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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 （1301）   HTML （69）    PDF （1016KB）（320）       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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A Conceptual Framework of Higher-order Thinking Shufeng Ma, Xiangdong Yang Journal of East China Normal University(Educational Sciences)    2022, 40 (11): 58-68.   DOI: 10.16382/j.cnki.1000-5560.2022.11.005 Abstract （937）   HTML （106）    PDF （755KB）（497）       Knowledge map    Higher-order thinking is a key competence for individuals to adapt to external environments and cope with future challenges. The theory of constructivism argues that people do not passively receive information from the environment, but actively construct knowledge to update their mental models. In authentic learning contexts, higher-order thinking manifests as the ability to identify the connection between prior knowledge and external information, transfer background knowledge to a new situation, and solve complex problems that do not have definite answers. Higher-order thinking is not a single thought process, but a complex cognitive process in which multiple mental operations coordinately work together. The conceptual framework of higher-order thinking incorporates the analysis of problem situations, the identification and formation of the relationship between old and new knowledge, the synthesis of information from different dimensions, the creation of new knowledge, and the monitoring, management and adjustment of the thinking process. The conceptual framework explains how the five cognitive components influence each other and synergistically regulate the process of cognitive development. The framework provides a new theoretical perspective for interpreting higher-order thinking, and lays a theoretical foundation for in-depth research on the developmental mechanism of higher-order thinking. 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 （796）   HTML （77）    PDF （728KB）（663）       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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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 （695）   HTML （128）    PDF （837KB）（852）       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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Digital Transformation in Education: What to Turn and How? Zhenguo Yuan Journal of East China Normal University(Educational Sciences)    2023, 41 (3): 1-11.   DOI: 10.16382/j.cnki.1000-5560.2023.03.001 Abstract （513）   HTML （60）    PDF （672KB）（402）       Knowledge map    The digitalization of education is not only an empowerment of education, but also a reform and reshaping of education. Due to the complexity and specificity of the digitalization of education, the digital transformation of education has not achieved the expected results in many other areas. There is some confusion and even misunderstanding in the perception of scholars, policy makers and the public. It is necessary to clarify the basic theoretical and practical issues of the current digital transformation of education. The fundamental difference between the digitalization of education and digitalization in other fields is that educational activities are not the connection between things and things, but the connection between people, and the digitalization of education not only cannot replace people, but also aims at human development, through people, by people, for people, and whether it promotes human development as the standard. At present, the key tasks of education digitalization are to innovate education scenarios, develop digital resources, improve teachers' digital literacy, improve the level of the national digital education platform, and govern the digitalization of education with digital thinking. Reference | Related Articles | Metrics

