiry framework, this study surveyed a sample of 1,347 university students to identify latent profiles of teaching presence in VR-based instruction using latent profile analysis. In addition, network analysis was employed to examine the structural characteristics and core components of each profile, and the effects of different profiles on perceived learning effectiveness were tested while also assessing the moderating role of need for cognition. The results revealed that: (1) teaching presence in VR instruction can be categorized into three profiles—“Basic Construction Type,” “Innovative Leading Type,” and “Balanced Progressive Type”—which differed significantly across the dimensions of instructional design, facilitation, and direct instruction; (2) network analysis indicated distinct differences among the three profiles in network density, core nodes, and cross-dimensional interaction levels, with the “Innovative Leading Type” exhibiting the highest level of integration and systemic coordination; and (3) the “Innovative Leading Type” achieved the highest score in perceived learning effectiveness, with need for cognition significantly moderating the differences between the “Basic Construction Type” and the other two profiles. These findings illuminate the latent profiles of teaching presence, their network structures, and their differential impacts on perceived learning effectiveness in VR contexts, offering theoretical insights and practical implications for teacher professional development and personalized instructional support.

Generative artificial intelligence (GAI) is attracting growing attention for its potential roles in project-based learning (PBL). However, there is still limited evidence on how teachers and students actually use GAI in authentic PBL classrooms, and how students interact with GAI during the learning process. This study examines GAI use in PBL and proposes a teacher–student dual-layer nested framework that integrates roles, technologies, functions, and interaction patterns. Based on a coding analysis of 18 classroom episodes captured at the product-construction stage of AI-enhanced PBL, we found that teachers primarily positioned GAI as a mentor and a learning partner. Teachers’ use of GAI was mainly situated at the transformation level, with assessment and feedback as the dominant function. Students’ interactions with GAI exhibited a high degree of autonomy. Building on these findings, we discuss implications for human–AI collaboration in the development of GAI-PBL, teachers’ TPACK professional growth, and the cultivation of student agency.

As a strategic technology leading the new round of scientific and technological revolution, Artificial Intelligence (AI) technology, while profoundly changing the ecology of education and teaching, also brings many ethical risks and challenges. How to assess ethical risks in order to maximize the benefits of intelligent technology has become an important issue for the healthy development of educational artificial intelligence. Through theoretical research, expert interviews, literature research, etc., four primary indicators, 13 secondary indicators, and 31 tertiary indicators are identified, such as the risk of educational technology ontology, the risk of educational data, the risk of machine algorithms, and the risk of educational applications. The corresponding questionnaires are designed using the Analytic Hierarchy Process, and the weights of the indicators are calculated using MATLAB software to establish a systematic and robust ethical risk assessment system. Cases are then selected for evaluation to validate its effectiveness. The construction of the ethical risk assessment index system applicable to the application of AI in education can be used to identify and assess the risks in specific educational scenarios, help education management departments, schools, teachers, and students standardize and rationally apply AI technology to improve teaching and learning, and provide a basis for the governance of AI in education.

In the critical phase of building a powerful education nation and advancing Chinese-style education modernization, promoting the spirit of educators has become a core issue in teacher team development. The key to transforming this spirit from a value-driven advocacy into a practical norm lies in taking the teachers’ belief system as the inherent foundation. As the core carrier for the emergence, cultivation, and practical transformation of the educators spirit, the teachers’ belief system currently faces three major practical bottlenecks: cultural inheritance, rights allocation, and institutional support, which restrict the realization of high-quality education development and the cultivation of the educators spirit. Centering on the construction logic and practical path of the teachers’ belief system oriented towards the spirit of educators, and adopting the “value-theory-practice” analytical framework, this study integrates philosophical hermeneutics, communicative action theory, and social systems theory to construct an “efficiency-structure” integrated model. The model takes “history-norm-evolution” as its three-dimensional theoretical foundation, comprising three major efficiency systems—cultural generation, policy transformation, and ecological evolution and a four-tiered double-loop structure—meaning base, dynamic axis, action response, and regulatory feedback, forming a dynamic cycle of “structure supporting efficiency and efficiency feeding back structure”. Targeting the three practical bottlenecks, the model clarifies the core function of the teachers’ belief system as a “meaning translation hub”, reveals the dialectical relationship of “value guidance-practical carrier” between the educators spirit and the teachers’ belief system, and breaks through the static and individual limitations of traditional belief research. It provides inherent theoretical support and practical operation mechanisms for the cultivation of the educators spirit and the implementation of the fundamental task of fostering virtue through education.

“Inquiry Practice” is a core competency targeted in China’s primary and secondary science curricula and has been a key educational concept and instructional approach in science education globally over the past three decades. While there is a strong advocacy for integrating authentic inquiry that mirrors scientific practice into the classroom, empirical analyses on the alignment between classroom inquiry and real scientific inquiry remain scarce, and no consensus has been reached on what constitutes “authentic classroom inquiry.” This study analyzes 34 award-winning elementary science class videos and lesson plans from a city in eastern China to examine how inquiry tasks are implemented in the classroom, assess their authenticity, and discuss what forms of authentic inquiry are needed in elementary science education. Findings reveal that over 90% of the classes included at least one inquiry task, with half to two-thirds of class time on average devoted to inquiry activities. However, most tasks involved simple experiments or observations, differing significantly from authentic scientific inquiry in both cognitive and epistemological dimensions. Classroom inquiry exhibited low openness, with teachers dominating the introduction and conclusion phases, while students rarely engaged in autonomous exploration, negotiation, or argumentation. Although fully replicating scientific inquiry in school settings may not be feasible, teachers should strive to balance structure and openness in inquiry tasks, guiding students to simulate authentic scientific practices through cognitive, epistemological, and social dimensions.

This study adopts a case study approach, taking the doctoral dissertations from Beijing Normal University and East China Normal University as two cases, to explore the content and forms of methodological statements on qualitative research. The study finds that the methodological statements feature an internal structure of two-level logical linkage, an explicit function of legitimizing justification, and an implicit assumption of positional reconstruction. In terms of internal logic, the first-level linkage refers to the intrinsic continuity between ontological and epistemological positions within the conceptual world, achieved through the particularity of social science research subjects and the dual role of researchers. The second-level linkage connects these ontological and epistemological positions with methodological choices in the empirical world, realized through the articulation of the research orientation. As for its explicit function, researchers consciously adopt historical, disciplinary, and situational justifications in their writing to legitimize their methodological choices. As for its implicit assumption, qualitative, quantitative, and mixed-methods researchers presuppose the dominance of the positivist paradigm and quantitative methodology. While they reproduce the prevailing methodological stance in different yet convergent ways through their writing, they also inadvertently facilitate its reconstruction through qualitative methods and associated paradigms. Over the past decade, the methodological statements on qualitative research in doctoral dissertations of education in China have demonstrated a hybrid characteristic of “spirality” and “escalation”: while reflecting a growing methodological self-awareness, they also reveal the potential risk of a collective unconsciousness.