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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 （6459）   HTML （812）    PDF （699KB）（5823）       Knowledge map    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

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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 （4155）   HTML （550）    PDF （805KB）（5665）       Knowledge map    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

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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 （6902）   HTML （750）    PDF （853KB）（3257）       Knowledge map    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

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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 （2114）   HTML （132）    PDF （1388KB）（3280）       Knowledge map    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

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Principles, Procedures and Programs of Latent Class Models Zhonglin Wen, Jinyan Xie, Huihui Wang Journal of East China Normal University(Educational Sciences)    2023, 41 (1): 1-15.   DOI: 10.16382/j.cnki.1000-5560.2023.01.001 Abstract （2979）   HTML （289）    PDF （837KB）（3658）       Knowledge map    The models used in Latent Class Analysis and Latent Profile Analysis are collectively referred to as latent class models, a kind of statistical methods of classifying individuals according to their different response patterns in observation indicators, so as to identify population heterogeneity. It has attracted increasing attention from applied researchers in the fields of pedagogy, psychology, and other social science disciplines. However, it is not easy for most education researchers to understand the existing Chinese literature on the statistical principles and analytical procedures of such models. This paper systematically introduces the basic knowledge, statistical principles, analytical procedures and Mplus programs of latent class models, and clarifies various methods and selection strategies involved in the subsequent analysis of these models. It would help applied researchers enhance their understanding of the principles and methods of the latent class models, and promote the application of these models to educational research. Table and Figures | Reference | Related Articles | Metrics

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Artificial Intelligence Curriculum Guidelines for Primary and Secondary Schools Jiang Bo Penner:, Dai Juan Core Members:, Zhou Aimin , Dong Xiaoyong , Liu Xiaoyu , Hong Daocheng Participants:, Jiang Fei , Zheng Longwei , Zhao Jiabao , Zhang Hengyuan , Liu Yalin , Yuan Zhenguo Consultant: Journal of East China Normal University(Educational Sciences)    2023, 41 (3): 121-134.   DOI: 10.16382/j.cnki.1000-5560.2023.03.013 Abstract （3307）   HTML （210）    PDF （728KB）（3362）       Knowledge map    Artificial intelligence (AI) education in primary and secondary schools has just started in China. Lack of unified curriculum standards, we still face many difficulties in the curriculum nature and objectives, textbooks development, and academic evaluation. To address this issue, East China Normal University and Shanghai Artificial Intelligence Laboratory jointly developed the Artificial Intelligence Curriculum Guidelines for Primary and Secondary Schools. The proposed guidelines has six parts including course nature and basic concept, core competency and curriculum objectives, course structure, course content and requirements, academic evaluation standards and implementation suggestions. We aim to construct a scientific and open curriculum guidelines for AI education in primary and secondary schools and simultaneously provide a reference for the construction of an AI education system in China. Table and Figures | Reference | Related Articles | Metrics

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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 （1817）   HTML （108）    PDF （668KB）（2497）       Knowledge map    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

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Determining Sample Size in Qualitative Research: Saturation, its Conceptualization, Operationalization and Relevant Debates Ailei Xie, Jiayi Chen Journal of East China Normal University(Educational Sciences)    2021, 39 (12): 15-27.   DOI: 10.16382/j.cnki.1000-5560.2021.12.002 Abstract （2703）   HTML （492）    PDF （899KB）（3552）       Knowledge map    Saturation has become an important criterion to judge the quality of qualitative research and explain the rationality of sample size. This paper systematically and critically reviews the literature and introduces three types of saturation: theoretical saturation, thematical saturation and data saturation and points out that researchers should consider their own overall research design to decide which model to adopt. The paper also introduces three ways to record the process of saturation. Among them, the structural coding book is more suitable for recording deductive thematical saturation and data saturation. There are two types of saturation tables which are more suitable for recording a prior thematical saturation. The conceptual depth scale is particularly suitable for recording theoretical saturation. This paper points out that saturation is a process rather than an event. Quality rather than quantity is the key to understand saturation. Saturation itself should be a concrete methodology practice. Researchers should pay attention to the concept of saturation and make a clear statement of the process of achieving saturation, which can help to improve the standardization, transparency, quality and recognition of qualitative research. Table and Figures | Reference | Related Articles | Metrics

