Cultivating innovative talent has become a primary path for China to develop science and technology and solve “bottleneck” technical problems. Catering to the trend of educational reform in the intelligent age, the use of robotics to enhance students’ creativity shows richer practical value and contemporary significance. In this study, 48 China and foreign experimental studies and 6,057 samples are coded using the meta-analysis method, and the findings are as follows: First, the overall effect of educational robots on students’ creativity is 0.576, reaching a medium or above level of influence. Among them, the effect of promoting students’ innovative, practical ability is the most obvious, and the degree of influence on the quality of innovative personality is average. Second, from the perspective of the academic stage, the effect of educational robots on the creativity of students in junior middle schools and primary schools is more obvious. Third, in terms of disciplines, robot courses impose the best effect on students’ creativity. Fourth, among teaching themes, prototype creation has the most impact on students’ creativity, and the level is above the intermediate level. Fifth, in terms of the choice of teaching methods, inquiry teaching can better stimulate students’ creativity. Finally, compared with ordinary classrooms, the laboratory environment is more optimistic for developing students’ creativity. Combined with field research, four practical suggestions are put forward.

The development of artificial intelligence (AI) technology and the demand for general-subject teaching give birth to general-subject AI teacher-led courses. In this study, 79 fourth-grade pupils from two classes in a primary school in Guangzhou City are selected as the samples. The research methods of interview, classroom observation, and questionnaire survey are used to explore the effects of the AI general- subject teacher on pupils’ learning effectiveness based on the framework of anthropomorphic learning process theory. The results show that the AI general-subject teacher can significantly enhance pupils’ learning motivation (including intrinsic motivation and extrinsic motivation), increase pupils’ learning engagement (including behavioral engagement, cognitive engagement, and emotional engagement), and improve pupils’ learning outcomes (including knowledge and skills, process and method, emotional attitude and values). The findings confirm the important role of the AI general-subject teacher as the main instructor to promote pupils’ efficient learning and provide a significant reference for solving the shortage problem of excellent teachers and reducing the burden on teachers.

With the adoption of competency reconstructing path of functional analysis in the organizational behavior theory, and the consideration of the core mission and attributes of educational organizations plus the urgency for digital transformation, this paper concludes four pillar competencies for teachers: 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 in 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’ information and communications technology capabilities in smart environments; effective moral education competency determines the primary role of teachers in the process of digital transformation; and self-growth competency is the purpose and means of digital existence. 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.

Based on the analysis of the digital foundation and transformation demands of teacher development, the paper proposes a logical architecture of teachers’ digital learning from the perspective of 70- 20-10 model for learning and development, including self-learning based on platform resources (10%), blended learning based on collaborative support (20%), and embedded learning based on work scenarios (70%). Then, a pyramid model of evaluation and governance for teacher development needs that is compatible with the three types of learning paradigms is proposed, i.e., focusing on using teacher portraits to evaluate learning behaviors, using skills certification to evaluate knowledge and competencies, and focusing on ethics to promote practical wisdom. Finally, to support the transformation of learning paradigms plus evaluation and governance, this paper proposes an action architecture of service upgrading for digital transformation in teacher development, namely, creating a multi-level coherent online learning architecture for platformization, creating a seamless learning space with multi dimensional integration for ecologization, and leading the transformation from just-in-time learning to just-in-need practice for practicalization, ultimately realizing a leap of teachers’ practical wisdom.

With the advantages of real time analysis and visual evaluation results, intelligent technology-enabled teaching behavior evaluation has gradually become a powerful means to help teachers adjust teaching behaviors and improve teaching quality. However, at present, the evaluation of intelligent teachers’ behaviors is still in the preliminary exploration stage, and the application research is not deep enough. This paper analyzes the application of intelligent technology in the evaluation of teachers’ classroom teaching behaviors from the perspectives of evaluation data, methods, and results. Voice print recognition technology is used to recognize the teachers’ identities and track the speech in the classroom videos, and the videos are segmented. Then, the evaluation framework of teachers’ classroom teaching behaviors is constructed using three dimensions of emotion, posture, and position preference. Finally, evaluation results are presented to teachers in a more intuitive and easy to-understand visual way, to help teachers reflect on teaching. This paper aims to promote the transformation of teachers’ classroom teaching behavior evaluation toward an intelligent, efficient, and sustainable direction through current research.

