Allocation Of Educational Resources Research Articles

Challenges and Teaching Reform Strategies in Vocational College Engineering Training Courses

With the rapid development of vocational education, engineering training has become a crucial course for cultivating highly skilled technical professionals, highlighting its importance. However, vocational college engineering training courses still face numerous challenges during the actual teaching process, which affect the effectiveness of course teaching and the enhancement of students’ engineering competence. This article thoroughly analyzes the main problems existing in current engineering training course teaching, focusing on four aspects: students’ cognitive differences, inadequate course development, poor course adaptability, and limited teaching resources. Based on this analysis and previous research findings, targeted strategies are proposed, including enhancing students’ course cognition, clarifying course positioning, improving course adaptability, and optimizing the allocation of teaching resources. Furthermore, this article preliminarily verifies the effectiveness of some reform strategies through a small-scale teaching experiment. This study aims to provide theoretical guidance and practical reference for enhancing the teaching quality of vocational college engineering training courses.

Research on the Balanced Development of Urban and Rural Compulsory Education Through Education Resource Allocation

With the rapid development of our country’s economy, education has gradually become the focus of social attention. The problem of unbalanced distribution of urban and rural educational resources has become increasingly prominent, urban educational resources are relatively rich, while rural educational resources are relatively scarce, and the balanced development of urban and rural compulsory education has become an urgent task. This paper mainly investigates and studies the distribution of urban and rural educational resources, discusses the unbalanced distribution of urban and rural educational resources and analyzes the reasons, and puts forward a series of corresponding solutions to promote the balanced development of urban and rural compulsory education.

A novel multi-scale fractional-order Bernoulli grey model and its application on primary school scale prediction

Primary education plays an important role in the whole educational structure. The prediction of the development scale of primary schools is of great significance to the optimal allocation of educational resources by education departments. The paper introduces a novel multi-scale fractional-order Bernoulli grey model by combining a local cumulative operator with a global cumulative operator, abbreviated as MFGM. First, a nonlinear grey Bernoulli model based on conformable fractional derivative is proposed, where a hybrid accumulation is presented. Then, the MFGM parameters are obtained by an PSO optimizer, which are adaptive to data sets. Finally, the proposed model is validated and used to predict the scale of primary school scale. Experimental results show that the MFGM is superior to the other grey models and machine learning models in the fitting and testing primary school scale. The prediction results contribute to the decision-making of education sectors.

Research on Efficiency of Allocation of Higher Education Resources in China--Empirical Analysis based on DEA-Malmquist Model

Research on Efficiency of Allocation of Higher Education Resources in China--Empirical Analysis based on DEA-Malmquist Model

Innovative Analysis of Student Management Path Based on Artificial Intelligence and Big Data Integration

This paper discusses the application path and effect evaluation method of big data and artificial intelligence in college student management, aiming at promoting the intelligent and humanized development of management through technological innovation. A BP neural network model (IFOA-IAGA-BP) based on the combination of improved firefly optimization algorithm (IFOA) and improved artificial pigeon colony algorithm (IAGA) is studied and constructed, aiming at improving the accuracy and efficiency of management quality evaluation. This model can identify students' individual needs more accurately, optimize the allocation of teaching resources, improve teaching quality, predict students' learning risks through intelligent algorithms, intervene in time, and provide all-weather learning consultation services, so as to enhance the immediacy and effectiveness of student support services.

Research on the Educational Needs of Long-term Hospitalized Children

This study discussed the parents' educational needs and expectations of a university-affiliated hospital in the neonatal and oncology departments in a semi-structured interview survey. Parents generally pay close attention to their children's learning environment in the hospital, the allocation of educational resources, and the organization and implementation of educational activities. At the same time, the parents also put forward clear requirements for the professional quality and attitude of the education volunteers, hoping that the volunteers will have solid professional knowledge, personalized teaching ability, and warm and caring emotional attitude. In addition, parents emphasized the importance of educational support in enriching children's lives, promoting physical and mental growth, focusing on mental health and behavioral management, and expected hospitals to provide more flexible and diverse ways of educational support.

The empowerment of AIGC technology in high school English education

The application of AIGC technology in high school English teaching creates a rich virtual language application environment and diverse learning platforms for students. These multimodal activities not only provide tailored learning paths but also, through in-depth data analysis and effectiveness evaluation, support the implementation of adaptive learning. While fostering independent thinking among students, they also assist in integrating English learning into their daily lives. This advancement not only optimizes the allocation of educational resources in underprivileged western regions, promoting an overall improvement in educational quality, but also confers profound significance on education.