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Research on the Relationship between Exam-oriented Education and Students’ Creativity Zheng Ke, Can Liang Journal of East China Normal University(Educational Sciences)    2023, 41 (4): 72-82.   DOI: 10.16382/j.cnki.1000-5560.2023.04.006 Abstract （459）   HTML （50）    PDF （783KB）（219）       Knowledge map    Although many people rightly believe that exam-oriented education hinders the development of Chinese students’ creativity, there is no basic evidence to prove that the overall creativity level of Chinese students is lower than that of other countries. Therefore, it should not be simply asserted that exam-oriented education restricts the cultivation of Chinese students’ creativity. But this does not mean that exam-oriented education has nothing to do with students’ creativity. A reasonable explanation is that exam-oriented education has different effects on different types of students. It is effective in “raising the bottom”, but it will obviously hinder the creativity of top students. This is supported by many direct and indirect factual evidence. Although the number of highly creative students accounts for a small proportion, their creativity is affected, which is related to national security and competitiveness and deserves attention and vigilance. Exam-oriented education has a significant negative impact on the creativity level of top students, which does not mean that other groups of students are not affected by it. But in the environment of exam-oriented education, the top students are more affected and restricted. Using the analytical framework provided by the “the componential theory of creativity”, this negative impact can work through three mechanisms, that is, reducing the width and depth of top students’ knowledge mastery, reducing the spirit of adventure and questioning, as well as the tolerant attitude towards uncertainty, and weakening the internal motivation of learning. 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 （439）   HTML （41）    PDF （776KB）（264）       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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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 （427）   HTML （271）    PDF （1287KB）（549）       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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Educational Improvement Science: The Art of the Improving Organization Li Jun Journal of East China Normal University(Educational Sciences)    2022, 40 (12): 1-13.   DOI: 10.16382/j.cnki.1000-5560.2022.12.001 Abstract （424）   HTML （477）    PDF （1176KB）（310）       Knowledge map    Advocating educational improvement science as an emerging transdisciplinary area, I reflect philosophically on the three major pathways through which the education mission has been realized in human history and discern the misuses and pitfalls of reform. I also examine the terms “reform” and “improve” and their synonyms both etymologically and in East-West cultural and political traditions, which are embodied in educational theorizations and practical implications. Based on these reflections, I propose the concept of neo-improvementalism, define educational improvement science, and systemically elaborate on its philosophical assumptions, disciplinary fundamentals, and theoretical frameworks. I identify and elucidate growability, developability, and improvability as the three key properties of education and construct disciplinary knowledge of educational improvement science through two main categories, namely, subject matter knowledge and profound knowledge. I then highlight three foundational characteristics of educational improvement science – namely, discipline-oriented, systems thinking, and evidence-based – and the building of professional improvement communities promoting institutional improvement capabilities. I conclude that educational improvement science is the art of the improving organization for classes, schools, and more broadly defined educational agencies, and that its birth signifies the respect and recognition of the disciplinary status and specialization of educational improvement. Finally, I call for the recognition of the significance of educational improvement science and research thereon, especially with respect to discipline-building and exploration based on local characteristics in a global vision, and the cultivation of new fronters of educational research and practices, which need to be enhanced through disciplinarization and scientificization. Table and Figures | Reference | Related Articles | Metrics

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Artificial Intelligence Promotes the Development of Future Education: Essential Connotation and Proper Direction Xiaoqing Gu, Shijin Li Journal of East China Normal University(Educational Sciences)    2022, 40 (9): 1-9.   DOI: 10.16382/j.cnki.1000-5560.2022.09.001 Abstract （412）   HTML （302）    PDF （724KB）（408）       Knowledge map    The development of artificial intelligence technology brings both opportunities and challenges to the education system. Based on the major social science project “Research on Artificial Intelligence Promoting the Development of Future Education”, the study found out the key focus points of artificial intelligence to promote the development of future education: artificial intelligence highlights the challenges of innovative talent development; artificial intelligence supports the personalized realization of large-scale education; artificial intelligence reshapes the concept of knowledge and teaching innovation; artificial intelligence empowers future teacher development research; and artificial intelligence promotes the systematic update of the education ecosystem. At the same time, technology empowerment education, technology innovation education, and technology reshaping education are the advanced forms of the “trilogy” of artificial intelligence to promote the development of future education. To explore the core mechanism of artificial intelligence to promote future education development, it is necessary to reveal the interaction law of “technology-education-society” from the perspective of complex systems, explore the essential impact of artificial intelligence on educational development from the perspective of learning science, and predict the development trend of future education from the perspective of “history-culture”. On this basis, it's important to grasp the development strategy of innovative talents driven by the intelligent era, focus on the key elements of education innovation driven by artificial intelligence, reshape the blueprint of future education ecology boosted by artificial intelligence, so as to create a “high-quality and warm” artificial intelligence education new ecology in China. Table and Figures | Reference | Related Articles | Metrics