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How Natural Language Processing Technology Empowers the AIED: The Perspective of AI Scientist Bo Zhang, Ruihai Dong Journal of East China Normal University(Educational Sciences)    2022, 40 (9): 19-31.   DOI: 10.16382/j.cnki.1000-5560.2022.09.003 Abstract （1248）   HTML （326）    PDF （1287KB）（2519）       Knowledge map    Natural language processing (NLP) is one of the most important research branches of artificial intelligence (AI). With the boosting of computer performance and the construction of large-scale corpora in the last decade, NLP technology has made great progress and has been widely applied in various areas, especially in the field of education. Specifically, in this paper, we investigate the present research and the trends of NLP technology, and how NLP promotes the development of artificial intelligence in education (AIED) through studying and analyzing publications, reports, and speeches, etc. from eminent domestic and international AI specialists. We are aiming to explore the direction and trend of AIED in the future. Table and Figures | Reference | Related Articles | Metrics

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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 （1576）   HTML （102）    PDF （845KB）（1533）       Knowledge map    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

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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 （1794）   HTML （338）    PDF （1057KB）（1887）       Knowledge map    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

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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 （1373）   HTML （95）    PDF （1879KB）（1930）       Knowledge map    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

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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 （1372）   HTML （97）    PDF （640KB）（1830）       Knowledge map    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

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A Maturity Model for Digital Transformation in Education Yonghe Wu, Qiuxuan Xu, Zhuzhu Wang Journal of East China Normal University(Educational Sciences)    2023, 41 (3): 25-35.   DOI: 10.16382/j.cnki.1000-5560.2023.03.003 Abstract （1508）   HTML （72）    PDF （854KB）（1926）       Knowledge map    The digital transformation in education is the driving force and innovation factor of the high-quality development of education. The evaluation of the ability level of the digital transformation in education has become one of the key points of the current education reform and practice. The maturity model provides a new method to solve the difficulty of evaluating the ability level of education digital transformation and helps to lead the implementation of the transformation practice. Based on the theory and basic structure of maturity model, this study analyzes the existing digital maturity model from the perspective of international comparison, and refines the key components of education digital transformation through policy analysis. By referring to the maturity levels and behavior characteristics of Capability Maturity Model and combining with the development characteristics of education digital trans- formation, an evaluation framework of education digital transformation maturity was constructed, which included five key process domains, 18 sub-key domains and five maturity levels. Based on the idea of “macro to medium to micro” to systematically promote digital transformation, this study discusses the key application scenarios of the ma-turity evaluation framework of education digital transformation from national, regional and school levels. A maturity model for digital transformation in education provides feasible evaluation paths for the implementation of education digital strategic actions and high-quality development of education. Table and Figures | Reference | Related Articles | Metrics

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Should Calculators Be Allowed to Use in College Entrance Examinations in Mathematics: An International Comparison of 30 Countries and Regions’ Calculator Use Policies and Practices in College Entrance Examinations Shuhui Li, Shang Li, Lianghuo Fan Journal of East China Normal University(Educational Sciences)    2023, 41 (4): 83-92.   DOI: 10.16382/j.cnki.1000-5560.2023.04.007 Abstract （1144）   HTML （33）    PDF （1579KB）（1596）       Knowledge map    Whether calculators should be introduced to College Entrance Examinations in Mathematics (CEE-M) in China is a long-standing controversial topic. This study examined calculator use policies and practices in CEE-M in 30 relatively economically developed countries and regions, and compared their delivery modes (single, mixed), types of calculators allowed and roles of calculators in exam questions and solutions; representative questions in selected sample exams were also used for case analysis. The study found that most CEE-M allowed students to use calculators, with mainly the single delivery mode using scientific calculators, and introducing calculators into the CEE-M can provide a new opportunity to enhance the real-life context, openness, and flexibility of questions in mathematics examinations. According to the results, the study concluded that there is a need to fully realize the value of introducing calculators in CEE-M, carry out more research in designing exam questions allowing calculators to promote examination reform and innovation, and establish a long-term plan for introducing calculators into mathematics classrooms and examinations. Table and Figures | Reference | Related Articles | Metrics