Digital Twins Empower Higher Education

This paper explores the application of digital twin technology in higher education and its enabling effect. Through literature review and case studies, this paper studies the generation, basic concepts, technical frameworks, and application scenarios, e.g., in higher education, of digital twins. The results show that digital twin technology can significantly improve the teaching quality and learning effect and optimize educational resource allocation and management efficiency. This paper also discusses the challenges of digital twin technology and the prospects for future development in higher education. It provides new ideas and practical paths for the digital transformation of higher education.

Factors influencing research productivity among Syrian medical professionals amidst conflict: a case-control study

BackgroundMedical research productivity is globally increasing, with a lagging progress in third-world countries due to significant challenges, including inadequate training and brain drain. Syria had been showing a slow upward trend until the war broke out and severely hindered academic growth and productivity. A deeper understanding of the factors influencing research productivity in this context are fundamental to guide educational policies and resource allocation. Previous cross-sectional studies that evaluated the perspectives of Syrian academics on the issue were limited by the small sample size of published healthcare workers, making it difficult to identify the factors that enabled them to pursue research.MethodsTo address this challenge, we employed a case-control design. We isolated published early-career Syrian healthcare workers and compared their characteristics and perceptions to unpublished matched controls. Authors in the fields of medicine, dentistry, and pharmacy affiliated with any Syrian University were identified through an extensive search of PubMed and Google Scholar.These authors were invited to complete a questionnaire that covered participants’ research contributions, alongside their self-assessed knowledge, attitudes, and barriers towards research. The questionnaire was publicly published to recruit an equal sample of matching controls, with half consisting of unpublished researchers and the other half of participants without prior research contributions.ResultsSix-hundred-sixteen participants were recruited. Their knowledge, attitudes, and perceived barriers explained 46% and 34% of the variability in research involvement and publication, respectively (P < 0.001). Getting involved in and publishing research studies associated with higher research-related knowledge and attitudes (P < 0.001). Respondents’ assessment of research-related barriers and their academic scores did not differ between cases and controls. Superior research-related knowledge and attitudes were associated with male gender, higher English competency, and better internet connectivity. Meanwhile, extracurricular training and mentors’ support were associated with more positive research-related attitudes and less perceived barriers.ConclusionsResearch productivity of medical professionals in Syria exhibits a positive correlation with their knowledge and favorable attitudes towards medical research. Noteworthy, the demographic variations are linked to disparities in research-related knowledge and motivation. In conclusion, these results suggest a potential avenue for enhancement through concentrated efforts on improving extracurricular training interventions and mentors’ support.

The application of greedy algorithm in the course selection and scheduling system of college students

On December 19, 2023, the Chinese Ministry of Education's press conference once again emphasized the continued expansion of undergraduate professional degree enrollment. Nowadays, under the influence of the expanding enrollment scale of colleges and universities, the reasonable allocation of limited educational resources has become the primary task of educators, and college students' course choice and course arrangement will directly determine their school life quality. However, the number of students is large, so the research topic of this paper is to use greedy algorithms to design a more efficient course selection and scheduling system. The course selection and scheduling system based on the greedy algorithm can save the resources required by manual scheduling to the maximum extent and directly improve the work efficiency of educators. The system designed and practiced in this paper is effective to a certain extent, and the effective use of the algorithm can avoid many problems in course selection and course arrangement.

Causes and Recommendations for the Involution of Chinese Family Education

Addressing the phenomenon of involution currently observed in Chinese family education, this paper employs interviews and analyzes various dimensions including social background, traditional culture, educational systems, and family education concepts to elucidate the roots of involution in Chinese family education. Considering the adverse impacts of this involution on childrens physical and mental development, comprehensive growth, and family relationships, targeted recommendations are proposed. Through collaborative efforts among society, schools, and families to optimize the allocation of educational resources, transform educational concepts, and improve family education practices, this study aims to create a healthier, more harmonious, and conducive educational environment for the comprehensive development of children.

The Influence of Economic Development on Educational Equity

Amidst the continuous economic development, notable disparities in economic prosperity have emerged across different regions. These economic imbalances have led to significant disparities in educational investment and resource allocation. Education, as a crucial factor in shaping the quality of human resources, begs the question: does the variance in its level further exacerbate regional development gaps, or can economic growth pave the way for educational equity? This paper delves into the intricate interactions and relationships between educational fairness and economic development. Using statistical data from Gansu and Zhejiang provinces as examples, we gain a glimpse into the profound influence of economic development levels on the allocation of educational resources. Regions with more robust economies often boast more comprehensive and advanced educational resources, which are closely linked to factors such as fiscal budgets, social demands, and population structures. Furthermore, this paper explores the reverse effect of educational fairness on economic development. Not only does educational equity enhance the overall quality and productivity of human resources, but it also promotes social mobility and harmony, helping to alleviate societal injustices and class conflicts. The relationship between educational fairness and economic development is intricate yet interconnected.

