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Research Report on Employment Trends of Chinese College Graduates: Based on 2003—2021 Survey Data Changjun Yue, Qinxue Feng, Xiaojia Xin, Wenqi Qiu Journal of East China Normal University(Educational Sciences)    2023, 41 (9): 138-154.   DOI: 10.16382/j.cnki.1000-5560.2023.09.010 Abstract （18002）   HTML （1309）    PDF（pc） （853KB）（7787）       Knowledge map    Save Based on ten national survey data sets on Chinese college graduates’ employment status from 2003 to 2021, this paper conducts empirical analysis on employment characteristics and trend of Chinese college graduates. The main conclusions are as follows. First, from the perspective of graduation destination, the proportion of formal employment has reached a new low level, while the proportion of further education continues to rise. The placement rate has declined, and the unemployment rate has rebounded. The placement rates of graduates with different educational levels tends to converge. Second, from the perspective of employment quality, the higher the graduates’ education level, the higher the starting salary and the faster the salary grows. There is a L-shaped downward trend in relative starting salary. Nearly 50% of graduates have lower starting salaries than expected. Employment satisfaction is on a fluctuating upward trend. Third, from the perspective of employment structure, the employment proportion in large and medium-sized cities exceeds 80%. The employment proportion of private enterprises has jumped to first place. The employment proportion of enterprises increases at the beginning and then decreases, which exceeds 50%. Career types shift from homogenization towards diversification, then back to homogenization. The education industry has become the preferred choice for graduates. Fourth, from the perspective of employment matching, the proportion of education-job match first decreases and then increases, exceeding 70%. The proportion of major-job mismatch is about 40%. Fifth, from the perspective of job-searching status, schools are the main source of job-searching information. The number of job applications has not gradually increased over time, and some graduates have obtained job opportunities but do not accept. Expenses on human relationship, transportation and clothing are the three major job-searching expenses. Ability is the most important factor that affects employment outcomes. Graduates have stable career intentions, attaching importance to prospects and income. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Exploring the Impact of ChatGPT/AIGC on Education and Strategies for Response Zongkai Yang, Jun Wang, Di Wu, Xu Chen Journal of East China Normal University(Educational Sciences)    2023, 41 (7): 26-35.   DOI: 10.16382/j.cnki.1000-5560.2023.07.003 Abstract （15841）   HTML （1267）    PDF（pc） （699KB）（59828）       Knowledge map    Save ChatGPT, as a representative of AIGC, has a significant impact on education. It empowers teaching by shifting the teaching model from “teacher-student” to “teacher-computer-student”, promoting the shift of teaching content from manual production to intelligent production, and catalyzing the assessment model of “knowledge + literacy”. ChatGPT also empowers learning by promoting the ubiquitization of learning space, meeting the personalized needs for full coverage of the learning process, and forming a human-computer collaborative learning mode. Additionally, ChatGPT empowers education by promoting higher-order ability cultivation and comprehensive literacy cultivation, and innovating the education model of discipline integration. To cope with the impact caused by ChatGPT, we must pay full attention, think calmly, and respond positively. This requires us to accelerate the development of high-level competing products with localized characteristics and to thoroughly study the laws of intelligent pedagogy with human-computer synergy. It also involves handling the important relationships between change and invariance, equity and efficiency in education, and the specialization and universality of technology. Besides, it's important to correctly grasp the direction and development of integration of AI technology and education, and lead the transformation of education system structure and operation mechanism. Reference | Related Articles | Metrics | Comments（0）

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ChatGPT/AIGC and Educational Innovation: Opportunities, Challenges, and the Future Yongxin Zhu, Fan Yang Journal of East China Normal University(Educational Sciences)    2023, 41 (7): 1-14.   