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ChatGPT in Education: A Diagnostic Study of Teaching Ability Liang He, Zhenyu Ying, Yingying Wang, Wenqi Sun Journal of East China Normal University(Educational Sciences)    2023, 41 (7): 162-176.   DOI: 10.16382/j.cnki.1000-5560.2023.07.015 Abstract （1192）   HTML （85）    PDF （964KB）（1823）       Knowledge map    The development of artificial intelligence technology is triggering profound changes in the field of education. As a new generation of natural language processing tools driven by artificial intelligence technology, ChatGPT has attracted widespread attention and use due to its powerful language understanding and text generation capabilities. However, due to the special nature of education, it is especially important to pay attention to whether it will have a negative impact on students while accepting it. In order to investigate the current teaching ability of ChatGPT, Shanghai Institute of AI Education, East China Normal University organized a diagnostic study of ChatGPT in teaching ability. Through 118 questions and 800 rounds of questioning, six teachers and nine students found that ChatGPT does not yet have the ability to tutor students independently, but it can be used as a good assistant for teachers to improve their daily work efficiency. Teachers should approach, learn, and use general AI tools as soon as possible, understand their potential risks, and teach students how to properly face and use general artificial intelligence tools. Table and Figures | Reference | Related Articles | Metrics

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The Difficulties and Corresponding Strategies of Educational Digital Transformation Junjie Shang, Xiuhan Li Journal of East China Normal University(Educational Sciences)    2023, 41 (3): 72-81.   DOI: 10.16382/j.cnki.1000-5560.2023.03.008 Abstract （2906）   HTML （132）    PDF （1016KB）（1926）       Knowledge map    The digital transformation in education is an inevitable result of the developing affordance of digital technology for education. This paper discusses the barriers, difficulties, and coping strategies in the educational digital transformation. It first describes three stages of future panoramic transformation of education: infrastructure upgrading, learning mode reforming, and educational process reengineering. The digital transformation of education, as a technology-involved innovative social revolution, is not bound to be a smooth journey. The interaction between technologies and education subjects is affected by multiple factors, thus leading to various corresponding difficulties and obstacles. The surface difficulties mainly come from the barriers of technological availability in building the new education infrastructure, referring to limited investments (e.g., human & financial) and technical bottlenecks. The deep difficulties mean educational subjects’ (e.g., teachers, students, & parents) action obstacles. The core difficulty is how to improve the consensus on digital educational innovation and how to deal with the relationship between humans and technology. To solve the core difficulty of educational digital transformation, it is necessary to carry out structural reform in education and strengthen the basic research of learning science to have a deep understanding of the process and mechanism of education with digital transformation. Finally, this paper puts forward several practical strategies to solve these difficulties from three levels: foundation-building strategies, empowering strategies, and exploring strategies. Table and Figures | Reference | Related Articles | Metrics

