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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
    Abstract695)   HTML128)    PDF (837KB)(852)      

    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.

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    Adapting, Remixing and Emerging: The Function and Essence of the Second Bachelor’s Degree Education in the New Era
    Xiaodong Lu
    Journal of East China Normal University(Educational Sciences)    2022, 40 (10): 1-16.   DOI: 10.16382/j.cnki.1000-5560.2022.10.001
    Abstract167)   HTML42)    PDF (872KB)(804)      

    In the higher education structural system, in the “world”, and in the dual time vision of personal and public time, the second bachelor’s degree education is indispensable. The three key words of its function and essence are adapting, remixing and emerging. The important function of the second bachelor’s degree education in the new era is to quickly respond to the demand for talents and human resources from the changes in the market and industrial structure, and to provide learning opportunities for individual/Dasein with emerging learning motivations to enhance their adaptability; to supplement students enrollment to “unpopular” majors; cultivating top-notch creative talents based on remixing to increase the probability of “emerging” and enhance the country’s momentum for innovation and development. At the same time, the second bachelor’s degree education also provides a repair for the current teaching reforms that are still lagging behind in some colleges and universities. The classifications of remixing provide framework guidelines for the curriculum construction, enrollment qualifications and teaching of the second bachelor’s degree major. In the dual time vision of personal time and public time, the individual/Dasein recognizes himself, locates himself, projects himself with understanding of the world and the earth, and new learning motivation emerges unpredictably and unplannedly in the field within the worldliness and worlding of the world. The second bachelor’s degree education and other learning opportunities together promote the emerging and sheltering of diversity, richness and innovation.

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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
    Abstract796)   HTML77)    PDF (728KB)(663)      

    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.

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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
    Abstract331)   HTML91)    PDF (915KB)(591)      

    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.

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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
    Abstract427)   HTML271)    PDF (1287KB)(549)      

    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.

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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
    Abstract351)   HTML102)    PDF (2774KB)(535)      

    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.

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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
    Abstract937)   HTML106)    PDF (755KB)(497)      

    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.

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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
    Abstract412)   HTML302)    PDF (724KB)(408)      

    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.

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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
    Abstract514)   HTML60)    PDF (672KB)(402)      

    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.

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    IQ or EQ: Which is More Important for Students’ Learning ?
    Jing Zhang
    Journal of East China Normal University(Educational Sciences)    2022, 40 (11): 69-79.   DOI: 10.16382/j.cnki.1000-5560.2022.11.006
    Abstract266)   HTML59)    PDF (1243KB)(398)      

    This study of a sample of 860 Chinese secondary school students used Raven reasoning test and Big Five personality scale to investigate the longitudinal relationship between intelligence, personality and students’ academic performance in three subjects (Chinese, Math, and English). This is a three-wave longitudinal study covering one school year. The cross-lagged panel model analyses indicated that: (1) students’ previous intelligence level can significantly and positively predicted their academic performance in all three subjects. That is, students with high intelligence level tended to achieve higher academic performance in three subjects; (2) students’ personality traits, especially openness, also significantly and positively predicted their academic performance in all three subjects; (3) in the long-term run, there is a compensatory interaction between students’ intelligence and openness in the prediction of academic performance. In this regard, both intelligence and personality traits are very important for students’ learning. Educators should not only pay attention to the development of students’ potential and intelligence, but also to the cultivation of students’ personality traits.

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    What Can Bayesian Network Contribute to Educational Research?
    Xin Gu, Mengqi Mao, Shufeng Ma, Senyu Chen
    Journal of East China Normal University(Educational Sciences)    2022, 40 (11): 110-122.   DOI: 10.16382/j.cnki.1000-5560.2022.11.009
    Abstract191)   HTML38)    PDF (1550KB)(357)      

    This paper proposes to use the Bayesian network method to analyze educational research data in view of the complexity, uncertainty and dynamic characteristics of current educational research problems. In terms of research paradigm, Bayesian network integrates theoretical and data-driven research procedures, determines a prior model based on educational research theories and expert experience, and updates data evidence that can support or oppose the theoretical model by collecting new data. In terms of data analysis, Bayesian network brings the uncertainty of variables or variables’ relations into the model and gives accurate inference and prediction by means of probability. In terms of application, Bayesian network can evaluate students’ knowledge mastery, ability training and competence development in real teaching and learning situations. This offers methods and technical support for dynamic evaluation of teaching and learning process.

