Since the 20th National Congress, with the emphasis on innovation and entrepreneurship on country, innovation and entrepreneurship education has become an important part of talent training in universities. The constructivist learning concept advocates that students' learning should respect their own meaning construction, and social mutual assistance and situational construction to acquire knowledge. Based on the current issue of students' innovation and entrepreneurship, this article takes the constructivist learning perspective as a guide to explore strategies to enhance their innovation and entrepreneurship abilities, and is committed to promoting the improvement of their abilities.

The country has vigorously promoted the work of school aesthetic education, which is a great opportunity and also a major challenge for the art major of Yili Normal University. At present, the quality of teaching in the art major is not very optimistic. How to ensure and improve the teaching quality of the art major is worth pondering. Based on the investigation of the current situation of teaching quality in the art college, this article identifies the factors that hinder the improvement of teaching quality, analyzes the reasons, and ultimately provides strategies to improve the teaching quality of the art major, providing effective reference suggestions to ensure the teaching quality of the major.

The Primary and secondary shadow education refers to a kind of unofficial education that exists outside the traditional mainstream primary and secondary education system in China, with both commercial and educational attributes. As the primary and secondary school stage is an important key stage for further education, existing research mainly focuses on the spatial distribution of primary and secondary school basic education facilities and non-subject training, with fewer studies targeting primary and secondary school subject tutoring shadow education. With the changes in China’s education industry and the introduction of the Double Reduction Policy, there is an urgent need to conduct in-depth research on the spatial aggregation characteristics and influencing factors of Shadow Education Enterprises for primary and secondary school students. This paper takes the main urban area of Zhengzhou City as the study area, and takes primary and secondary school Shadow Education Enterprises as the research object, and applies spatial analysis methods such as kernel density, nearest-neighbor index, and geographic detector to quantitatively analyze the spatial distribution characteristics of primary and secondary school shadow education tutoring enterprises in Zhengzhou City and the factors affecting them The results show that: 1) The overall spatial pattern of primary and secondary school tutoring Shadow Education Enterprises in the main urban area of Zhengzhou City has largely formed a core-edge structural feature that spreads from the urban center to the periphery, and presents the spatial agglomeration feature of “double nuclei many times” distributed along both sides of the Beijing-Guangzhou Line. 2) The distribution of mentoring Shadow Education Enterprises in the main urban area of Zhengzhou City in relation to provincial model primary and secondary schools is significant and there is a significant difference between the distribution around secondary schools and primary schools. 3) The spatial distribution of Shadow Education Enterprises in the main urban area of Zhengzhou City is mainly influenced by factors such as the size of the school-age population, the level of commercial development, the location of school buildings and the accessibility of transport.

The study documents the model of the knowledge transfer process between the University, the Vocational Training Center and the industrial actors. The research seeks to answer to the following questions. Where is new knowledge generated? Where does knowledge originate from? Is there a central actor? If so, which organization? Hypotheses tested by the research: H1: Knowledge starts from the higher education institution. H2: Most “new knowledge” is generated in universities and large multinational companies. H3: The university is a central actor in the knowledge flow, transmitting both hard and soft skills, as well as subject (‘know-what’), organizational (‘know-why’), use (‘know-how’), relational (‘know-who’), and creative (‘care-why’) knowledge. The aim of the research is to model the way of knowledge flow between the collaborating institutions. The novelty of this research is that it extends the analysis of the knowledge flow process not only to the actors of previous researches (higher education institutions, business organizations, and government) but also to secondary vocational education and training institutions. The methodology used in the research is the analysis of the documents of the actors investigated and the questionnaire survey among the participants. Knowledge transfer is the responsibility of the university and its partner training and business organizations. In vocational education and training, knowledge flows based on the knowledge economy, innovation and technological development are planned, managed and operational. The research has shown that knowledge is a specific good that it is indivisible in its production and consumption, that it is easy and cheap to transfer and learn.

This research evaluates the regionalization of tourism in Hungary, revealing the breakdown of the national gross domestic product (GDP) of tourism. It also explores the density, spatial variations, and features of these indicators. A multimodal approach is used to evaluate the competitiveness of Hungarian counties, and the distribution of these tourism regions is analyzed using the tourism penetration index. Furthermore, regional GDP is calculated for the whole territory of Hungary. The study identifies significant regional disparities in tourism competitiveness, highlighting Budapest-Central Danube as the most competitive region and Lake Balaton as underperforming despite its potential. The research contributes by providing a detailed regional GDP analysis and emphasizing the need for targeted policy interventions to enhance tourism development across all regions.

In the wake of the COVID-19 pandemic, the prevalence of online education in primary education has exhibited an upward trajectory. Relative to traditional learning environments, online instruction has evolved into a pivotal pedagogical modality for contemporary students. Thus, to comprehensively comprehend the repercussions of environmental changes on students’ psychological well-being in the backdrop of prolonged online education, this study employs an innovative methodology. Founded upon three elemental feature sequences—images, acoustics, and text extracted from online learning data—the model ingeniously amalgamates these facets. The fusion methodology aims to synergistically harness information from diverse perceptual channels to capture the students’ psychological states more comprehensively and accurately. To discern emotional features, the model leverages support vector machines (SVM), exhibiting commendable proficiency in handling emotional information. Moreover, to enhance the efficacy of psychological well-being prediction, this study incorporates an attention mechanism into the traditional Convolutional Neural Network (CNN) architecture. By innovatively introducing this attention mechanism in CNN, the study observes a significant improvement in accuracy in identifying six psychological features, demonstrating the effectiveness of attention mechanisms in deep learning models. Finally, beyond model performance validation, this study delves into a profound analysis of the impact of environmental changes on students’ psychological well-being. This analysis furnishes valuable insights for formulating pertinent instructional strategies in the protracted context of online education, aiding educational institutions in better addressing the challenges posed to students’ psychological well-being in novel learning environments.