Employment Of College Students Research Articles

Exploration and Analysis of the Improvement Path of College Students’ Employment Ability Under the Concept of Career Planning

In the face of the fierce environment of employment, the employment of college students is a hot topic in all walks of life. The concept of career planning plays an important role in promoting the employability of college students. The career planning course for college students is a course generally offered by colleges and universities, which can help college students to better determine their employment goal and direction, and lay a solid foundation for the improvement of the employment rate of Chinese college students. This paper analyzes the reasons for the difficult employment of college graduates, puts forward the application value of career planning education in the improvement of college students’employability, points out the reasons for the difficulties of college students’ employment, and makes targeted measures to improve the employability of college students under the concept of college students’career planning.

A study on the methods of cultivating the competitive advantages of college students' employment under the new employment forms

The article mainly discusses the relationship between education management and the employment of college students, as well as how to cultivate competitive advantages in employment under new employment forms. The article points out that education management plays an important role in the employment of college students, and can help students adapt to new forms of employment by providing relevant training and resources. At the same time, the article also emphasizes the importance of cultivating competitive advantages in employment, including improving professional skills, expanding employment channels, and enhancing innovation capabilities. In summary, education management should be committed to providing training and resources for college students to adapt to new forms of employment, and helping them cultivate competitive advantages in employment.

Understanding university graduate’s independent entrepreneurship by 3D designing cultural and creative products

In the context of the COVID-19 pandemic, the global economy is sluggish and the employment situation is grim. It is difficult for fresh graduates to find a job with a stable income. Therefore, college students' self-employment has become one of the main forms of college graduates. Among them, designing a meaningful cultural and creative product for sale is one of the ways for art graduates to achieve employment. However, college students' entrepreneurship must face fierce competition from existing cultural and creative products in the market, which often leads to a high failure rate of college students' entrepreneurship and a weaker ability to resist market risks. Based on the above problems, this paper is triggered to help college students quickly adapt to the business competition environment. The research methods of this subject mainly include the following two: (1) With the help of teachers, college graduates majoring in art and design can design cultural and creative products with practical, beautiful, and cultural characteristics, so that these novel cultural and creative products have price competitiveness and product design competitiveness in existing cultural and creative products. (2) Helping college students to visit enterprises broadening employment channels, and expanding sales forms through college leaders are also effective ways to improve students' self-employment. From these two aspects, the main research content of this paper is to promote the entrepreneurship and employment of college students in the context of COVID-19.

Confusion and Countermeasures of College Students’ Career Guidance Work Based on Deep Learning Models

Abstract In this paper, we identify teaching signals and employment factors by designing a college student employment guidance work model. The deep learning model is used to identify the given feature vectors, find the word sequence with the highest probability among them, generate the probability of the corresponding acoustic feature vectors, and model the college students’ employment guidance work model to model and calculate them. The teaching signal feature distribution is used to create the description, and the output probability is adjusted to it. The number of college graduates in 2020 will be 6.3 million, an increase of 190,000 compared to last year, and the initial employment rate is 91.07%. The deep learning model can effectively identify college students’ employment confusion, propose effective countermeasures and improve the employment rate.

An Analysis of the Impact of Industrial Robots on Employment of College Students

With the development of artificial intelligence technology and the promotion and application of industrial robots, it has had a profound impact on economic behavior and reform, as well as on the job market. As an important part of the labor market, the impact of AI and industrial robots on the employment situation of college students is also a topic worth studying. This paper investigates the impact that AI and industrial robots will have on the overall employment number as well as the employment number of college students through the data of the employment market in 30 Chinese provinces from 2015 to 2019 with the OLS and fixed effect model. The empirical research results prove that the development of AI technology and the promotion and application of industrial robots will have the impact of the promotion effect on the overall employment number as well as the employment number of college students.

Employment Analysis of College Graduates and Feasible Suggestions

In China, the population is constantly growing, and with it comes a large number of graduates pouring into society. However, the market cannot bear the influx of so many graduates, resulting in employment difficulties for many graduates. This research mainly analyzes the social phenomenon of difficult employment for college students. This article first analyzes the reasons for the employment difficulties of contemporary university students from three factors: individual college students, social enterprises, and the government. Afterwards, in responses to the problem of difficult employment for graduates, suggestions are proposed to students to have insight, plan for themselves, and adjust students mindset. Regarding social enterprises, more tolerance and friendly suggestions should be given to college students, and it is also hoped that the government will provide more encouragement to college students. Research has found some problems, including some college students having some psychological and ideological problems, enterprises exploiting college students, and the schools lack in regulating of students' emotions. This indicates that the issue of better employment for graduates not only requires individual actions from college students, but also requires active action from all sectors of society to jointly overcome this difficulty and help graduates find better employment.