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    Psychological Views on Cultivating Students’ Creativity: Goals, Principles, and Strategies
    Weiguo Pang
    Journal of East China Normal University(Educational Sciences)    2022, 40 (11): 25-40.   DOI: 10.16382/j.cnki.1000-5560.2022.11.003
    Abstract249)   HTML41)    PDF (738KB)(339)      

    Creativity is a multifaceted concept which involves creative potentials, creative achievements, creative talents, and many other facets. Basically, creativity can be divided into four types, namely mini-creativity, little creativity, professional creativity, and big creativity. In school context, creativity cultivation should focus on students’ creative potentials, highlight the roles of creative cognition, metacognition, personality, motivation, and domain-specific knowledge. As creativity usually develops from general domains to specific domains, and autonomy and idea generation are the key components of creative processes, school education which aims to cultivate each student’s creativity in everyday classroom activities should encourage students’ autonomy, employ generative tasks, and stimulate creative thinking in specific contexts. To effectively develop students’ creativity, a series of strategies should be employed, which include creating supportive climates, using generative activities, modeling and rewarding creativity, training creative metacognition, setting creativity as separate goals, and providing feedback on creative performance.

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    The Game and Integration between AI and Human in Knowledge Production and its Enlightenment to Education
    Xiangjun Hao, Xue He
    Journal of East China Normal University(Educational Sciences)    2022, 40 (9): 78-89.   DOI: 10.16382/j.cnki.1000-5560.2022.09.008
    Abstract226)   HTML80)    PDF (774KB)(335)      

    Since making stone tools, humans have been committed to using tools to liberate themselves. As an artificial technology tool, artificial intelligence has entered many fields of society and participated in human knowledge production activities. It is gradually sharing the physical and even mental labor of human and showing strong characteristics of autonomy. Therefore, humans and artificial intelligence are bound to engage in a “game” to maintain their own subjectivity. This paper analyzes the current situation of artificial intelligence participating in knowledge production activities from three aspects: the change of the subject of knowledge production, the change of the methods of knowledge production and the change of the form of knowledge presentation, and analyzes the characteristics and differences between artificial intelligence and human intelligence based on this. It is believed that the game between artificial intelligence and human intelligence will move towards the “handshake and reconciliation” between human and machine under the trend of high division of labor, turning “zero-sum” into “win-win”, and reaching a new stage of development through external man-machine cooperation and internal man-machine intelligence integration. Finally, artificial intelligence reconstructs the knowledge production process, which changes the society’s demand for talents, and also causes the thinking on education. The study summarizes three points of inspiration to discuss the focus of future education.

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    Does the Digital Tools-supported Teaching Have an Impact on Students’ Learning Results:Meta-Analysis Evidence from 137 Experiments and Quasi Experiments
    Hao Lei, Xue Li
    Journal of East China Normal University(Educational Sciences)    2022, 40 (11): 92-109.   DOI: 10.16382/j.cnki.1000-5560.2022.11.008
    Abstract218)   HTML51)    PDF (978KB)(330)      

    In order to clarify the impact of digital tools-supported teaching on students’ learning outcomes, this study conducted a meta-analysis based on 137 experiments and quasi-experiments. The results show that compared with traditional teaching, digital tools-supported teaching can enhance learning motivation (g=0.482) and improve academic achievement (g=0.479). In addition, this positive effect was moderated by demographics, knowledge assessments, and study attributes.The specific manifestations were as follows: in terms of demographic, the use of digital tools to support teaching in the context of collectivism culture had a more significant positive impact on learning motivation and academic achievement compared with individualism culture; the predictive effect of digital tools-supported teaching on learning motivation and academic achievement is not affected by the stage; the influence of digital tools-supported teaching on boys’ academic achievement is significantly higher than that of girls. In terms of knowledge assessment, compared with digital tutorials and simulation, intelligent tutoring system and hypermedia are more conducive to improving academic achievement; as opposed to other subjects, the teaching supported by digital tools has a greater impact on language learning motivation, but the teaching supported by digital tools has a significant impact on mathematics and science achievement. In terms of study attributes, the use of digital tools by trained teachers had a better impact on student motivation than did untrained teachers; only when the intervention time of digital teaching is moderate can it give full play to its best effect on academic achievement; the impact of digital tools-supported teaching on academic achievement is strengthened as the intensity of intervention increases; with the change of years, the predictive effect of digital tools- supported teaching on learning motivation will become more and more prominent.

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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
    Abstract1302)   HTML69)    PDF (1016KB)(320)      

    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.