Online knowledge-sharing is the key link to individuals in the digital era. Postgraduates are the core members of the future knowledge-based society. Exploring factors affecting postgraduates’ online knowledge-sharing behavior is of significance promoting their fair enjoyment of digital dividends and contributing to the construction of Digital China. However, little literature exists on this topic. This study examines factors resulting in postgraduates’ differentiated online knowledge-sharing behavior from two dimensions: social structure and individual initiative. The results of the questionnaire survey of 501 postgraduates show that: First, not all postgraduates are aborigines of the digital age; and structural factors (gender, school type, location, father’s occupation, and father’s education) have a significant impact on postgraduates’ online knowledge-sharing behavior. These factors also have a greater impact on the quality of online knowledge sharing than in a quantity sense. Second, the individual initiative factor (information literacy) also has a significant impact on postgraduates’ online knowledge-sharing behavior. It has a greater impact on the quantity of online knowledge- sharing than in a quality sense. Third, there is a Matthew effect under the internet context, and certain effects of structural factors on online knowledge-sharing behavior are indirectly generated through individual initiative factors. Participants with privileged structural status show a higher level of information literacy, which further encourages them to be more active in online knowledge-sharing behavior and facilitates their high-quality production.

As an important teaching method in the era of education informatization 2.0, the smart classroom has become a hot topic in terms of whether it can really improve students’ learning effectiveness. Many scholars have carried out empirical studies in this field, but the conclusions are not the same. By the use of meta-analysis, this study quantitatively analyzes 48 experimental and quasi-experimental studies in China and other countries to explore the smart classroom’s effect and influencing factors. The results show that, on the whole, the smart classroom has a better-than-average promotion effect on students’ learning effectiveness; from the perspective of moderating variables, the learning outcome of smart classrooms is influenced by the factors of learning stage, knowledge type, teaching cycle, class scale, and equipment condition, but is not moderated by the factors of subject, teaching strategy, and evaluation tool. Specifically, smart classrooms can become a suitable partner for large-class teaching, short-term courses, and experimental courses. However, the misuse of technology and equipment should be avoided in the application process.

Teachers are the primary resource of education and an important guarantee for building a high-quality education system. Teaching research is an effective way for teacher professional development. This paper focuses on problems of the failure of traditional teaching research models, unbalanced supply, and inaccurate support, with the core goal of realizing the clustered, synergistic, and high quality development of teachers, and builds a new form model of three integrations, one focus, and N innovations for regional informatization teaching research with innovative characteristics, a dual coordination mechanism for the clustered high-quality development of teachers, and an accurate support strategy for the comprehensive literacy of teacher informatization teaching research.

In the era of artificial intelligence, teachers’ subjectivity presents new characteristics, such as the interweaving of virtual and reality, the integration of individual and groups, and the coexistence of exuberance and disorientation. While reshaping teachers’ subjectivity, intelligent technologies also easily make teachers fall into the subjectivity dilemmas, such as self-crisis, distortion of interaction, and alienation of action. Therefore, to reinstate teachers’ subjectivity, it is necessary to know oneself in pursuit of truth by sticking to the nature of life, to become oneself by constructing the nature of choice in practical activities, and to achieve oneself by returning to the nature of creation in lifelong learning.

Based on the increasingly prominent power of information technology in the innovative development of education, people pay more attention to the information and communications technology (ICT) teaching competency of pre-service teachers. In order to explore the supporting elements, key issues, and possible paths of current normal universities and colleges in cultivating pre-service teachers’ ICT teaching competency, this study collects the survey data of graduates from 20 normal universities and colleges at provincial & ministerial, local, and junior levels. Based on the total quality management theory, technology acceptance model, and pre-service teachers’ ICT teaching competency framework, it carries out the survey and analysis from three aspects: supporting elements, supporting effects, and ability development. The study finds that the support of personnel, facilities, curriculum, mechanism, and environment provided by normal universities and colleges does not play a full role in improving the ICT teaching competency of pre-service teachers. There are still great differences among different levels of universities and colleges. Among them, the influence of personnel support and curriculum support should be greatly strengthened, and facility support is even more inhibited. Based on these findings, it puts forward some strategies that are conducive to better cultivating the ICT teaching competency of pre-service teachers in the pre-service education stage, to make them adapt to the new standards and requirements for teachers in the new era. Keywords pre-

In recent years, China has been issuing artificial intelligence (AI) education policies to promote the deep integration between AI and education. Setting AI courses at the basic education phase can cultivate students’ AI literacy and enhance the country’s science and technology competitiveness in the future. However, due to shortages of AI teachers and inadequate conditions for practice, the current AI courses in primary and secondary schools are not enough in effectiveness. In light of current problems, this study, based on the foundation of university-enterprise cooperation, integrates the “competition and education” mechanism into informal AI course design and practice. Using a design-based research paradigm, the study proposes the design framework from four dimensions: goals, themes and content, methods and steps, and evaluation, and then further refines the framework through two rounds of iterations, to provide a reference for the development and practice of AI courses.