Machine learning prediction model based on enhanced bat algorithm and support vector machine for slow employment prediction.

The employment of college students is an important issue that affects national development and social stability. In recent years, the increase in the number of graduates, the pressure of employment, and the epidemic have made the phenomenon of 'slow employment' increasingly prominent, becoming an urgent problem to be solved. Data mining and machine learning methods are used to analyze and predict the employment prospects for graduates and provide effective employment guidance and services for universities, governments, and graduates. It is a feasible solution to alleviate the problem of 'slow employment' of graduates. Therefore, this study proposed a feature selection prediction model (bGEBA-SVM) based on an improved bat algorithm and support vector machine by extracting 1694 college graduates from 2022 classes in Zhejiang Province. To improve the search efficiency and accuracy of the optimal feature subset, this paper proposed an enhanced bat algorithm based on the Gaussian distribution-based and elimination strategies for optimizing the feature set. The training data were input to the support vector machine for prediction. The proposed method is experimented by comparing it with peers, well-known machine learning models on the IEEE CEC2017 benchmark functions, public datasets, and graduate employment prediction dataset. The experimental results show that bGEBA-SVM can obtain higher prediction Accuracy, which can reach 93.86%. In addition, further education, student leader experience, family situation, career planning, and employment structure are more relevant characteristics that affect employment outcomes. In summary, bGEBA-SVM can be regarded as an employment prediction model with strong performance and high interpretability.

An improved TODIM-TOPSIS method for quality evaluation of college students employment and entrepreneurship education with probabilistic hesitant fuzzy sets

In recent years, employers have continuously raised their requirements for college students, not only requiring a solid professional foundation, but also emphasizing personal professional literacy. As the first base for cultivating college students, major universities should not only guide them in their correct employment and entrepreneurship, but also help them find employment and entrepreneurship faster and better. However, in the context of the new era, universities still face some problems in the process of carrying out employment and entrepreneurship education, which hinder the progress of employment and entrepreneurship education. The probabilistic hesitant fuzzy sets (PHFSs), as an extension of hesitant fuzzy sets (HFSs), can more effectively and accurately describe uncertain or inconsistent information during the quality evaluation of college student employment and entrepreneurship education. TODIM and TOPSIS methods are two commonly used multi-attribute decision-making (MADM) methods, each of which has its advantages and disadvantages. The quality evaluation of college student employment and entrepreneurship education is regarded as the defined multiple attribute group decision making (MAGDM). This paper proposes a novel method based on TODIM and TOPSIS to cope with multi-attribute group decision making (MAGDM) problems under PHFSs environment. After introducing the related theory of PHFSs and the traditional TODIM and TOPSIS methods, the novel method based on a combination of TODIM and TOPSIS methods is designed. And then, an illustrative example for quality evaluation of college student employment and entrepreneurship education proved the feasibility and validity of the proposed method. Finally, the result has been compared with some existing methods under the same example and the proposed method’s superiority has been proved.

Employment for College Graduates under COVID-19 in China: Vocational Education Should Take a More Important Role

The issues affecting college undergraduates in terms of job choice and employment are increasingly complicated and pressing in the COVID-19 age. Among these, elements relating to career planning have drawn increased focus. This paper mainly discusses the career planning education for college graduates under COVID-19 period in China, it offers focused solutions including enhancing systematization, upgrading faculty teams, psychological interventions, and improving course applicability based on questionnaires and literature reviews. Interpretation of the current situation of domestic career education based on research and comparison of domestic and foreign career education models are provided to improve domestic career education, and to enhance the current situation of college students employment problems.

Research on the impact of basic psychological needs satisfaction on career adaptability of Chinese college students.

With social changes, the realization of smooth and satisfactory employment of college students is an issue that requires deep thought. Basic psychological needs satisfaction play an important role as a guiding factor that affects students' career adaptability. This study aims to explore the relationship and mechanism between the satisfaction of students' basic psychological needs satisfaction and their career adaptability. A survey is conducted among students from six different universities across the country, using the Basic Psychological Needs Satisfaction Scale, the Career Adaptability Scale, the Career Decision Self-Efficacy Scale, and the Career Outcome Expectations Scale. The satisfaction of basic psychological needs, career decision self-efficacy, and career outcome expectations are all significantly positively correlated with career adaptability.Career decision self-efficacy plays a partial mediating role between basic psychological needs satisfaction and career adaptability among college students. The moderated mediation model found that career outcome expectations play a regulatory role in the effect of career decision self-efficacy on career adaptability. College students' basic psychological need satisfaction can positively predict career adaptability directly and indirectly affect career adaptability through career decision self-efficacy, and career outcome expectations have a moderating role between career decision self-efficacy and career adaptability.