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Current Situation, Influence and Suggestions of China’s Elementary School Science Teacher: Based on a Large-Scale Survey in 31 Provinces Yonghe Zheng, Xuanyang Yang, Jingying Wang, Jia Li, Yangxu Lu, Shuhui Li, Yujing Yang, Xiaolin Zhang Journal of East China Normal University(Educational Sciences)    2023, 41 (4): 1-21.   DOI: 10.16382/j.cnki.1000-5560.2023.04.001 Abstract （412）   HTML （579）    PDF （2134KB）（297）       Knowledge map    To investigate the current situation of elementary school science teachers in China, large-scale research in 31 provinces was organized by the Professional Committee on Science Teaching of the Steering Committee for Basic Education of the Ministry of Education in the second half of 2021, and 131,134 valid questionnaires were collected. The current situation of the elementary school science teacher workforce involves three major aspects: faculty structure, professional literacy, and professional development. The study found that there is a serious structural imbalance in the structure of China’s elementary school science teachers, with part-time teachers and liberal arts backgrounds dominating; weak knowledge and beliefs, practical wisdom such as information technology application to be strengthened; weak professional development, lack of experimental resources and professional training. It is recommended to strengthen the teacher management of elementary science, improve the supervisory mechanism, and optimize the structure of the teaching force; strengthen the professional standards and development planning of integrated pre-service and in-service elementary science teachers; promote the reform of the content and form of elementary science assessment and pay attention to the monitoring and evaluation of the quality of elementary science teaching. 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 （386）   HTML （21）    PDF （1579KB）（114）       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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Difficulties and Solutions: Next Step in the Digital Transformation of Education Xiaozhe Yang, Ruoxin Wang Journal of East China Normal University(Educational Sciences)    2023, 41 (3): 82-90.   DOI: 10.16382/j.cnki.1000-5560.2023.03.009 Abstract （372）   HTML （34）    PDF （693KB）（204）       Knowledge map    The importance and value of digital transformation in education are getting more and more attention all over the world. Nowadays, China’s approach to the digital transformation of education is at an important and urgent stage, facing many difficulties, including blurred top-level design and lack of boundaries of responsibilities, inefficient digital resources and lack of stereo integration bases, overemphasizing data scale and technological innovation while ignoring the comprehensiveness of people development. This paper tries to point out paths for the next step of the transformation and think about how to break these dilemmas. The ways include reshaping the consensus and forming a diverse and consistent community; in-depth teaching and exploring five-application scenarios of digital education; and trying to promote people’s all-around development with people-oriented. Reference | Related Articles | Metrics

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Who is More Likely to Succeed: A Comparative Study of Competencies-based Education Reform in China, the United States and Finland Li Deng, Senyun Zhan Journal of East China Normal University(Educational Sciences)    2022, 40 (12): 38-49.   DOI: 10.16382/j.cnki.1000-5560.2022.12.004 Abstract （366）   HTML （59）    PDF （830KB）（233）       Knowledge map    The education reform based on key competencies is a global education policy, promoted by most countries in the world to improve the quality of talent training in respond to social changes and economic competition. The success of its implementation is related to the country’s labour quality and economic prosperity, as well as global competitiveness. In order to find the main influencing factors and the model that would most likely lead to success of the reform’s implementation, this study compares the key competencies-based education reforms of China, the United States, and Finland from the perspectives of political commitment and implementation capacities. It then points out that, in terms of education reform, China has strong political commitment but not strong implementation capacities; the United States has strong reform implementation capacities but not strong political commitment; Finland has both strong political commitment and implementation capacities, which is a more ideal reform model. China could learn from the experience of Finland and the United States from the aspects of evaluation methods, teacher education and training, and innovation in teaching and learning environments to enhance the implementation capacities, meanwhile keep up the political commitment, transform it into execution, bring non-governmental actors into the reform and further promote the successful implementation of the reform. Table and Figures | Reference | Related Articles | Metrics