Study on the Impact of Information Technology on Chinese Language Teaching

With the rapid development of information technology, its application in the field of education is becoming more and more widespread, especially in Chinese language teaching. The purpose of this paper is to explore the impact of information technology on Chinese language teaching and learning, and to analyse the current status of its application in terms of teaching mode, teaching resources, and teachers' roles, as well as the impact of these applications on teaching effectiveness and learners' development. The paper finds that the application of information technology can enhance teaching effectiveness, meet learners' individual needs, and promote educational equity and universality. However, it also faces challenges such as uneven development of technology, cyber security, and allocation of educational resources. Therefore, this paper proposes corresponding coping strategies, including strengthening teachers' IT training, optimising education management policies, and reforming the education evaluation system. The concluding section summarises the positive changes brought by information technology to Chinese language teaching and points out the important directions for future research and development.

The Impact of Rural–Urban Student Mobility on the Efficiency of Resource Allocation in China’s Rural Households: Optimization or Distortion?

The impact of rural-urban student mobility on the efficiency of resource allocation in China’s rural households is crucial for refining policies related to rural migrant settlement and the balanced allocation of urban and rural educational resources. Drawing on theoretical insights, this study employs a mixed methods approach—primarily qualitative, with quantitative support—to empirically test the impact of rural-urban student mobility on the resource allocation efficiency of rural households in China. Utilizing micro-survey data from China Family Panel Studies (CFPS), this study applies ordinary least squares (OLS) models, propensity score matching difference-in-differences (PSM-DID) models, and endogenous switching regression (ESR) models to ascertain the direction of this impact. Furthermore, this study incorporates in-depth interview data gathered from field research in D County to explore the dynamic mechanisms of resource allocation adjustments within these households. The results show that rural-urban student mobility significantly reduces the efficiency of labor resource allocation and agricultural production in China’s rural households. The impact is heterogeneous across different groups, most negatively affecting households with limited labor resources, lower educational levels, lower incomes, more productive fixed assets, and less self-owned land. Mobility leads to suboptimal occupational choices, resulting in decreased labor resource efficiency. Additionally, it distorts agricultural production by leading to labor loss, reduced investments in agricultural productivity, and misaligned land allocation decisions.

Long-Term Governance Mechanisms Against Large-Scale Re-Impoverishment of Previously Alleviated Groups: A Case Study of City C

Holding the bottom line of not returning to poverty on a large scale is the foundation and prerequisite for consolidating and expanding the results of poverty eradication in the stage of rural revitalization, and to realize the effective connection between precise poverty alleviation and rural revitalization. Taking C city of Guangxi border area as an example, the article understands the risk of returning to poverty and poverty-causing factors of the poverty-stricken households through field research, and the problems of constructing the governance mechanism, and puts forward corresponding countermeasures, including the development of regional featured industries, the optimization and allocation of educational resources, and the collaborative governance of multiple main bodies, in order to construct the mechanism of preventing the return to poverty of the long-lasting governance as well as the mechanism of helping the poverty-stricken households, so as to form the mode of rural revitalization with the characteristics of the border. Consolidate the results of poverty eradication through rural revitalization.

Optimization of Balanced Distribution of Online and Offline Biochemistry Teaching Resources Utilizing Machine Learning Algorithms and Big Data

Utilizing machine learning algorithms, the current conventional optimization methods for balanced allocation of teaching resources are enhanced. These methods primarily focus on predicting the current network resource load capacity without calculating the adaptation factor, often leading to suboptimal allocation outcomes. To address this issue, we propose a balanced allocation optimization approach for online and offline biochemistry education resources, taking into account the importance degree and big data. This approach calculates the probabilistic importance of teaching resources and the user delay in distinct modes to identify the optimal balanced allocation of teaching resources. Our experimental results comfirm that this approach achieves a higher resource utilization rate and a more desirable allocation effect compared to previous methods.

Research on the Development Status of Higher Vocational Education in China

With the rapid development of China's economy and the transformation and upgrading of industrial structure, higher vocational education plays an important role in cultivating high-quality skilled personnel. This paper analyses the current situation of the development of higher vocational education in China, discusses the challenges it faces, and puts forward corresponding countermeasures and suggestions. The study finds that the number and scale of schools in China's higher vocational education have been expanding, and the setting of disciplines and specialisations has been gradually diversified, but there are still certain problems in the construction of teaching staff and the guarantee of teaching quality. Meanwhile, the mismatch between higher vocational education and industrial demand, and the unbalanced distribution of educational resources are also challenges to the current development. In response to these problems, this paper puts forward countermeasures and suggestions such as diversified talent cultivation modes, balanced allocation of educational resources, strengthening industry-university-research-use cooperation, reinforcing the construction of faculty, as well as promoting the optimisation and updating of disciplines and specialties. These measures will help to improve the quality and level of China's higher vocational education and meet the demand for talents in social and economic development.

