This paper explores the extent and direction of the impact of digital technology-enabled rural cultural tourism development by constructing fixed-effects models, GMM models, spatial Durbin models, Moran indexes, mediation effects and other models. Using the hierarchical analysis method to construct measurement indexes from two aspects of scale and benefit, and then using the coupling coordination degree model to measure the level of digital rural tourism development, to summarize the level of development and coordination of cultural tourism industry in rural areas. The results show that the difference between the minimum value and the maximum value of the rural digitalization level is about 8, and the large gap also reflects to some extent the uneven development of digital rural tourism in different regions. Digital rural tourism has a significant impact on rural economic development and non-rural non-farm employment level, and its impact coefficient is 0.138 and 0.784 respectively. in the data measurement of 2017 and 2022, the more significant the degree of aggregation is, the faster the level of development of digital rural tourism becomes. the comprehensive evaluation index of digital rural tourism in the sample area in 2021 is 0.82, which is at a high level, and the sample region’s service quality satisfaction is also at a high level. Therefore, this paper analyzes from various aspects that the development of digital tourism can promote the sustainable development of rural economy and realize rural revitalization.

There is a close quantitative relationship between college management and college students’ employability. This paper adopts Adaboost integration algorithm to construct an employment management system that integrates graduates’ personalized recommendation. And it divides graduates according to their personal situation and analyzes the relationship between their personal ability and employment recommendation. In addition, the relationship between the management based on the system of this paper and the employment ability of graduates in colleges and universities is quantitatively analyzed by logistic regression model. A questionnaire survey is taken to assess the changes in graduates’ employability as a result of the employment management activities organized by colleges and universities. The recommendation system constructed in this paper has a higher accuracy rate of 6.92% and 16.32% than the comparison system 1 and 2 respectively when the number of job recommendations is 60. And its recall rate and F1 value are also consistently higher than the comparison system. In this paper, the system divides the sampled 200 graduates into 5 categories to provide more accurate employment recommendation for graduates of different categories. The results of regression analysis show that universities organize employment management activities can improve the employability of graduates. For example, for every unit of “Interview practice”, the employability of graduates increases by 0.349. The results of the questionnaire survey show that the employability of graduates, both individually and as a whole, improves to different degrees after participating in the management activities organized by colleges and universities. In conclusion, the construction of employment management system in universities and the organization of employment management activities can improve the quality and ability of graduates’ employment.

This paper firstly studies the current situation of rural e-commerce development in China, and then collects the gross output value of agriculture, forestry, animal husbandry and fishery, express delivery volume, rural delivery routes and so on through consulting the relevant official data of the National Bureau of Statistics, which provides an effective and reliable data basis for the construction of econometric model. Through the establishment of a fixed-effects model to analyze the empirical results, to explore the role of rural e-commerce platform development on the promotion of the economy. Finally, with the help of the spatial Durbin model to measure the spatial spillover effect, analyze whether the development of rural e-commerce can reduce the urban-rural income gap. The results show that the number of Taobao villages, kilometers of rural delivery routes, and 10,000 rural broadband access users are the explanatory variables, and the gross output value of agriculture, forestry, animal husbandry and fishery is the explanatory variable, and the coefficients are 0.0156, 0.0781, and 0.0442, with the p-value less than 0.01. Therefore, the better the development of rural ecommerce, the better the economic development is. And the increase in the level of economic development can significantly reduce the urban-rural income gap with an estimated parameter of – 0.022.

The integration of science and education is conducive to promoting the integrated development of education, science and technology, and talents, and is a key path for the high-quality development of vocational education and serving the strategy of a strong education nation. This paper explains the necessity of integrating science and technology with education, and realizes the path design of vocational education quality improvement based on the new concept of science and education integration. Then, the quality of science and education integration in vocational education is evaluated using hierarchical analysis and fuzzy comprehensive evaluation. Then, a comparison test is designed and independent sample t-test is applied to verify the practicality of the path in this paper. In the criterion layer of the established evaluation index system, the weight of industry-university-research integration is the largest, which is 23.91%, indicating that industry-university-research integration is particularly important in the path of vocational education quality improvement. In the indicator layer, the research team building has the largest weight, 10.17%, which needs to be emphasized in the implementation of the integration of science and education in vocational education. The overall rating of the quality of science and education integration in H higher vocational colleges implementing the path of this paper is 84.638, which is between good and very good, and is at a high level. And the two sided Sig value of the T-test of the evaluation score of the quality of science and education integration in the higher vocational colleges and universities using this paper’s pathway and those using the traditional education model is 0.000<0.05, which is a significant difference. It indicates the practicality of this paper's path for improving the quality of vocational education based on science and education integration. This paper provides a path paradigm for improving the quality of vocational education using science and education integration.

Ideological and political education has the teaching characteristics of keeping pace with the times. In this paper, the nonlinear support vector machine is used as the ideological and political text data classification algorithm, combined with the text mining technology to collect and screen the ideological and political education data, and the ideological and political text data is divided into various clustering centers of ideological and political education, which are reflected in the research themes of ideological and political education, the hot spots of curriculum ideological and political research, and the teaching methods of ideological and political teachers. This paper analyzes the acquisition of ideological and political education resources from the perspective of students, and explores the matching degree between the acquisition of ideological and political education resources and the individual needs of students. The research objects and research hotspots of ideological and political education are divided, and the optimization strategy of ideological and political education is proposed. In the classification of research topics, the frequency of “college students” was the highest, which was 12568, and the calorific value of the research content “ideological and political education” and the research object “college students” was 8654, indicating that ideological and political education mainly revolved around “college students”. The matching degree between ideological and political education resources and students’ individual needs was 69.37%. Combined with the results of nonlinear analysis, ideological and political education can improve the effectiveness of educational content, strengthen the coupling degree between research content and research object, and strengthen the teaching factor of teachers.

