This study explores the factors influencing work value orientation among digital generation university students in China, employing partial least squares structural equation modeling (PLS-SEM) to test and analyze a comprehensive theoretical model. Findings indicate that personal and work factors directly enhance work salience, while family and social factors influence work salience indirectly through personal factors, underscoring the mediating role of individual agency. The study provides practical implications for educators, employers, policymakers, and families to collaboratively cultivate intrinsic motivation, flexible digital workplaces, and equitable career environments that foster healthy, fulfillment-oriented work values among the digital generation.

The development and use of artificial intelligence (AI) create a huge demand on talents with comprehensive AI skills that should be cultivated in K-12 education. However, the AI program in K-12 education remains a critical bottleneck in the AI-talent pipeline. This study posits that the K-12 stage should establish the "Five Core Competencies"-encompassing interdisciplinary integration, top-tier innovation, future-oriented development, foundational literacy and values, and AI fundamentals and core capabilities-as its unified objective. Grounded in Vygotsky's theory of the Zone of Proximal Development, the study proposes a dynamic weighting of these competencies across different school phases. Building upon this, an "internal-external dual-cycle" cultivation architecture is constructed: the internal cycle operates through the iterative closed loop of "Curriculum system-AI tools-Teacher training" to drive student growth, while the external cycle functions via the synergistic closed loop of "Environment incentives-Management guarantee-Resource integration" to form the cultivation platform, thereby enabling dynamic talent development. This article designs a large-language-model (LLM) prompting framework oriented toward the five competencies to automatically generate interdisciplinary cultivation plans. The educational effectiveness of these AI-generated plans is then rigorously evaluated through a comparative experiment. The evaluation metrics are theoretically grounded in the works of Piaget, Bruner, and Gardner, focusing on the three dimensions of cognitive appropriateness, knowledge structuring, and intellectual diversity. The experimental results affirm that interdisciplinary integration constitutes a pivotal pathway for cultivating AI talent. Furthermore, the dual-cycle architecture, when coupled with the competency-guided LLM generation approach, demonstrably enhances the systematicity and adaptability of the cultivation plans.

This study investigates the relationship between AI ethics literacy and students’ self-rated learning competence using AI by developing a comprehensive framework of AI ethics literacy comprising knowledge, attitude, and competence dimensions. Data were collected from 482 college students through an online questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Key findings reveal that: (1) AI ethics knowledge is primarily characterized by four ethical principles: fairness and inclusivity, privacy protection, human-centricity, and responsibility and accountability; (2) AI ethics knowledge positively influences both AI ethics attitude and competence; and (3) AI ethics attitude and competence significantly enhance students’ self-rated learning competence using AI. This research contributes a novel theoretical framework for understanding AI ethics literacy while providing practical insights for cultivating students’ self-rated learning competence using AI.

Artificial Intelligence in Education (AIED) is becoming increasingly influential in the educational sphere, offering significant benefits and presenting ethical risks. This study fills a crucial gap by systematically classifying and analyzing these risks. Using a combined approach of systematic review and grounded theory coding, ethical risks were categorized into three dimensions: technology, education, and society. In the technology dimension, risks include privacy invasion, data leakage, algorithmic bias, the black box algorithm, and algorithmic error. The education dimension risks involve student homogenized development, homogeneous teaching, teaching profession crisis, deviation from educational goals, alienation of the teacher-student relationship, emotional disruption, and academic misconduct. Risks in the society dimension consist of exacerbating the digital divide, the absence of accountability, and a conflict of interest. Based on an analysis of the types, potential triggers, and hazards associated with these risks, we propose strategies spanning three critical dimensions—technology, education, and society, from the perspectives of stakeholders, to address these ethical risks. This study contributes to a concise and precise analysis of the ethical risks associated with AIED, offering practical solutions for the responsible implementation of AIED.

In the domain of smart education, the integration of intelligent technology has undergone extensive exploration, yet a comprehensive investigation into its transformative potential for teaching and learning remains elusive. To address this research gap, our study employs a literature review methodology, analyzing 55 studies to offer empirical insights into the application of intelligent technologies in reshaping educational paradigms. The key findings encompass: (a) the identification of five crucial pillars of smart education, namely intelligent technology, smart pedagogy, smart learning environments, smart learning, and smart learners; (b) the acknowledgment that smart education relies on diverse intelligent technologies, such as the Internet of Things, artificial intelligence, virtual/augmented reality, big data, cloud computing, and smart mobile devices; and (c) the identification of three typical teaching methods and five learning methods supported by intelligent technology for smart education. This systematic review provides valuable insights and implications for advancing teaching and learning through the strategic utilization of intelligent technologies.