Effects of Entry Grades on Students' Academic Performance Under Homogeneous Educational Resources.

A minor difference in college entrance examination scores can result in vastly different educational resources in China, so it has been debated whether it is the difference in the student population or the difference in educational resources that causes the difference in medical graduates. We aimed to evaluate the effects of entry grades on students' academic performance under homogeneous educational resources. Students in grade 2016 with 13-point difference in the average admission scores of 2 medicine schools in Sun Yat-sen University were educated in mixed classes and were taught with the same educators during the 5 years of undergraduate period. The grades, graduation, and postgraduate enrollment rates of the students were compared between the two campuses. The average admission scores for Shenzhen Campus (SZC) students are 13 points lower than those of Guangzhou North Campus (GZNC) (613 points vs 626 points). After 5 years of homogeneous education, comparing the GZNC students with the SZC students, there were no significant differences in the average total score (80.2 ± 4.6 vs 80.0 ± 5.6, P = 0.691), the average compulsory course (78.9 ± 3.4 vs 78.4 ± 6.1, P = 0.438), the average core course score (78.8 ± 7.4 vs 78.7 ± 5.0, P=0.860) and the average clerkship score (85.1 ± 7.2 vs 84.6 ± 2.7, P=0.275). However, the completion rate for SZC was higher than for GZNC (93.94% vs 86.27%, P=0.009). There was no statistical difference in postgraduate enrolment between the two institutions (P=0.758). Given the same educational resources, more medical students with lower entrance scores completed their studies and achieved the same percentage of postgraduate acceptance. This finding suggests that a key component of improving the quality of medical higher education in China may be to further rationalize the allocation of high-quality educational resources, rather than to pursuing students with high entrance examination scores.

Research on Educational Inequality among Students in Poverty-stricken Areas in China

Education in reality and the constant pursuit of equality of education, are both sides of the same problem. This article makes research on educational inequality in rural education and urban education. To sort out and explain the reasons for the existing inequality in the field of education, this article involves reasons for inequality in education in rural regions and available ways to alleviate it. The inequality in education is not that some students can attend schools and some cannot, problems in deep are much more worth being concerned about. In the study, the author finds that students in disadvantaged are mainly in different sorts of inequality, like curriculum, teacher quality, and educational investments. It leads to improper and unequal allocation of education resources, and then students in rural regions cannot have access to education in quality and generate their living environment for the next generation. Solutions to alleviate existing problems are listed in the following parts of the research, namely offering incentive pay for teachers, applying local resources in the curriculum, and offering educational programs on vocational training and guidance for disadvantaged juniors.

Optimization of Resource Allocation of University Innovation and Entrepreneurship Education Based on Collaborative Filtering Algorithm

Entrepreneurship education resource allocation involves the strategic distribution of resources to support programs and initiatives aimed at fostering entrepreneurial skills and mindset among students. These resources can include funding, faculty support, curriculum development, mentorship opportunities, and access to networks and facilities. Effective resource allocation ensures that entrepreneurship education programs are adequately equipped to provide students with the knowledge, skills, and support needed to succeed as entrepreneurs. By prioritizing resource allocation to areas such as experiential learning, incubation spaces, and networking events, institutions can create a vibrant ecosystem that nurtures innovation and encourages entrepreneurial ventures. This paper presents an innovative approach to optimizing the resource allocation of university innovation and entrepreneurship education through the application of a collaborative filtering algorithm, enhanced by Flemingo Optimized Collaborative Filtering Classification (FOCFC). The study aims to address the challenge of efficiently allocating resources such as funding, mentorship, and infrastructure to support innovation and entrepreneurship initiatives within universities. Through simulated experiments and empirical validations, the effectiveness of the FOCFC-enhanced collaborative filtering algorithm is evaluated in recommending resource allocations tailored to the unique needs and preferences of students and entrepreneurial ventures. Results demonstrate significant improvements in accuracy and efficiency compared to traditional methods, with the FOCFC model achieving a precision rate of 95% in recommending resource allocations. Additionally, the model provides valuable insights into emerging trends and opportunities in the innovation and entrepreneurship ecosystem, enabling universities to adapt their resource allocation strategies proactively. These findings highlight the potential of collaborative filtering algorithms with FOCFC in optimizing resource allocation for university innovation and entrepreneurship education, fostering a supportive and conducive environment for entrepreneurial success.