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Reconstruction of Teachers’ Competencies: A Key Support for the Digital Transformation of Education Xiaohong Tian, Yilong Ji, Yueliang Zhou Journal of East China Normal University(Educational Sciences)    2023, 41 (3): 91-100.   DOI: 10.16382/j.cnki.1000-5560.2023.03.010 Abstract （362）   HTML （29）    PDF （1645KB）（196）       Knowledge map    The digital transformation of education is driven by the technical ecology formed by the integration of multiple technologies, and it is necessary to analyze the needs it brings to the teaching profession from a technical perspective. The technical intention of the digital transformation of education has shifted teachers from “teaching” to “learning”-centered, and smart education environment has shifted human-machine relationship from auxiliary to collaborative. The physical-social-cyber space survival mode penetrated by technology requires teachers to have corresponding moral cultivation capabilities, and the paradigm of knowledge growth in the digital age requires teachers to continue to develop themselves. Borrowing the functional capacity analysis construction path of organizational behavior elements analysis, the paper analyzes the core mission and attributes of educational organizations, and combines the needs of education digital transformation to obtain the specific types of capabilities supporting the digital transformation of education: curriculum development and teaching competency, human-computer collaboration competency, effective moral education competency and self-growth competency. From the perspective of supporting the digital transformation of education, curriculum development and teaching competency is the premise and guarantee of “learning”-centered, and human-computer collaboration competency is the transformation direction of teachers’ ICT capabilities in smart environments. Effective moral education competency is the primary role of teachers in the process of digital transformation, and self-growth competency is the purpose and means of digital survival. Teacher education needs to face up to the current problems in teacher capacity development and reshape teacher education around the core competencies required by digital transformation. Table and Figures | Reference | Related Articles | Metrics

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Situational Learning: Connotation, Value and Implementation Zeyuan Yu, Mingming Na Journal of East China Normal University(Educational Sciences)    2023, 41 (1): 89-97.   DOI: 10.16382/j.cnki.1000-5560.2023.01.008 Abstract （353）   HTML （39）    PDF （642KB）（263）       Knowledge map    Situation is the product of interaction. Interaction and mobility are the essential attributes of situation. Learning takes place in specific situations, which affect people and learning. People in learning create continuous situations. Situational learning refers to the process in which learners experience the growth of experience by fully interacting with the situation around the learning theme, which emphasizes the maximization of the use of information and factors in the situation. Situational learning can build complex situations for the cultivation of students’ literacy, facilitate students’ independent participation, promote the development of high-level complex mind and nourish the cultivation of literacy. The situational learning that points to the cultivation of literacy needs to be realized by relying on grand concept and swarm intelligence. Structuring the situation with grand concept and constructing swarm intelligence in interaction are the key to the implementation of situational learning. Reference | Related Articles | Metrics

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Research on Learning Affective Computing in Online Education: From the Perspective of Multi-source Data Fusion Xuesong Zhai, Jiaqi Xu, Yonggu Wang Journal of East China Normal University(Educational Sciences)    2022, 40 (9): 32-44.   DOI: 10.16382/j.cnki.1000-5560.2022.09.004 Abstract （351）   HTML （102）    PDF （2774KB）（535）       Knowledge map    Learning affection is an essential factor affecting learning performance, perception, and higher-order thinking ability. Existing research on learning affective computing is mainly based on a small sample analysis of heavyweight physiological feedback technology. There is a lack of learning affective computing research in online courses. In the online course environment, the data sources for learning affective computing are relatively limited, mainly based on a single facial expression data. On the other hand, learners are often under insufficient supervision in online learning scenarios. The body posture is more random, so it is very likely to affect the extraction of facial features. However, this study believes that the pose of online learners also has affective characteristics and is also a key source of affective information. Therefore, we try to fuse the learner’s posture data into the facial expression data, build a multi-source data fusion deep learning affective calculation model, and make up for the facial recognition defects caused by the learner’s posture change. Also, we perform collaborative analysis multi-source affective data to realize data cross verification and mutual compensation. The research concludes that it is an effective method for online learning affective calculation to build a dataset containing 7,878 facial expressions and posture images of online learners constructed through training, and use the convolutional neural networks and decision fusion methods to integrate learner posture data into facial expression data.The accuracy of affections recognition increases 3%, compared with a single facial expression recognition. In theory, this research provides a model basis for the effectiveness of multi-source data fusion in learners’ affective computing. In practice, it provides an effective technical path to learning affective computing in an online education environment. Table and Figures | Reference | Related Articles | Metrics