At the opening ceremony of the u201CGlobal Smart Education Conference 2024u201D, the Global Smart Education Network released the Global Understanding of Smart Education in the Context of Digital Transformation, which promoted the consensus understanding of international smart education. In order to promote the in-depth research and practice of education digitization, this paper interpreted this report. Firstly, the questionnaire and Delphi methods were adopted to collect the views of 92 policy makers, researchers and educators from 41 different countries, and the international consensus understanding and regional development priorities of smart education were extracted from the perspective of experts. Secondly, 48 digital education policy documents from 48 countries were combed and analyzed in this report, and the planning focuses of digital education under the policy perspective were clarified, which involved the phase division, core features, and policy focuses of different regions, etc. Thirdly, based on the international publicly available relevant education data, this report constructed an observation framework for the development of global smart education, which included 10 primary indicators and 30 secondary indicators, and analyzed the development status of smart education in different countries, and the contribution degree of each smart education indicator to the quality of education. Finally, based on the results and recommendations of expert webinars from more than 10 countries, the strategies to promote the inclusion and equity of smart education were proposed. The interpretation to the report in this paper can provide reference for promoting the digital transformation of education and the international understanding of smart education.

ChatGPT has proven to facilitate computer programming tasks through the strategic use of prompts, which effectively steer the interaction with the language model towards eliciting relevant information. However, the impact of specifically designed prompts on programming learning outcomes has not been rigorously examined through empirical research. This study adopted a quasi-experimental framework to investigate the differential effects of prompt-based learning (PbL) versus unprompted learning (UL) conditions on the programming behaviors, interaction qualities, and perceptions of college students. The study sample consisted of 30 college students who were randomly assigned to two groups. A mixed-methods approach was employed to gather multi-faceted data. Results revealed notable distinctions between the two learning conditions. First, the PbL group students frequently engaged in coding with Python and employed debugging strategies to verify their work, whereas their UL counterparts typically transferred Python code from PyCharm into ChatGPT and posed new questions within ChatGPT. Second, PbL participants were inclined to formulate more complex queries independently, prompted by the guiding questions, and consequently received more precise feedback from ChatGPT compared to the UL group. UL students tended to participate in more superficial-level interactions with ChatGPT, yet they also obtained accurate feedback. Third, there were noticeable differences in perception observed before and after the ChatGPT implementation, UL group reported a more favorable perception in the perceived ease of use in the pre-test, while the PbL group experienced an improvement in their mean scores for perceived usefulness, ease of use, behavioral intention to utilize, and a significant difference regarding the attitude towards utilizing ChatGPT. Specifically, the use of structured output and delimiters enhanced learners’ understanding of problem-solving steps and made learning more efficient with ChatGPT. Drawing on these outcomes, the study offers recommendations for the incorporation of ChatGPT into future instructional designs, highlighting the structured prompting benefits in enhancing programming learning experience.

Online-merge-offline (OMO) learning in a hybrid learning space is becoming a popular pedagogy to enhance students' blended learning using appropriate technology. This investigation delves into the impact of OMO learning on developing physics problem-solving skills among high school students. A ten-week intervention employing OMO learning is implemented with 34 participants in both the experimental and control groups at a high school in Hangzhou, China. The efficacy of OMO learning is assessed through a quasi-experimental design encompassing pre- and post-assessments. The findings of this inquiry reveal: (1) The experimental group's physics problem-solving abilities are significantly impacted by OMO learning; (2) the use of cognitive tools rationally, the integration of online and offline collaborative learning, rich learning resources, and heuristic teaching all help students become more adept at solving physics problems; and (3) the cognitive load, students' lack of prior knowledge, poor self-regulation, and lack of help-seeking techniques all work against the improvement of students' physics problem-solving abilities. Suggestions are made in line with the research results and aims.

Integrating intelligent technology to promote smart education, had become a focus of education policies in many countries. However, there was little literature on strategies and trends of smart education policies at the national level. This study investigated the framework for developing national smart education strategies and trends of national policy making on smart education. Based on the Delphi technique method, a National Smart Education Framework was developed, consisting of four essential leveraging points: (1) forward-thinking governance and policy initiatives, (2) digital learning environments conducive to smart education, (3) transformative teaching and learning enabled through technology, and (4) overarching considerations. Additionally, a textual analysis method was employed to analyze 24 smart education policies from 24 countries or organizations, to uncover the strategies and policy trends of smart education in accordance with the proposed smart education framework. Promoting high-quality, inclusive, and accessible education, increasing Internet connectivity and access to digital tools, enhancing digital skills, ensuring information security and privacy, implementing new digital pedagogies, providing real-time feedback, emphasizing critical thinking, problem-solving, and creativity, etc. were the main trends for smart education policy making. The findings of this study provide valuable insights for policymakers and educators in shaping smart education policies and practices worldwide to promote sustainable development.