DOI: 10.16382/j.cnki.1000-5560.2023.07.001 Abstract （10067）   HTML （852）    PDF（pc） （805KB）（24821）       Knowledge map    Save A text-based artificial intelligence application called ChatGPT has sparked attention from all walks of life upon its launch, and its demonstrated value of educational innovation has been hotly debated in particular. Thanks to its advanced algorithms, powerful computing capabilities and massive data base, ChatGPT can learn on its own when interacting with users, thus intelligently providing Q&A, translation, writing and other services. In addition, the newly-released upgraded version of ChatGPT—GPT-4 can also better solve real-time problems, reason logically and write creatively. In the field of education, ChatGPT can be used as a teaching tool, answer professional academic questions, build autonomous learning platforms, save human resources costs, and reconstruct school education structures, providing many development opportunities for educational innovation. However, it also brings some risks and challenges, impacting the role of teachers, the goals of talent cultivation, the traditional school order, and exposes typical issues such as technological dependence, academic misconduct, and intelligent discrimination. Currently, technological renovation is pressing educational innovation step by step, which requires us to approach new technologies positively and cautiously, achieving self-reliance and strength in intelligent technology by strengthening organized scientific research, building a national digital security barrier through revising relevant laws, enhancing application service transparency by clarifying digital education standards, and transforming talent cultivation concepts to form flexible thinking in education evaluation. Based on all this, we must make every effort to create a new form of human civilization in the process of moving towards human-machine co-teaching. Reference | Related Articles | Metrics | Comments（0）

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What is Artificial Intelligence (AI) Competency: Essence, Composition and Evaluation Systems Baichang Zhong, Xiaofan Liu, Minghuan Yang Journal of East China Normal University(Educational Sciences)    2024, 42 (1): 71-84.   DOI: 10.16382/j.cnki.1000-5560.2024.01.005 Abstract （8023）   HTML （404）    PDF（pc） （845KB）（13585）       Knowledge map    Save The ChatGPT has both positive and negative effects on education. The field of education should consider not only how to empower students to meet the challenges posed by AI, but also how to develop students’ competency to adapt to AI. In this paper, we refer to this competency as AI competency, i.e., the core competency of students with both domain specificity and domain generality cultivated through AI education. AI competency is a new competency arising from the development of AI technology. Technology ontology, philosophical epistemology and educational psychology are interconnected to understand the essence and composition of AI competency. From the perspective of technology ontology, this paper analyzes the essence of AI competency-the technicalization of human beings. From the perspective of philosophical epistemology and educational psychology, this paper analyzes the composition of AI competency. Key competency development is essentially a dynamic transformation process of “knowledge and thinking”. Affectivity, as a knowledge-derived emotional experience, not only nourishes the process of knowledge construction and thinking development, but also serves as the foundation and source for acquiring moral conceptions. Thus, the interplay of knowledge, affectivity and thinking underpins the logic of students’ AI competency. In this vein, this paper constructs an evaluation system of AI competency based on three dimensions: AI knowledge, AI affectivity, and AI thinking. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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The Transformation of Teachers’ Work in the Era of ChatGPT/AIGC: Opportunities, Challenges, and Responses Huan Song, Min Lin Journal of East China Normal University(Educational Sciences)    2023, 41 (7): 78-90.   DOI: 10.16382/j.cnki.1000-5560.2023.07.008 Abstract （6003）   HTML （242）    PDF（pc） （1388KB）（13408）       Knowledge map    Save As the latest breakthrough in artificial intelligence, ChatGPT has attracted widespread attention and discussion in the field of education since its release, requiring an analysis and exploration of its impact on teachers’ work from both theoretical and practical perspectives. Drawing upon the theoretical ideas of Biesta’s “weakness of education” and Dewey’s “philosophy of communicative action”, this paper deeply considers the essence of the integration between ChatGPT and education. According to different ways of thinking about “strong education” and “weak education”, teachers and schools have different degrees of replaceability. Teachers should pay attention to the value orientation of education, grasp the essence of education, seize the opportunities brought by ChatGPT in personalized learning, teacher workload, and teacher self-growth, and actively respond to the challenges brought by ChatGPT in learning objectives, teaching processes and design, and evaluation methods. Starting from the fundamental task of education and “competency-based suyang” education, and focusing on the digital information literacy of educators, this paper proposes new requirements for the structure of teachers’ competency in the new era: the ability to lide shuren (cultivate moral character and educate students), professional ethics in the digital age, the ability to integrate artificial intelligence into teaching, and the ability to update the curriculum, learning, teaching, and evaluation. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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The Influence of ChatGPT/AIGC on Education: New Frontiers of Great Power Games Nanping Yu, Yiran Zhang Journal of East China Normal University(Educational Sciences)    2023, 41 (7): 15-25.   DOI: 10.16382/j.cnki.1000-5560.2023.07.002 Abstract （4526）   HTML （419）    PDF（pc） （1057KB）（6248）       Knowledge map    Save The emergence and development of the new generation of artificial intelligence (AI), represented by the ChatGPT, marks the significant transformation from the weak AI to the strong AI, so as to bring great opportunities and challenges to the education system. The new generation of AI’s technological involvement in education elevates the relationship between teachers and students to a brand new third dimension. It presents the following characteristics: a)the network effects of the relationship between teachers and students, b) the dynamic creation of teaching activities, c) th implicit transmission of knowledge and information. From the perspective of application scenarios, the ChatGPT model will focus on three fields: “teachers”, “students”, and “disciplines”, and play an active role in team building, student training, , and discipline building. The application of ChatGPT to the education system not only cast game-changing influence on the current education norms, but also enlarges the gaps in regional developments, controls the industrial transformation process, reshapes the labor structure and complicates the national information security. Th above-mentioned influences not only go beyond the scope of self-definition of education, but also spread to every field of today’s society, and becomes new Frontiers of Great Power Games, directing the shaping of international power structure. In this process, education will be re-understood and redefined. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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The Impact of the “Double Reduction” Policy on the Participation and Expenditure of Students’ Families on Off-campus Tutoring Xiaodong Pang, Haiping Xue, Fengqiu Xiao Journal of East China Normal University(Educational Sciences)    2025, 43 (1): 17-36.   DOI: 10.16382/j.cnki.1000-5560.2025.01.002 Abstract （4485）   HTML （99）    PDF（pc） （1174KB）（2571）       Knowledge map    Save The “Double Reduction” policy proposes the goal of “reducing the burden of off-campus tutoring expenditures on the families of students in the compulsory education stage.” However, there is currently a lack of research to evaluate the degree of achievement of this policy goal. This study uses a large sample survey data of families of students in the compulsory education stage sampled nationwide, applying the difference-in-differences model (DID) to analyze the impact of the “Double Reduction” policy on the participation and expenditure of students’ families on off-campus tutoring. The study found that (1) the “Double Reduction” policy has significantly reduced the participation and expenditure of students’ families on “disciplinary” off-campus tutoring. The effect remain robust after applied PSM-DID model. (2) the “Double Reduction” policy has a significant reduction effect on student families’ participation in various “disciplinary” off-campus tutoring in “mid-semester, winter and summer vacations”, “online and offline”. The conclusion remain robust after applied PSM-DID model. (3) The “Double Reduction” policy has a significantly increasing effect on the participation and expenditure of students’ families in “non-disciplinary” off-campus tutoring, and the findings does not pass the PSM-DID robustness test. (4) Heterogeneity analysis found that the “double reduction” policy significantly reduced the participation and expenditure of “disciplinary” off-campus tutoring for families of students with middle and low socioeconomic backgrounds, but had no significant impact on families of students with high socioeconomic backgrounds. The research findings of this article provide evidence that the “Double Reduction” policy goal has been achieved. The government should strengthen the supervision of “disciplinary” off-campus tutoring, further strengthen the supervision of “non-disciplinary” off-campus tutoring, intensify efforts to manage the “invisible variation” problem of “non-disciplinary” off-campus tutoring. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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ChatGPT/AIGC and the Future Vocational Education Guoqing Xu, Jinfang Cai, Beijia Jiang, Zheng Li, Hui Yang, Jie Zheng Journal of East China Normal University(Educational Sciences)    2023, 41 (7): 64-77.   