Analysis of using big data to achieve precise employment of college students

Abstract In order to solve the social phenomenon of difficult employment of college students, this paper constructs a college employment recommendation platform based on an improved collaborative filtering algorithm. Firstly, the framework of the employment recommendation system is designed for the user use case, system architecture, system function module, database and user portrait of the platform, respectively. The functional modules are divided into six module parts: campus recruitment management, internship management, employment information management, employment affairs management, employment analysis management, and employment guidance management. Next, the platform is analyzed to combine the recommendation algorithm of collaborative filtering algorithm and clustering technology based on users and items to realize the recommendation of employment information for college students. Then the employment platform is used to get the high stickiness of users in the employment of college students, which can retain about 62% of the number of people, and even 5% of the number of people are particularly fond of the platform. With the increase in recommendation times, the recommendation accuracy increased from 22% to 83%, and the accuracy increased by about 61%, and the comparison with the traditional employment form is much higher than the traditional method in both accuracy and recall rate by about 30%. It is concluded that using the college employment recommendation platform can realize the precise employment of college students.

Design and Innovation of Green Recycling System for Express Packaging Based on New Development Concept

The implementation of green recycling of express packaging is an inevitable requirement of sustainable economic development. Green recycling of express packaging conforms to the trend of social development and helps to alleviate the current problems such as waste of express packaging and high environmental pressure. Based on the background of implementing the new development concept, this paper analyzes the development status, problems and reasons of express packaging recycling at home and abroad. The questionnaire is designed for the green recycling system of express packaging and its development, the questionnaire results are counted and analyzed by SPSS 20.0, and the logistics systems and system design architectures of express packaging are put forward, hoping to simplify the recycling process, improve the recycling rate, promote the recycling process of express packaging and reduce environmental pollution to improve the ability of sustainable development.

Big Data Analysis and Modeling Method of College Student Employment Management Based on Deep Learning Model

In order to study the big data of college students' employment, this paper takes the big data of college students' employment as the premise, analyzes the current employment data by establishing a DBN model, and puts forward relevant management measures, aiming to provide scientific basis for the management of graduates' employment data. The results are as follows: By comparing the application evaluation of linear regression method, BP neural network and DBN model, this paper finds that DBN model has better accuracy and lower error and has better advantages in the application of college students' employment data management characteristics. In addition, the development of social economy and the number of college graduates are the key factors for the employment rate of college students. Therefore, this paper suggests that through the use of big data technology, college will build a data platform for college students' employment management and provide a carrier for college students to obtain professional information and employment management information.

A novel approach to employment quality evaluation of college graduates with probabilistic linguistic MAGDM

With the continuous extension and deepening of college education reform, the research on the future employment of college students and the evaluation of employment quality has become a major focus topic. The traditional evaluation system for the employment quality of college graduates is relatively outdated and unitary, lacking a vision of the future development status of college graduates, as well as an effective understanding and mastery of the overall feedback and evaluation of the entire employment market for college graduates. Moreover, most colleges and universities mainly focus on the level of competence that college graduates should achieve five years after graduation from college in terms of talent cultivation goals, The lack of specific evaluation work for long-term employment tracking of graduates has resulted in universities being unable to grasp and understand the degree of fit and matching between the comprehensive abilities of university graduates and the future employment market, and thus unable to provide effective feedback and summary of talent cultivation and innovation strategies. Therefore, it is imperative to comprehensively innovate the employment quality evaluation system and methods for college graduates. The employment quality evaluation of college graduates is a classical multiple attribute group decision making (MAGDM) problems. Recently, the TODIM and VIKOR method has been used to cope with MAGDM issues. The probabilistic linguistic term sets (PLTSs) are used as a tool for characterizing uncertain information during the employment quality evaluation of college graduates. In this manuscript, the probabilistic linguistic TODIM-VIKOR (PL-TODIM-VIKOR) method is built to solve the MAGDM under PLTSs. In the end, a numerical case study for employment quality evaluation of college graduates is given to validate the proposed method.

Risk perception of coronavirus disease 2019 and career adaptability among college students: the mediating effect of hope and sense of mastery.