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The Essence of Education Digital Transformation: From Technology Integration to Human-machine Fusion Lianyu Cai, Mingfei Jin, Yueliang Zhou Journal of East China Normal University(Educational Sciences)    2023, 41 (3): 36-44.   DOI: 10.16382/j.cnki.1000-5560.2023.03.004 Abstract （1252）   HTML （53）    PDF （766KB）（1732）       Knowledge map    Exploring the qualitative prescriptive nature of education digital transformation is the cognitive basis for effectively promoting transformation practices. Information technology enhances the efficiency of information sharing, but objectively brings about the separation of technology from educational subjects (teachers, students, and administrators) and fails to achieve the convergence and fusion of machine intelligence and human intelligence. As a theoretical paradigm, “education technology integration” believes that the application of information technology in education is a process of improving the efficiency of industrialized “educational production” through the “integration of things and things” between technology and curriculum, innovating the presentation of teaching content, focusing on knowledge push, and facilitating students’ knowledge acquisition. The “technology integration” paradigm has limitations in the four dimensions of ontology, methodology, epistemology and axiology, and it is difficult to meet the value creation needs of education digital transformation. The essence of education digital transformation points to “human-machine fusion”. This new paradigm believes that the application of information technology in education is a process of “human-machine fusion” between educational subjects and machine, using human-machine collaboration to bring together machine intelligence and human intelligence to promote students’ mental growth, thus realizing “teaching students in accordance with their aptitudes on a large scale”. This paradigm follows the modern educational philosophy and is the theoretical basis for education digital transformation. Pushing education digital transformation needs to be based on the paradigm of “human-machine fusion”, and: (a) realize the digital-intelligence drive of the education system by the overall process of reengineering; (b) realize the human-machine fusion of education through new capacity building; (c) realize value system reconstruction by system optimization & innovating; (d) realize the educational function improvement of technology by organizing special researches and developments. Table and Figures | Reference | Related Articles | Metrics

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An Empirical Study on the Evaluation Model of Teacher’s Interdisciplinary Instruction Competency Dequan Zhu, Hongli Peng Journal of East China Normal University(Educational Sciences)    2023, 41 (2): 1-13.   DOI: 10.16382/j.cnki.1000-5560.2023.02.001 Abstract （1646）   HTML （74）    PDF （776KB）（1646）       Knowledge map    Interdisciplinary instruction competency is the fundamental driving force for teachers to carry out interdisciplinary teaching practice activities. Interdisciplinary instruction competency evaluation is an important tool and necessary means to guide and promote teachers to develop interdisciplinary instruction competency. By clarifying the connotation and characteristics of teachers’ interdisciplinary instruction competency, this paper constructs the interdisciplinary instruction competency evaluation index system of primary and secondary school teachers, and uses Delphi method and analytic hierarchy process to form a three-dimensional evaluation model of teacher interdisciplinary instruction competency with weight coefficient value, which integrates interdisciplinary teaching knowledge, interdisciplinary teaching ability and interdisciplinary teaching affection. Through empirical test, combined with the current level of interdisciplinary instruction competency of primary and secondary school teachers in China, this paper puts forward the development path of teachers’ endogenous interdisciplinary instruction competency, that is, to understand the interdisciplinary teaching concept and enhance the interdisciplinary teaching sentiment and liberal consciousness, to deepen interdisciplinary teaching practice and temper interdisciplinary teaching ability and cross-border thinking, and to strengthen the communication between subject teachers and develop interdisciplinary teaching community and organizational culture. Table and Figures | Reference | Related Articles | Metrics

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Music, Mind and the Brain Zhang Weidong Journal of East China Normal University(Educationa    2014, 32 (1): 89-96.   Abstract （1134）   HTML （1218）    PDF （492KB）（4894）       Knowledge map    Music plays an important role both in one’s life and in a society and therefore attracts psychologists and neuroscientists to explore intensively and extensively the psychological mechanisms and neural basis of human musical mind. This paper reviewed the major research advances and results in the areas of cognitive processing and emotional experience of music, the individual differences in responding to and enjoying music, and the implications of psychological and neuro-scientific research on music. The concluding remarks addressed the key issues in current studies as well as directions for future research in the area of music, mind and brain. Reference | Related Articles | Metrics