This research delves into the global understanding of smart education from various perspectives, including expert viewpoints, policy dimensions, public datasets, and visions of equity and inclusion. Multiple webinars have revealed that the concept of smart education with a shared vision of quality education in the age of AI is being understood by different countries through diverse cultural, technological, and pedagogical lenses. We collected 48 topical digital education policies from Africa, the Americas, Asia-Pacific, and Europe and conducted coding analysis on inspective digital education policies for smart education to find that creating a high-quality, inclusive, and sustainable digital education ecosystem is the main concern in digital education policy vision and plan. Infrastructure development and human capacity building are also integral to digital education policies. Analysis of public datasets identified a global framework for tracking smart education encompassing 10 indicators and 30 sub-indicators was identified which coincide well with the GSE datasets covering 58 observing data points. Additionally, we organized a series of webinars with participants from 13 countries and explored specific cases to find pathways to achieve Sustainable Development Goal 4.

Smart Learning Environments (SLEs) have evolved rapidly over the past 20 years. However, current investigations of SLEs have narrowly focused on specific technologies or have remained at the theoretical level without discussing the practical implications; the role and application of technology in teaching and learning aren't sufficiently clear. The purpose of this review is to systematically examine the design and learning approaches of SLEs. This study employs a literature review method, specifically analyzing the literature on SLEs in the Web of Science database. (a) SLEs are globally recognized research fields, with contemporary studies emphasizing five key areas: technical support for SLEs, the design of learning spaces, teaching and learning ways in SLEs, SLEs models and assessment of SLEs' quality. (b) Research mainly focuses on software devices like smart learning systems and platforms for technical support, with limited attention given to hardware devices. (c) The design of learning spaces is trending toward integrating virtual and physical elements. (d) Learning approaches in technology-supported SLEs focus on cooperative learning and autonomous learning. Finally, in view of the shortcomings of the current research, suggestions for future research are put forward.

同步课堂的开展能够推动基础教育均衡发展,实现不同区域学校优质教育资源共享.从规模化应用角度对同步课堂实践过程中教师同步教学能力进行分析,通过问卷调查探讨了两端教师同步教学能力的现状和差异.发现:开展同步课堂教学实践活动,技术环境应用能力是两端教师同步教学能力的基础;协同备课能力是两端教师同步教学能力的重要组成部分.因此,针对以上结论提出相应对策:强化两端教师信息技术应用能力和信息技术与学科知识融合的能力,强化两端教师之间的协同备课教研能力.

Online learning became more commonplace all over the world in the post-pandemic era; however, the research on how to promote Online Persistent Learning (OPL) was still in its infancy. Therefore, this study aimed to analyse the influencing factors of Online Persistent Learning Supported by Intelligent Technology (OPLSIT) based on the dimensions of user's stickiness, dispositional trust and learning satisfaction. The Partial Least Squares Structural Equation Model (PLS-SEM) method was used to analyse data collected from 385 students who experienced online learning supported by intelligent technology (OLSIT). The results showed that learning satisfaction has a significant positive impact on OPL. In addition, user stickiness and dispositional trust were also two important predictors of OPL. Learning intention, social presence and cognitive presence were positively correlated with learning satisfaction, which indirectly and positively influence OPL. Technology anxiety had a negatively impact on learning satisfaction, which indirectly and negatively affected the OPL. Therefore, suggestions that enhance OPLSIT were put forward from the perspectives of teaching presence, cognitive presence, social presence, emotional presence, learning intention and dispositional trust and user stickiness for the design and development of intelligent online learning tools.

The purpose of this study was to investigate the influence of interaction quality and information quality of intelligent learning tools on students' satisfaction and intention to use these tools, as well as to examine the relationship between the intention to use intelligent learning tools and students' independent learning abilities. The study utilized Smart-PLS 3, a Partial Least Squares Structural Equation Modeling (PLS-SEM), to analyze data collected from 384 Grade 6 students in China. The results of the study showed that (a) intention to use intelligent learning tools had a significant and direct impact on students' independent learning abilities; (b) interaction quality did not have a significant impact on intention to use, but information quality and satisfaction with the tools did have an impact on intention to use; (c) interaction quality and information quality indirectly influenced intention to use through students' satisfaction with the tools. Furthermore, this research provided valuable recommendations for improving the interaction quality and information quality of intelligent learning tools, which can ultimately enhance students' independent learning abilities.