The Coronavirus Disease 2019 (COVID-19) pandemic has not only caused widespread economic recession but also had a serious negative impact on the employment of college students. However, little is known about the relationship and mechanisms between the risk perception of COVID-19 and career adaptability. This study aimed to examine whether the risk perception of COVID-19 is associated with career adaptability directly and indirectly through hope and a sense of mastery in college students. A questionnaire survey was conducted among 594 Chinese college students aged 16 to 25, who completed assessments on risk perception of COVID-19, career adaptability, hope, and sense of mastery. The results showed that susceptibility was negatively associated with career confidence, control, and curiosity; moreover, susceptibility indirectly affected career adaptability (including concern, confidence, control, and curiosity) through the sense of mastery; uncontrollable indirectly affected career concern through hope; and uncontrollable indirectly affected career adaptability (including concern, confidence, control, and curiosity) through hope and the sense of mastery. The findings emphasize the role of hope and a sense of mastery in the career adaptability of college students and reveal the necessity of improving hope and a sense of mastery to promote college students' career development. "Implications and limitations are discussed".

The generation mechanism underlying the career decision-making difficulties faced by undergraduates in China during the COVID-19 pandemic: a qualitative study based on SCCT theory.

As COVID-19 continues to spread worldwide, the record number of graduates in China and pressure resulting from the economic downturn have led to low confidence in employment among college students, and the difficulties associated with career decision-making have gradually developed into a psychological barrier to the successful employment of Chinese college students. Using the "purposive sampling" approach to qualitative research, this study selected 20 undergraduates exhibiting delayed employment from a university as our research sample and used the career self-management model of social cognitive career theory (SCCT) as an analytical framework to conduct semistructured interviews with the aim of exploring influencing factors associated with and generation mechanism underlying the career decision-making difficulties experienced by Chinese undergraduates during the COVID-19 pandemic. According to the career self-management model of SCCT theory, the four variables of individual, parents, peers and social environment influence Chinese undergraduates' career decision-making difficulties. On this basis, this study proposes a multivariable and single-subject generation mechanism to explain undergraduates' career decision-making difficulties and tries to explicate the mental changes associated with the career decision-making difficulties encountered by undergraduates exhibiting delayed employment by reference to mind sponge theory.

Research on the evaluation of the employment effect of Jiangsu artificial intelligence based on neural network on colleges and universities

Abstract Under the wave of digitization of big data information, the development of artificial intelligence technology continues to deepen the information technology revolution, which has a profound impact on human society and will also revolutionize the employment of different industries and groups. In this paper, we study the evaluation of employment effects of universities based on the neural network Jiangsu artificial intelligence. Since a neural network model needs to be built for training and there is a certain requirement for sample size, Jiangsu AI is selected for the study on the evaluation of employment effects in colleges and universities. The results show that the Dense Net model (C2) has better overall performance than the Vgg Net model, with weight and efficiency values of 89 and 88%, respectively, under the index of the educational level of college employment. Analyzing the impact of AI on college employment and unemployment in Jiangsu for the eight years from 2015 to 2022, it is concluded that with the development of time, the employment rate of college graduates reaches 87%, and the unemployment rate is 13% in 2022. This study has a guiding value for the employment of college graduates, and colleges and universities should focus on the future talent demand, guide students to cope with the possible impact of AI technology actively, cultivate students to acquire core competencies and literacy that AI does not easily replace, and promote high-quality employment of college students.

A Study on the Employment Analysis of University Graduates majoring in Interior Design in Guangxi Province

With the steady progress of urbanization, the demand for interior design talents in the market is also increasing. Therefore, the interior design major in universities has gradually become one of the popular majors. This paper takes the employment situation of college graduates majoring in interior design in Guangxi Province as the research object, and specifically analyzes the factors that affect the employment of college students. The paper also proposes corresponding strategies to provide theoretical basis for the improvement of employment quality and the development of professional education for college students.

The Impact of Intelligent Development on the Employment of College Students

The Impact of Intelligent Development on the Employment of College Students

An empirical study on employment behavior of college students in the post-epidemic era based on Herzberg's two -factor theory

The COVID-19 epidemic has had a profound impact on work in all walks of life. Many enterprises and units have changed their employment standards, which has greatly impacted the employment of college graduates. How to find a desirable job in the context of the new coronavirus epidemic is a major problem that college graduates must face. In order for the majority of students to better enter the society, combine the actual needs of college students in the post-epidemic era with the current stage of higher education, and cultivate practical talents that the post-epidemic society really needs, it is particularly important to investigate and study the values of employment of today's college students. Based on Herzberg's two-factor theory, entropy method and principal component analysis method, this paper conducts empirical analysis on the employment values of today's Chinese college students, and concludes that in the post-epidemic era, the emphasis on "health factors" is higher than that on "incentive factors" when choosing jobs.