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    The Profiles of Parental Control and its Influence on Adolescents’ Adaptation: Based on Latent Transition Analysis
    Yan He, Keman Yuan, Mingming Zhang, Yufang Bian
    Journal of East China Normal University(Educational Sciences)    2023, 41 (1): 25-39.   DOI: 10.16382/j.cnki.1000-5560.2023.01.003
    Abstract238)   HTML44)    PDF (1019KB)(314)      

    Parental control refers to a relatively stable behavior pattern used by parents to control and manage their children in the process of parenting activities, which has an important and direct influence on the psychological development and social adaptation of children and adolescents. This study explored the profiles of parental control, transformational characteristics and its impact on adaptation among Chinese adolescents based on a longitudinal study and a person-centered approach. The main findings are as follows. First, the parental control of Chinese parents is heterogeneous with three profiles: low-medium control (i.e., low psychological control-medium behavior control, and so on), medium-medium control and high-high control. The proportion of parents in the medium-medium control group was the highest at the two time points, which were about 60 percent and 50 percent respectively. Second, the profiles of parental control change as time passes. From the first grade to the second grade of junior middle school, there were about 70 percent of parental control profiles remaining stable and around 30 percent mainly changing to adjacent profiles. If the profile of medium-medium control is not maintained in the first grade, it will be more likely to become high-high control. Third, the profiles of parental control have significant effects on adolescents’ adaptation (including subjective well-being, Internet addiction and parent-child conflict). Above all, this study lays a foundation for empirical research on the precise intervention of different profiles of parental control.

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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
    Abstract424)   HTML477)    PDF (1176KB)(310)      

    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.

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    Competence and Its Model Building: A Theoretical Analysis
    Xiangdong Yang
    Journal of East China Normal University(Educational Sciences)    2022, 40 (11): 41-57.   DOI: 10.16382/j.cnki.1000-5560.2022.11.004
    Abstract198)   HTML44)    PDF (965KB)(307)      

    Competence can be broadly defined as the capacity of a human being interacting with environment, with the aim to maintain and enhance the survival and development of humankind at both individual and population level. Inherently implied in the concept of competence are such characteristics as agency-driven, socially-constructed and culturally-laden. Therefore, a theory of competence should explicate from an ecological perspective the nature of various competences as well as their epigenetic and developmental mechanism within the dynamically bilateral relationship of co-existence and co-ordination between an individual and environment. Competence development is an organic process, a process of continuous becoming and constructing throughout the life-span of an individual, during which various elements and their relationships are involved and integrated across a variety of layers including those of physical-biological, social-cultural as well as psychological-behavioral. In particular, collective practice, individual agency and social transaction constitute a three-dimensional dialectic system for human competence development, within which the culture plays a mediated role in that it can be considered as tools in the most general sense. Under this theoretical perspective, three approaches to competence model building can be described as demand-functional approach, culture-psychological configuration approach and hologram-layer approach, respectively. These approaches are complementary with each other and provide a more comprehensive and systematic understanding of the nature, structure and development of human competences.

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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
    Abstract412)   HTML579)    PDF (2134KB)(297)      

    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.

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    Developmental Trajectory of High School Students’ Academic Motivation and Its Relation with Academic Achievement
    Yi Jiang
    Journal of East China Normal University(Educational Sciences)    2022, 40 (11): 80-91.   DOI: 10.16382/j.cnki.1000-5560.2022.11.007
    Abstract208)   HTML44)    PDF (910KB)(293)      

    As a bridge between compulsory education and higher education, high school education plays a vital role in Chinese education system. Whether students can establish adaptive motivational beliefs in high school significantly influences their future academic development. Using latent cross-lagged modeling, the present study investigated the longitudinal interrelation among self-concept, interest value, and effort cost in students’ academic achievement from grade 11 to 12 for both math and English domains. Results based on a sample of 694 Chinese high school students revealed significant reciprocity between self-concept and effort cost in math. In math, effort cost in the second semester of grade 11 also negatively predicted interest value in the first semester of grade 12. In English, the development of motivational beliefs is relatively independent, only self-concept in the first semester of grade 11 negatively predicted effort cost in the second semester of grade 11. In both math and English, self-concept positively predicted academic achievement, whereas effort cost negatively predicted academic achievement. Latent interaction analysis further revealed that there was significant interaction effect between self-concept and effort cost on achievement in the math domain. Findings of the present study highlight the importance of students’ motivational beliefs in influencing their academic achievement. In the meantime, the developmental trajectories of motivational beliefs are dynamic and demonstrate a clear pattern of domain-specificity.

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