DOI: 10.16382/j.cnki.1000-5560.2023.07.007 Abstract （4457）   HTML （174）    PDF（pc） （668KB）（10946）       Knowledge map    Save Generative artificial intelligence such as ChatGPT has attracted strong attention since its inception. This paper reveals the future picture of vocational education under the influence of ChatGPT from four main aspects: vocation, vocational ability, personnel training in vocational education and scientific research in vocational colleges, which affect the development of vocational education and reflect the important functions of vocational education. Firstly, in terms of vocation, this paper puts forward corresponding coping strategies after clarifying the technical principles, mechanisms and paths of ChatGPT’s impact on vocation. Secondly, in terms of vocational ability, after combing the ability of ChatGPT, this paper analyzes the influence of ChatGPT on vocational ability from the explanation of the characteristics and structure of vocational ability, and suggests how to deal with the above influence. Thirdly, in terms of personnel training in vocational education, this paper first discusses the personnel training of vocational education school system, combs the application of artificial intelligence technology in the field of higher vocational education personnel training, and then analyzes the challenge of ChatGPT to higher vocational education personnel training and puts forward countermeasures. Then this paper discusses the personnel training of vocational skills training system, expounds the influence of iterative update of ChatGPT on future skills training and the influence of ChatGPT on the future skills training mode of vocational education. Finally, in terms of scientific research in vocational colleges, after clarifying the basic connotation of scientific research in vocational colleges, this paper depicts the iterative process of scientific research in vocational colleges in the change of skill formation, expounds the influence of ‘de-skill’ technology development represented by ChatGPT on scientific research in vocational colleges, and answers how scientific research in vocational colleges should deal with ‘de-skill’ technology development represented by ChatGPT. Reference | Related Articles | Metrics | Comments（0）

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ChatGPT/AIGC and the Value and Mission of Higher Education Yuan Xun Journal of East China Normal University(Educational Sciences)    2023, 41 (7): 56-63.   DOI: 10.16382/j.cnki.1000-5560.2023.07.006 Abstract （4126）   HTML （121）    PDF（pc） （640KB）（5824）       Knowledge map    Save Even though large multimodal models have broad application prospects at all stages of education, especially higher education, we should first focus on how to more effectively train students’ ability to cope with AI, or develop their wisdom to cooperate with AI in the process of applying this model. Today, with the rapid development of artificial intelligence, what artificial intelligence cannot achieve in education, especially in the field of higher education, is exactly the real value of human education, especially higher education, including the development of human unique rationality, collectivity and richness of human intelligence, adaptability of human culture, human moral and ethical choices, and human creativity. Higher education in the era of artificial intelligence must adhere to the intrinsic value of higher education, focus on the development of students’ morality, ethics, spirit and creativity, and provide necessary guidelines for rational application of artificial intelligence, so as to ensure that the young generation can continuously develop human collective intelligence under the premise of correct use of artificial intelligence, so as to create a future of common happiness for mankind. Reference | Related Articles | Metrics | Comments（0）

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First Report on the Development of Chinese Adolescents’ Social and Emotional Skills: Based on the Second Round of SSES Data Zhenguo Yuan, Zhongjing Huang, Hong Wang, Xiangyu Wang, Jing Zhang Journal of East China Normal University(Educational Sciences)    2024, 42 (5): 1-32.   DOI: 10.16382/j.cnki.1000-5560.2024.05.001 Abstract （4115）   HTML （127）    PDF（pc） （4355KB）（3334）       Knowledge map    Save This report analyzes data from the Survey on Social and Emotional Skills for the 10- and 15-year-old groups of students in Jinan City, China, and finds that students in the 10-year-old group scored higher than students in the 15-year-old group in all 16 social and emotional skills. In the 10-year-old group, boys scored higher than girls in all social and emotional skills except responsibility and achievement motivation, where the top three skills with the greatest differences were curiosity, creativity, and emotional control. In the 15-year-old group, girls scored higher than boys on responsibility, empathy, and tolerance, with empathy being the top one with the largest difference. Boys scored higher than girls in all other social and emotional skills, with the top three skills with the greatest differences being stress resistance, emotional control, and curiosity. The social and emotional skills of the advantaged students were higher than those of the disadvantaged group. There is no significant difference in social and emotional skills between general secondary school students and vocational secondary school students. In the 15-year-old group, private school students were slightly higher than public school students in engaging with the others and open-mindedness, while the results were reversed in other skills. Optimism was by far the skill most closely related to health behaviors, body image, life satisfaction, satisfaction