Rethinking Higher Education/Chapter 9/en-zh

Language: EN · ZH · EN-ZH · ← Book

Chapter 9: Digital Natives in China and Europe

Martin Woesler

English (Source)	中文 (Target)
== Digital Natives in China and Europe: Comparative Digital Literacy, AI Attitudes, and Educational Implications ==	== 中欧数字原住民：数字素养、人工智能态度与教育启示的比较研究 ==
Martin Woesler	Martin Woesler
Hunan Normal University	湖南师范大学
Abstract	摘要
The concept of the „digital native“ — introduced by Marc Prensky in 2001 to describe a generation supposedly transformed by immersion in digital technology — has profoundly influenced educational policy on both sides of the Eurasian continent. Yet two decades of empirical research have consistently failed to validate its central claim: that growing up with technology produces uniformly high digital competence. This article examines digital literacy, AI attitudes, and educational implications through a systematic comparison of the European Union and China, drawing on the EU’s DigComp 2.2 framework (250+ competence examples across 21 areas), China’s centralized digital literacy campaigns, and recent empirical studies of student and teacher digital competence. We document significant gaps: only 55.6 percent of the EU population possesses at least basic digital skills, despite the Digital Decade target of 80 percent by 2030; China has achieved 99.9 percent broadband connectivity in schools while rural internet penetration remains at 69.5 percent. A multinational assessment of 1,465 university students across Germany, the United Kingdom, and the United States reveals substantial cross-national variation in AI literacy, while a latent profile analysis of 782 Chinese EFL teachers identifies four distinct AI literacy profiles ranging from „poor“ (12.1 percent) to „excellent“ (14.1 percent). We argue that the digital native myth has created dangerous policy assumptions — that young people need less, rather than more, structured digital education — and that both European and Chinese approaches must shift from measuring access to cultivating critical digital competence, AI literacy, and the capacity for responsible digital citizenship.	"数字原住民"概念——由Marc Prensky于2001年提出，用以描述据说因沉浸于数字技术而发生根本转变的一代人——对欧亚大陆两端的教育政策产生了深远影响。然而，二十年的实证研究始终未能验证其核心主张：在技术环境中成长并不能产生普遍较高的数字能力。本文通过对欧盟和中国的系统比较，考察了数字素养、人工智能态度和教育启示，借鉴了欧盟DigComp 2.2框架（21个领域的250多个能力示例）、中国集中式数字素养运动以及近期关于学生和教师数字能力的实证研究。我们记录了显著的差距：尽管"数字十年"的目标是到2030年达到80%，但只有55.6%的欧盟人口拥有至少基本的数字技能；中国在学校中实现了99.9%的宽带连接，而农村互联网普及率仍为69.5%。对德国、英国和美国1,465名大学生的多国评估揭示了人工智能素养的重大跨国差异，而对782名中国EFL教师的潜在类别分析确定了从"差"（12.1%）到"优秀"（14.1%）的四种不同人工智能素养类别。我们认为，数字原住民神话造成了危险的政策假设——年轻人需要的是更少而非更多的结构化数字教育——欧洲和中国的方法都必须从衡量接入转向培养批判性数字能力、人工智能素养和负责任的数字公民能力。
Keywords: digital natives, digital literacy, AI literacy, DigComp 2.2, China digital education, European digital skills, digital divide, Gen Z, digital competence, comparative education	关键词：数字原住民、数字素养、人工智能素养、DigComp 2.2、中国数字教育、欧洲数字技能、数字鸿沟、Z世代、数字能力、比较教育
1. Introduction	1. 引言
In 2001, Marc Prensky published a short essay in On the Horizon that would reshape educational discourse for a generation. „Digital Natives, Digital Immigrants“ argued that students entering the education system had been fundamentally transformed by their immersion in digital technology: they „think and process information fundamentally differently from their predecessors,“ and educators — digital immigrants who had adopted technology later in life — must adapt or become irrelevant (Prensky 2001). The metaphor was powerful, intuitive, and immediately influential. Within a decade, it had become a foundational assumption of educational technology policy worldwide.	2001年，Marc Prensky在《On the Horizon》上发表了一篇短文，重塑了一代人的教育话语。"数字原住民、数字移民"一文认为，进入教育系统的学生因沉浸在数字技术中而发生了根本性转变：他们"从根本上以不同于前辈的方式思考和处理信息"，而教育者——在后期才接触技术的数字移民——必须适应否则就会变得无关紧要（Prensky 2001）。这个隐喻强大、直觉且立即产生了影响力。不到十年，它已成为全球教育技术政策的基础性假设。