Este estudo teve como objetivo identificar os principais pilares da prática política para promover o desenvolvimento da educação inteligente através da análise de questões políticas relacionadas à educação inteligente na China de 2013 a 2023. Quatro pontos de alavancagem foram apresentados: governança prospectiva e iniciativas políticas, ambientes inteligentes de aprendizagem, ensino e aprendizagem transformadores habilitados através da tecnologia e considerações abrangentes para educação inteligente. As conclusões enfatizaram a importância da governança proativa e da formulação de políticas, do estabelecimento de ambientes de aprendizagem adaptativos, da integração da tecnologia para promover práticas transformadoras de ensino e de aprendizagem, e de considerações abrangentes para a implementação sustentável da educação inteligente.

The development of pre-service teachers' digital teaching competence is crucial for effectively infusing technology into teaching. With the growing importance of data in education, it is imperative to explore the influencing factors of digital teaching competence and the potential role of data literacy in facilitating competence. Thus, this study focused on investigating the factors influencing pre-service teachers' digital teaching competence, namely technology attitudes, technology operations, technology ethics, and data literacy. Additionally, it examined the potential effect of data literacy on digital teaching competence. The study involved 244 Chinese pre-service teachers, and a Structural Equation Model (SEM) was created using SPSS and SmartPLS for analysis. The findings highlighted that technology attitudes, technology ethics, and data literacy directly influenced pre-service teachers' digital teaching competence. Data literacy fully mediated the relationship between technology operations and digital teaching competence, and partially mediated the relationships between technology attitudes and digital teaching competence, as well as between technology ethics and digital teaching competence. Moreover, technology ethics acted as a partial mediator between technology attitudes and both digital teaching competence and data literacy. These results indicated that fostering positive technology attitudes, technology operations, and technology ethics could enhance pre-service teachers' data literacy and improve their digital teaching competence.

The digital divide between rural and urban areas is becoming the key factors resulting educational imbalance, which might be exacerbated by differences in teachers’ digital teaching competence. Therefore, it was crucial to explore the divide and determinants of digital teaching competence between rural and urban teachers. A large-scale survey was conducted with 11,784 K–12 teachers in China (43.40% from rural schools and 56.60% from urban schools). First, this study investigated potential factors for teachers’ digital teaching competence, including information and communication technology (ICT) attitude, ICT skills, and data literacy. Second, the data indicated the digital divide existed, i.e., the ICT attitude, ICT skills, data literacy, and digital teaching competence of rural teachers were significantly lower than those of urban teachers. Third, the Blinder-Oaxaca decomposition method demonstrated that data literacy and ICT skills were the most important determinants of the divide in digital teaching competence between rural and urban teachers. Hence, our research provided important insights for policymakers, school leaders and teachers to bridge the digital divide.

With the digital transformation of education, data and digital technologies are regarded as the driving forces for teaching innovation. Teachers' data literacy and digital teaching competence are becoming increasingly important for empowering students' digital capacity, ethically technology usage, and collaboration or communication skills in the classroom. Therefore, whether teachers' data literacy and digital teaching competence can empower students in the classroom needs to be explored. This study aims to reveal the relationship between teacher's information communication technology (ICT) attitude, ICT skills, data literacy, digital teaching competence and empowering students. The data were collected from an online self-assessment scale which included a total of 629 K-9 teachers who participated in this study. Using SPSS and AMOS, a model was built by using Structural Equation Models to explain and predict the relationships. The results indicated that: (a) ICT attitude had no significant impact on digital teaching competence, and ICT skills significantly predicted digital teaching competence, but neither ICT attitude nor skills had a significant direct impact on empowering students; (b) data literacy significantly predicted digital teaching competence and had a significant direct impact on empowering students; (c) digital teaching competence, as dominant mediator in ICT attitude, ICT skills and data literacy, strongly predicted empowering students. The findings provided valuable evidence for teachers, policymakers, administrators, teacher educators, and teachers to better reimagine the teachers' digital teaching competence. In the future, the teachers' digital teaching competence should become the top priority in teacher ICT training, which was the most direct influencing factor for empowering students.

Synchronous classrooms use video conferencing systems to connect students in physical classrooms and online classrooms to the same class. With the development of Internet technology, the research and application of synchronous classroom has developed rapidly since 2010. The study retrieved and screened 59 sample literatures from Chinese and English electronic databases, and conducted a systematic literature review. The study found: (1) From the perspective of research topics, the research on synchronous classroom mainly focuses on theoretical research, teaching mode, teaching strategy, classroom interaction design, support of environmental technology, teaching effect, synchronous classroom Intercultural learning in classroom support, teacher professional development, teaching and learning experiences, and more. (2) From the perspective of application effects, the implementation of synchronous classrooms has a good effect on improving students’ academic performance, promoting teachers’ professional development, promoting school informatization construction, and sharing regional high-quality educational resources. (3) From the perspective of hindering factors, remote students have low classroom participation; teacher and assistant’s information teaching capabilities need to be improved; school technical environment support is not yet perfect; education administrators lack multidisciplinary collaboration and organizational management capabilities.