with relationships, and current psychological well-being. Emotional control and stress resistance were most closely related to students’ test and class anxiety. Task performance, especially achievement motivation and perseverance, as well as curiosity were strongly associated with better student performance in Chinese, Math, and Arts. Notably, 15-year-old girls benefited more than boys from social and emotional skills, while 10-year-old boys benefited more than girls from social and emotional skills. The relationships between body image, health behaviors, satisfaction with relationships, current psychological well-being, and most of the skills were stronger for advantaged than that for disadvantaged students. Advantaged students tended to participate in more career development activities than disadvantaged students. Students with higher social and emotional skills, especially those with higher levels of creativity and curiosity, engaged in more career development activities. Girls and advantaged pupils tend to be more ambitious about their future education and careers than boys and disadvantaged pupils. Students with high levels of open-mindedness and task performance have higher future educational aspirations and career ambitions. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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AI-Driven Educational Reform: The Impact and Prospects of ChatGPT/GPT Li Jiang Journal of East China Normal University(Educational Sciences)    2023, 41 (7): 143-150.   DOI: 10.16382/j.cnki.1000-5560.2023.07.013 Abstract （4114）   HTML （235）    PDF（pc） （578KB）（7865）       Knowledge map    Save With the rapid development of artificial intelligence technologies and the emergence of AI such as ChatGPT and GPT-4, traditional education models are facing significant challenges. We have entered the era of artificial intelligence, and in this era, education should shift from focusing on cultivating individual abilities without AI assistance to nurturing comprehensive abilities with AI support. Using AI technologies such as ChatGPT correctly can provide students with learning resources and personalized learning paths. At the same time, AI can also offer many conveniences for teachers, transforming them into AI-enhanced “super teachers.” The education system should embrace technological changes to achieve truly interest-driven, self-driven, and inquiry-based learning. In the era of artificial intelligence, the focus of education should include teaching of AI thinking, creative and innovative capabilities, design thinking, communication skills, teamwork, problem-posing abilities, and learning abilities with the assistance of AI. Reference | Related Articles | Metrics | Comments（0）

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Learn to Question: Study on the Pattern of Undergraduates-GAI Collaborative Learning Shanyun He, Yan Shen Journal of East China Normal University(Educationa    2025, 43 (2): 34-48.   DOI: 10.16382/j.cnki.1000-5560.2025.02.004 Abstract （4096）   HTML （65）    PDF（pc） （1207KB）（5979）       Knowledge map    Save The advent of Generative Artificial Intelligence(GAI) represented by ChatGPT has challenged the traditional learning. How students learn through GAI tends to be an urgent problem to be explored in the current education and teaching reform. This research analyses the dialogues in class between undergraduate and GAI by coding discourse types, questioning levels, questioning strategies and students’ self report to explore the learning model of human-artificial intelligence collaboration. It is found that in student-GAI dialogues dominated by students, there are more single round conversations and less continuous discussions around a topic. The main types of students’ discourse are initial questioning, extended questioning and rephrasing questioning, while the evaluation and continuing instruction discourses are less. What’s more, students’cognitive level of questioning is low, focusing on knowledge level questioning and comprehension level questioning. The using of questioning strategies is unfamiliar and students seldom use role questioning, material questioning and scheme questioning. In addition, it is discovered that different task stages and different experience both lead to different conversation situation between students and GAI. With the development of task solving, there are more frequent and sustained dialogues, along with the deeper cognitive level and more proficient using of questioning strategies. Meanwhile, students with more experience in using GAI generate more dialogues with high cognitive level. In student-GAI dialogues representing different characteristics, though there are different opinions towards using GAI in class teaching, most of the students hold a positive attitude. In students’ perception, GAI has the advantage in generating responses, furnishing valuable information, handling various types of tasks and fostering the development of student abilities, thereby assisting students in learning. But at the same time, GAI faces challenges related to technical limitations, raising concerns about student development, learning assessment, and overall educational ecosystem. According to the findings of the research, our study provides effective suggestions for further introducing GAI into classroom teaching from three aspects: providing question guidance, enriching question scenes and strengthening reflection of GAI response. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Investigation into the Transformation of Knowledge-Centered Pedagogy with ChatGPT/Generative AI Jingyuan Chen, Liya Hu, Fei Wu Journal of East China Normal University(Educational Sciences)    2023, 41 (7): 177-186.   DOI: 10.16382/j.cnki.1000-5560.2023.07.016 Abstract （3827）   HTML （160）    PDF（pc） （2035KB）（3948）       Knowledge map    Save This paper explores the transformative role of ChatGPT in the teaching mode centered on knowledge concepts. As a language generation model, ChatGPT is capable of in-depth language comprehension and innovative combinations by mining the symbiotic relationships between words through massive language data learning. However, in the field of education, ChatGPT faces limitations such as over-reliance on training data, weak logical reasoning ability, and limited ability to handle new scenarios. To overcome these limitations and enhance the accuracy and relevance of ChatGPT’s generated content, this paper proposes an organic combination of ChatGPT with the organization of teaching resources centered on knowledge concepts, and improve ChatGPT by creating structure diagrams of knowledge concepts. Additionally, several specific and feasible ways to assist teachers and students using ChatGPT are also proposed. Finally, this paper discusses how to combine the prompt research paradigm with the teaching mode centered on knowledge concepts to help ChatGPT establish a “knowledge system”. This will enable ChatGPT to become a language generation model driven by both data and knowledge, providing more intelligent and personalized services in the education field, and promoting its development and transformation. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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ChatGPT/AIGC Reshape Education: Underlying Logic and Possible Paths Zhi Zhang Journal of East China Normal University(Educational Sciences)    2023, 41 (7): 131-142.   DOI: 10.16382/j.cnki.1000-5560.2023.07.012 Abstract （3777）   HTML （177）    PDF（pc） （1879KB）（20627）       Knowledge map    Save As a large model based on general artificial intelligence, ChatGPT can provide generative information acquisition services, and its functions far exceed any previous retrieval and search tools. Its appearance will also have a profound impact on education. This paper analyzes the influence of ChatGPT on education through literature research and other methods, analyzes and demonstrates its underlying logic of reshaping education from the perspective of brain science, knowledge view, and educational metacognition, and proposes its possible path to reshape education. The article believes that the impact of ChatGPT on education will mainly change education profoundly in the fields of the effectiveness of traditional educational tools, knowledge value theory, resource form, learning model, evaluation methods, and human-machine collaboration IQ. Its change in education conforms to the essence of brain science, echoes with the concept of knowledge, and also conforms to educational values. The birth of ChatGPT gave birth to a new form of education. In the future, it is necessary to accelerate the construction of human-computer collaborative IQ, educational evaluation systems, and computing-based teaching strategy models, and accelerate the revolutionary reshaping of human education. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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The Historical Background, Challenges and Choices for Building a Strong Education Power in a Century of Change Nanping Yu, Hao Huang Journal of East China Normal University(Educational Sciences)    2024, 42 (6): 9-19.   DOI: 10.16382/j.cnki.1000-5560.2024.06.002 Abstract （3721）   HTML （36）    PDF（pc） （755KB）（5365）       Knowledge map    Save The present time is in a situation of great change unprecedented in a century. From a macro perspective, the world is entering a period of political and economic reshaping. Education is crucial to raising the level of productivity and pushing human civilization out of the productivity stagnation period. The current process of reverse globalization has triggered the outbreak of deep-rooted global conflicts. At the same time, disruptive technologies and industrial changes are deconstructing and reshaping the global industrial chain and value chain while accelerating the reshaping of the new global political and economic landscape. Under the background of entangled and superimposed influences of political intervention and technological power, China will mainly face the influences and challenges of “graded decoupling” of education from the U.S. and the West, subversive technological barriers, and reshaping of the AI ecosystem in the process of constructing a strong educational power. Only with the inherent requirements of Chinese-style modernization and the goal of building a community of human destiny can China build and realize a strong education power in the revolution of education paradigm and education “self-creation”. Reference | Related Articles | Metrics | Comments（0）

