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01 November 2022, Volume 40 Issue 11 Previous Issue   

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Prelude to the Special Issue on Educational Psychology: Celebrating the 5th Anniversary of the Department of Educational Psychology at ECNU Zhenguo Yuan 2022, 40 (11):  1-3.  doi: 10.16382/j.cnki.1000-5560.2022.11.001 Abstract ( 116 )   HTML ( 31 )   PDF (496KB) ( 104 )   Save Educational psychology is one of the fundamental disciplines in the field of education. Over the past hundred years, educational psychology has been continuously innovated by generations of educators and researchers. Entering the 21st century, educational psychology is facing a situation in which opportunities and challenges coexist. In this context, ECNU established the Department of Educational Psychology in the Faculty of Education in 2017, focusing on the learning and development of students of all ages and committed to theoretical innovation and realistic problem solving. What should and can educational psychology do, and how should the discipline develop in the future? To reflect on the past, work on the present, and look to the future, this special issue discussed the positioning and development of educational psychology, with the goal of shedding lights on policymaking and educational reform in China. References | Related Articles | Metrics

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The Crisis of Educational Psychology: Its Challenge and Positioning Yun Dai David 2022, 40 (11):  4-24.  doi: 10.16382/j.cnki.1000-5560.2022.11.002 Abstract ( 167 )   HTML ( 33 )   PDF (915KB) ( 325 )   Save 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. Figures and Tables | References | Related Articles | Metrics

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Psychological Views on Cultivating Students’ Creativity: Goals, Principles, and Strategies Weiguo Pang 2022, 40 (11):  25-40.  doi: 10.16382/j.cnki.1000-5560.2022.11.003 Abstract ( 87 )   HTML ( 9 )   PDF (738KB) ( 189 )   Save 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. References | Related Articles | Metrics

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Competence and Its Model Building: A Theoretical Analysis Xiangdong Yang 2022, 40 (11):  41-57.  doi: 10.16382/j.cnki.1000-5560.2022.11.004 Abstract ( 114 )   HTML ( 15 )   PDF (965KB) ( 183 )   Save 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. Figures and Tables | References | Related Articles | Metrics

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A Conceptual Framework of Higher-order Thinking Shufeng Ma, Xiangdong Yang 2022, 40 (11):  58-68.  doi: 10.16382/j.cnki.1000-5560.2022.11.005 Abstract ( 297 )   HTML ( 35 )   PDF (755KB) ( 310 )   Save 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. Figures and Tables | References | Related Articles | Metrics

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IQ or EQ: Which is More Important for Students’ Learning ? Jing Zhang 2022, 40 (11):  69-79.  doi: 10.16382/j.cnki.1000-5560.2022.11.006 Abstract ( 119 )   HTML ( 28 )   PDF (1243KB) ( 153 )   Save 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. Figures and Tables | References | Related Articles | Metrics

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Developmental Trajectory of High School Students’ Academic Motivation and Its Relation with Academic Achievement Yi Jiang 2022, 40 (11):  80-91.  doi: 10.16382/j.cnki.1000-5560.2022.11.007 Abstract ( 84 )   HTML ( 22 )   PDF (910KB) ( 139 )   Save 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. Figures and Tables | References | Related Articles | Metrics

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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 2022, 40 (11):  92-109.  doi: 10.16382/j.cnki.1000-5560.2022.11.008 Abstract ( 112 )   HTML ( 22 )   PDF (978KB) ( 170 )   Save 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. Figures and Tables | References | Related Articles | Metrics

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What Can Bayesian Network Contribute to Educational Research？ Xin Gu, Mengqi Mao, Shufeng Ma, Senyu Chen 2022, 40 (11):  110-122.  doi: 10.16382/j.cnki.1000-5560.2022.11.009 Abstract ( 79 )   HTML ( 12 )   PDF (1550KB) ( 142 )   Save 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. Figures and Tables | References | Related Articles | Metrics

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The Past, Present and Future of Educational Psychology： A Discussion with Professor Eric Anderman M. Anderman Eric, Shufeng Ma, Yi Jiang, Xiangdong Yang 2022, 40 (11):  123-134.  doi: 10.16382/j.cnki.1000-5560.2022.11.010 Abstract ( 87 )   HTML ( 23 )   PDF (656KB) ( 136 )   Save Focusing on the topic of “The Past, Present and Future of Educational Psychology”, scholars from the Department of Educational Psychology at East China Normal University and Professor Eric Anderman of The Ohio State University reviewed the current trends in educational psychology and discussed the relationship between educational psychology and brain sciences, learning sciences, and other disciplines in the field of education. On this basis, we further reflected on the challenges and opportunities facing educational psychology in the new era, especially in the context of the COVID-19 pandemic. We discussed how educational psychology could promote children and adolescents’ learning and development, how theory and practice could support each other, and how to respond to the needs of future development in society. Finally, Professor Anderman emphasized the importance of interdisciplinary collaboration in the field, and provided his suggestions for the development of educational psychology in China. References | Related Articles | Metrics