In the era of information technology in education, accurate analysis of individual characteristics becomes the key to personalized learning and tailored teaching, which is of positive significance to the exploration of teaching reform paths. This paper constructs a cognitive map of college English courses under the guidance of cognitive theory, and establishes a reform model of college English teaching in combination with the cognitive map, so as to realize students’ self-knowledge and cognitive construction in the teaching process. The idea of fuzzy set theory is used to quantitatively analyze the knowledge ability level of college students, and then the Logistic model and Bernoulli distribution function are used to calculate the students’ cognitive level of mastering each knowledge point and their scores of answering the questions in the college English course. The analysis of the effect of the teaching model after practice found that the students’ mastery and cognitive level of subjective and objective knowledge points in the college English course were significantly improved and higher than the ideal reference value. The correct rate of answering composition questions in subjective questions increased by 30.44% compared with that before the teaching mode was carried out. The informatization teaching mode proposed in this paper lays a foundation for the teaching reform of college English and provides an effective path for students to improve their knowledge mastery and cognitive level.

With the development of artificial intelligence technology, the learning mode of “artificial intelligence + education” has become the direction of the times. Through a questionnaire survey on students’ vocabulary learning strategies and taking students of a middle school as the research object, the study explores the level of strategy use in English vocabulary learning in terms of the frequency of strategy use and the differences in strategy use among students of different levels. On this basis, the way of English word sense processing with the assistance of artificial intelligence is summarized and the word association memory model is proposed. And two classes in a middle school are selected for teaching experiments to apply the word association memory model to English vocabulary learning and explore the effect of the model on students’ word memory. Overall the cognitive strategy (3.489) and resource strategy (3.477) of English vocabulary learning are used more frequently. The English vocabulary level model of the students in the experimental class increased after the teaching experiment, which was 8.05 points higher than that of the control class and still 5.118 points higher than that of the control class in the delayed test, reflecting the vocabulary learning effect and durability of the word association memory model. Students can improve their language cognitive learning skills in three aspects: metacognitive strategies, cognitive strategies, and communicative/influential strategies, which further promote the development of English proficiency.

With the rapid development of informatization technology, the security of network data is more and more emphasized. In this study, ECDSA digital signature algorithm and PBET consensus algorithm are adopted to construct a network data security model based on blockchain technology. The system in this paper consists of three functional modules: application interaction client, federation chain Fabric module and data storage module DHT, which are further logically divided into ϐive parts: initialization, identity registration, uploading data, querying data and permission revocation. The average CPU occupation of each component of the system ranges from 0.02% to 39.96%, which consumes low resources, and the maximum value of the time used by the system for data encryption and decryption and signature authentication is no more than 41ms, which is a relatively fast operation speed, and it can support the operation of the network data security system, and the designed system has relatively high security in resisting the attack of the authentication process, and it utilizes the decentralized characteristics of blockchain to resist the attacks of the distribution process, and it utilizes the blockchain to resist the attacks of the distribution process. Centrality to resist distributed denial of service (DDoS) attacks and replay attacks. This study provides lessons and references for the application of blockchain technology in network data security.

With the accelerating process of urbanization development, it is urgent to optimize the national land spatial planning to promote the coordinated development of urbanization. Based on the image recognition technology, this study uses the kernel density gradient algorithm to segment the image samples of the national spatial layout and the GWO-SVM classiϐication model to classify the land use types of the national spatial layout, and ϐinally combines the Markov-FLUS model to predict the future planning of the existing national spatial layout. The research analysis found that the segmentation and classiϐication accuracy of the kernel density gradient algorithm and the GWO-SVM classiϐication model for the homeland spatial layout samples both reached more than 90%. The classiϐication accuracy using the GWO-SVM classiϐication model is improved to a greater extent than that of SVM, GA-SVM, etc. The Markov-FLUS model also maintains an accuracy of more than 80% for the prediction of future territorial spatial planning. In terms of land use types, the Markov-FLUS model shows that the proportion of residential land and industrial land will decrease after 10 years compared with 5 years, while the proportion of public facilities land will increase by about 8% after 10 years compared with 5 years. The optimization of national spatial layout is of great signiϐicance to the development of urbanization in China, and the research in this paper will promote the development of national spatial layout planning in a more reasonable direction.

With the development of sharing economy, educational resource sharing has become the focus of experts and scholars to explore and practice. In this paper, from the perspective of resource sharing, a smart teaching management platform is successfully designed by combining artiϐicial intelligence technology. This research adopts YOLOv5s algorithm for face recognition and prediction in the design process, which is convenient for teaching management. Relying on the Hadoop cloud resource base, the teaching resource sharing database is designed, and the system computing logic is optimized by the distributed ϐile system HDFS. It is analyzed that the maximum number of interactions per second of the intelligent teaching management platform designed in this paper can reach 207, and the maximum interaction response time is about 68ms, and the load performance is completely better than that of the traditional teaching resource platform. At the same time, the intelligent teaching management platform can accommodate nearly 300 people to study online at the same time, which is far more than the previous mode of learning in the classroom. With the use of the intelligent platform, the development of “Internet + education” is greatly promoted.