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Exploring The Cultivation Mode of Top-notch Innovative Talents in Undergraduate Education in The New Era:A Qualitative Study Based on TheTsien Excellence in Engineering Program’s 12 Years of Pilot in Tsinghua University Manli Li, Jinyu Wang, Quanshui Zheng, luping Xu Journal of East China Normal University(Educational Sciences)    2022, 40 (8): 31-43.   DOI: 10.16382/j.cnki.1000-5560.2022.08.004 Abstract （336）   HTML （52）    PDF （1708KB）（195）       Knowledge map    The direction of undergraduate education reform in research universities is one of the difficult problems in the reform and exploration of higher education in the past 20 years. This paper takes Tsien Excellence in Engineering Program (TEEP) in Tsinghua university, one of the pilot samples of China’s “Everest Plan”, as the research object, focusing on the pilot course and experience of undergraduate education in research universities in China. Based on a large number of static data such as official documents and meeting records across the past ten years of TEEP reform process, and dynamic data collected by researchers during the past two years including participatory observation, depth interview; etc, this paper comprehensively used the methods of archival research and case study. The study found that: compared with the traditional undergraduate education organization, TEEP has explored the “dual-axis driven” cultivation mode of “intensive course learning + advanced scientific research training” after more than a decade’s pilot practice. This paper reinterprets the core elements and operating mechanism of the “dual-axis driven” cultivation mode from its connotation and four dimensions: “systematic integration of knowledge and experience, logic of students’ time and space, interpersonal interaction between teachers and students, and self-construction of students”. The conclusion of this paper can provide theoretical framework and practical reference from different perspectives and value orientation for further promoting undergraduate education reform in research universities in the new era. Table and Figures | Reference | Related Articles | Metrics

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The Crisis of Educational Psychology: Its Challenge and Positioning Yun Dai David Journal of East China Normal University(Educational Sciences)    2022, 40 (11): 4-24.   DOI: 10.16382/j.cnki.1000-5560.2022.11.002 Abstract （331）   HTML （91）    PDF （915KB）（591）       Knowledge map    Educational psychology as a branch of psychology has a history of more than one hundred years. However, it is still very young as an independent discipline. Internally, it lacks central concerns of its own, a coherent conceptual system, and a distinct methodology. Externally, it faces new challenges brought up by the increasing division of disciplines. In the context of the 21st century, it is increasingly difficult to view educational psychology as a sub-discipline of psychology and ignore its nature as “design science” and “human science”. Repositioning educational psychology entails distinguishing itself from other psychological sciences by establishing distinct central concerns, especially by re-examining its epistemology and methodology. The traditional logic of mechanical reductionism has to be replaced by an organismic logic of emergence that is based on the plasticity, openness, choice, and growth of human beings. At the same time, educational psychology has to draw inspiration from “design science” in its exploration of possibilities and optimality of learning and growth, while psychological and behavioral evidence provides the viability and constraints for such practices. Table and Figures | Reference | Related Articles | Metrics

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The Core Technology Engine of Digital Transformation in Education: Trustworthy Education Artificial Intelligence Bo Jiang, Yingwen Ding, Yuang Wei Journal of East China Normal University(Educational Sciences)    2023, 41 (3): 52-61.   DOI: 10.16382/j.cnki.1000-5560.2023.03.006 Abstract （327）   HTML （30）    PDF （976KB）（220）       Knowledge map    The digital transformation of education aims to reengineer the education and teaching process and improve the quality and efficiency through digital technology. On the one hand, digital technology represented by artificial intelligence as the technical engine of digital transformation of education drives the continuous deepening of digital transformation of education. On the other hand, the “black box” problem of artificial intelligence technology has caused a crisis of human-machine trust, and there is a risk of violating basic constraints such as fairness, accountability, transparency, and ethics in education, hindering the digital transformation of education. This study sorts out the four major governance problems caused and aggravated by artificial intelligence to help the digital transformation of education, analyzes the theoretical research and development status of trustworthy artificial intelligence in education, puts forward the basic framework of trustworthy artificial intelligence in education, summarizes the opportunities brought by trustworthy artificial intelligence in education for the digital transformation of education, and puts forward the development suggestions of trustworthy education artificial intelligence to promote the digital transformation of education. The research recommends the introduction of relevant standards and regulations for trustworthy educational artificial intelligence, incorporating technical credibility into the evaluation system of education digitalization, further promoting educational data governance, and improving the digital literacy of education practitioners. Table and Figures | Reference | Related Articles | Metrics