In the context of the highly demanding trend of equitable and quality education, digital technology has outlined a blueprint for sharing resources across spatial and temporal boundaries and learner differences. The hybrid classroom implemented on university campuses during the pandemic demonstrates the tremendous shaping power of digital technology on teaching and learning across different groups, time, and space. This study investigates two types of learners, Clone Classroom and Global Hybrid Classroom at Tsinghua University, and finds that intrapersonal, interpersonal, and institutional dimensions of classroom climate all significantly affect learners’ learning outcomes. However, the influences at the three dimensions differ in degree, with interpersonal factors outweighing institutional factors and institutional factors outweighing individual factors. Furthermore, in individual factors, information literacy and tech-assisted support in institutional factors have the weakest impact on learning outcomes; institutional factors mediate individual and interpersonal factors influencing higher order cognition development. To avoid the pitfalls of techno-centrism, this study suggests promoting an insight of technology for humanity and embedding technology into teaching to better empower teacher development and student learning experience.

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With the in-depth development of internet plus education and the COVID-19 pandemic, online learning has become a universal teaching method in the world. However, the issue of superficial and low quality in online learning is still widespread. From the internal and external conditions of online deep learning, this study reveals the theory mechanism of how the online learning environment and teacher support, as external conditions, affect students’ emotions and learning motivation, and then affect students’ internal learning state. On this basis, an online deep teaching model is constructed, which consists of three stages: online asynchronous self-study before class, online synchronous live broadcasting teaching in class, and online asynchronous expansion after class. Meanwhile, a one term long online teaching practice is carried out in the course named the Instructional System Design. The results show that, in the learning process level, the online deep teaching model can effectively improve students’ online learning engagement, promote students to use deep learning methods and deep learning motivation to learn, and enhance the depth of online interaction between students. At the level of learning results, students’ critical thinking and online academic performance have been significantly improved.

With the application of the internet, big data, and artificial intelligence (AI) in education, a new form of textbook construction has been developed, promoting digital textbook development. However, problems during digital textbook construction still exist. This study analyzes the necessity of intelligent textbook development and explains the educational characteristics of intelligent textbooks, such as intelligent adaptation learning, intelligent guidance, accompanying evaluation, and in-depth learning interaction from the perspective of instruction theory. Moreover, combining the technical advantages of AI, including knowledge mapping, learning analysis, online tracking, learner digital profiles, and in-depth interaction, and taking existing achievements for reference, it describes the methods and strategies of intelligent textbooks to achieve corresponding educational functions and also makes interpretation with specific cases. Given the educational and engineering characteristics of intelligent textbooks, this study analyzes the strategies for promoting the construction of intelligent textbooks from adhering to the instruction theory, paying attention to the iteration of practice, and adopting technical methods to supervise and regulate.

Under the background of “emerging engineering education,” the engineering education with national defense characteristics, has put forward higher requirements for the engineering practice training of college students. Based on this, focusing on three characteristics of virtual reality (VR) technology, this paper puts forward the construction ideas of VR technology applied in engineering practice training courses. Then, by taking Northwestern Polytechnical University’s “VR Assembly Composite Practice Training Course” for example, this paper designs the teaching process of the practice training course and analyzes the teaching effect through questionnaires. It finds that VR technology can avoid teaching risks, improve teaching quality, and have a high promotion value in the existing engineering practice training courses. Finally, three suggestions on the VR technology applied in engineering practice teaching are put forward.

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Assignments are an important tool to evaluate learners’ learning effectiveness in online courses. Clarifying assignment design strategies is of great significance for promoting the quality construction of online education courses. This paper uses Bloom’s taxonomy framework revised by Anderson and Krathwohl (2001) as a reference to label the knowledge types and cognitive dimensions in the assignment context of eight courses. Combined with a literature review, a discipline–objective–schedule (DOS) threedimensional analysis framework based on the achievement of curriculum objectives, the design of chapter schedule, and the heterogeneity of disciplines is constructed to conduct an in-depth analysis of online course assignment design strategies. The research findings show that the online course assignment design strategy has an obvious curriculum objective orientation, follows the gradual learning rule, and presents typical disciplinary differences. The study finds that the current assignment design of online courses has three issues: first, a mismatch between assignment design and curriculum objectives; second, a lack of diversity in assignment formats; and third, insufficient comprehensiveness of some subject assignments. Based on the above discussions, corresponding suggestions are provided.

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