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Expectation and Reality: An Analysis of Pay Level and Pay Mix of University Staff in China Yongmei Hu, Ping Zhao, Jing Yuan Journal of East China Normal University(Educational Sciences)    2024, 42 (1): 24-40.   DOI: 10.16382/j.cnki.1000-5560.2024.01.002 Abstract （3712）   HTML （89）    PDF（pc） （921KB）（6565）       Knowledge map    Save In order to find out the problems and then provide empirical basis for the reform of pay system of Chinese university staff, the current study analyzes the actual and expected pay level and pay mix of Chinese university staff by using administrative data and large-scale micro survey data, and draws the following conclusions. The pay level of Chinese university staffs is relatively competitive in China, but it is not internationally competitive enough. The annual pay and its components of most staff are lower than the average, and the pay expectation of the vast majority of staffs is higher than the actual pay. The proportion of the base pay of university staff in the monthly pay is low, and it is lower than their expectation. The proportion of faculties in the “Double First-Class” universities and staff in the eastern regions expecting salary increases is significantly higher than that of other staff. Based on the above research findings, the study proposes three suggestions on raising pay level and optimizing pay mix to facilitate the reform of pay system of Chinese university faculty. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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The Connotation and Influencing Factors of Employment Ability of College Students in China：Based on the Comparison Between Applied Universities and Research Universities Qiuheng Shi, Kexin Ren Journal of East China Normal University(Educational Sciences)    2023, 41 (8): 1-12.   DOI: 10.16382/j.cnki.1000-5560.2023.08.001 Abstract （3627）   HTML （136）    PDF（pc） （1194KB）（8042）       Knowledge map    Save The structural contradiction between employment difficulty and recruitment difficulty highlights the disharmony between the structure of higher education and the demand for talents of economic and social development. This paper explores the current situation and influencing factors of the employability of college students in research universities and applied universities by constructing a structural model of the employability of college students. It is found that the employability model of college students, which is composed of personality traits, general ability and professional knowledge and skills, is well supported by the data. The employability of Chinese college students is mainly based on comprehensive literacy and ability, and the applied talents have obvious advantages in vocational technical skills. The first classroom is the main front to improve the employability of college students, while the second classroom is of great value to college students with high employability. The quality of practical training in application-oriented colleges and universities needs to be improved. Therefore, colleges and universities should give full play to the different values of the first classroom and the second classroom to realize individualized teaching. Application-oriented colleges and universities should take engineering talents as the goal of talent training, improve students’ comprehensive quality in an all-round and multi-channel way, increase the construction of practice and training so as to realize the combination of characteristics and high quality. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Can Growth Mindset be Effectively Cultivated in adolescents? A three-year Intervention and Follow-up Study Based on a Rural School in China Junfeng Zhang, Ruxian Yun Journal of East China Normal University(Educationa    2025, 43 (4): 53-69.   DOI: 10.16382/j.cnki.1000-5560.2025.04.006 Abstract （3443）   HTML （51）    PDF（pc） （864KB）（4108）       Knowledge map    Save Cultivating growth mindset is an important strategy for the International Economic Cooperation and Development Organization to enhance the core competencies of adolescents. However, recent empirical studies have weakened or even reversed the positive driving force of growth mindset cultivation, and there is a lack of empirical evidence from East Asia. Addressing the debate of effectiveness of growth mindset intervention and its cross-cultural applicability, this study designed and implemented culturally adapted growth mindset intervention program to a randomized trial and three-year follow-up study at a rural primary school in the Yangtze River Delta region from 2021 to 2024, and used the Difference in Difference method to evaluate the intervention effect. The study found that the intervention program significantly improved the growth mindset level of rural students and had a long-term effect. The effect was more significant for younger students or those with lower initial mindset levels. Besides, the growth mindset enhancement brought about by the intervention effectively improved the students’ learning behavior, including suppressing negative learning motivation, weakening ability-based attribution, improving process-based peer feedback, and strengthening effort-based attribution. Accordingly, schools, families, and society should collaborate closely to jointly create a growth-oriented educational environment, strengthen growing educational principles, equip disadvantaged students with growth mindset as early and as sustained as possible, and bridge academic gaps while promoting educational equity through the development of psychological capital. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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The Impact of Family Socioeconomic Status on Students’ Social and Emotional Skills: The Serial Mediation Role of Growth Mindset and Test and Class Anxiety Zhi Liu, Jia Li, Chenxi Liang Journal of East China Normal University(Educational Sciences)    2024, 42 (5): 83-98.   DOI: 10.16382/j.cnki.1000-5560.2024.05.005 Abstract （3423）   HTML （79）    PDF（pc） （1097KB）（6293）       Knowledge map    Save Based on the data from the OECD Survey on Social and Emotional Skills conducted in Jinan in 2023, this study focuses on the impact of family socioeconomic status on students’ social and emotional skills. It explores the mediating mechanisms through which growth mindset and test and class anxiety influence this relationship. The findings indicate that: (1) both family socioeconomic status and growth mindset have a significant positive effect on students’ social and emotional skills, while test and class anxiety has a significant negative effect; (2) growth mindset plays a significant positive mediating role, meaning that family socioeconomic status positively promotes students’ social and emotional skills through the mediation of growth mindset; (3) test and class anxiety, as a mediator, shows a significant negative mediating effect, suggesting that family socioeconomic status can adversely affect students’ social and emotional skills through the mediation of test and class anxiety; (4) the study further reveals a significant positive serial mediation effect between growth mindset and test and class anxiety, indicating that family socioeconomic status affects students’ growth mindset, which in turn regulates their level of test and class anxiety, ultimately exerting a comprehensive impact on their social and emotional skills. Based on empirical discussions, this study proposes three suggestions for enhancing the development of student’s social and emotional skills. Firstly, schools should provide more resources and platforms to support students from lower socioeconomic backgrounds. Secondly, establish a path mechanism for cultivating growth mindset with schools as the main battlefield system. Thirdly, promote collaboration between home and school to address the issue of test and class anxiety among adolescents jointly. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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From Single-agent to Multi-agent: Motivational Learning Activities Design and Empirical Study Supported by LLM-based Agents Changqin Huang, Yihua Zhong, Xizhe Wang, Zhongmei Han, Tongquan Wei Journal of East China Normal University(Educationa    2025, 43 (5): 44-56.   DOI: 10.16382/j.cnki.1000-5560.2025.05.004 Abstract （3418）   HTML （48）    PDF（pc） （1458KB）（4841）       Knowledge map    Save The continuous advancements in large language models (LLMs) and agent technologies have made LLM-based agents a promising new tool for enhancing the quality and efficiency of teaching and learning in the educational domain. Based on the functional positioning of LLM-based agents, single-agent systems are capable of supporting various teaching and learning tasks, such as content generation, intelligent feedback, and assessment. However, due to the homogeneous nature of their interaction characteristics and functional attributes, single-agent systems face limitations in promoting deeper cognitive development. In contrast, multi-agent systems can simulate various educational roles, enhancing the diversity and depth of learning interactions and thereby providing more personalized and profound learning experiences. Considering that the application of agents in the learning process primarily relies on learners’ initiative, this study based on the ARCS model designed motivational learning activities for both single-agent and multi-agent systems to ensure the effective implementation of learning activities and conducted a quasi-experimental study in the context of English reading. The experimental results reveal that motivational learning activities supported by multi-agent systems significantly outperform single-agent systems in improving students’ performance in reasoning, evaluation, and application tasks. Furthermore, multi-agent systems exhibit stronger motivational effects and effectively promote deeper cognitive development, particularly in abstraction and generalization skills. The study underscores the value of multi-agent systems in supporting deeper learning and provides insights for further exploration of their applications in education. Table and Figures | Reference | Related Articles | Metrics | Comments（0）