It was also, as subsequent research would demonstrate, largely wrong. Bennett, Maton, and Kervin (2008), in what remains the most widely cited critical assessment, showed that the empirical evidence did not support claims of a generation with uniformly high technological skills or radically different learning styles. The variation within age cohorts far exceeded the variation between them. Socioeconomic status, educational background, and individual motivation were far stronger predictors of digital competence than generational membership. The „digital natives„ debate, they concluded, resembled an academic „moral panic“ more than an evidence-based policy framework. Reid, Button, and Brommeyer (2023) confirmed these findings in a narrative review spanning two further decades of evidence: exposure to digital technologies does not equate to digital literacy, and the myth has created deficits in educational programs by assuming students already possess adequate digital skills.	然而，正如后续研究所证明的，它在很大程度上是错误的。Bennett、Maton和Kervin（2008）在迄今被引用最多的批判性评估中表明，实证证据不支持关于一代人具有普遍高技术技能或根本不同学习方式的主张。同一年龄群体内部的差异远大于群体之间的差异。社会经济地位、教育背景和个人动机是数字能力的预测因素，其效力远强于代际成员身份。他们得出结论，"数字原住民"之争更像是一场学术"道德恐慌"，而非基于证据的政策框架。Reid、Button和Brommeyer（2023）在涵盖此后二十年证据的叙述性综述中确认了这些发现：接触数字技术并不等同于数字素养，这一神话因假设学生已具备足够的数字技能而在教育项目中制造了缺陷。
Mertala and colleagues (2024), in a bibliometric analysis of 1,886 articles published between 2001 and 2022, document the remarkable persistence of the digital native concept despite its empirical weakness. The initial literature relied on unvalidated claims and waned upon facing empirical challenges, yet the concept continues to shape policy and public discourse — particularly in contexts where rapid digitalization creates pressure to demonstrate technological readiness.	Mertala等人（2024）在对2001至2022年间发表的1,886篇文章的文献计量分析中，记录了数字原住民概念尽管实证基础薄弱却具有显著的持久性。最初的文献依赖于未经验证的主张，在面对实证挑战后逐渐减弱，但该概念继续影响着政策和公共话语——尤其是在快速数字化造成展示技术准备度的压力的背景下。
This article examines the contemporary reality behind the digital native myth through a systematic comparison of the European Union and China. Both are rapidly digitizing their education systems. Both face significant digital divides. Both are developing frameworks to measure and cultivate digital competence. Yet they approach these challenges from fundamentally different institutional, cultural, and political positions. By comparing their frameworks, their empirical outcomes, and their policy responses, we aim to move beyond the digital native myth toward an evidence-based understanding of what young people in China and Europe actually know, can do, and need to learn about digital technology and artificial intelligence.	本文通过对欧盟和中国的系统比较来考察数字原住民神话背后的当代现实。两者都在迅速推进教育系统的数字化。两者都面临显著的数字鸿沟。两者都在开发衡量和培养数字能力的框架。然而，它们从根本不同的制度、文化和政治立场出发应对这些挑战。通过比较它们的框架、实证结果和政策应对，我们旨在超越数字原住民神话，走向对中国和欧洲年轻人实际上了解什么、能做什么以及需要学习什么关于数字技术和人工智能的循证理解。
2. Frameworks: DigComp 2.2 versus China‘s Digital Literacy Initiatives	2. 框架：DigComp 2.2与中国的数字素养倡议
2.1 The European Approach: DigComp 2.2	2.1 欧洲方法：DigComp 2.2
The European Union‘s primary instrument for defining and measuring digital competence is the Digital Competence Framework for Citizens (DigComp), developed by the Joint Research Centre. The most recent version, DigComp 2.2, published in 2022, provides over 250 new examples of knowledge, skills, and attitudes organized across 21 competences in five areas: information and data literacy, communication and collaboration, digital content creation, safety, and problem solving. Notably, the 2022 update incorporates examples related to artificial intelligence systems and data-driven technologies, reflecting the recognition that digital competence now encompasses AI literacy as a core component (Vuorikari, Kluzer, and Punie 2022).	欧盟定义和衡量数字能力的主要工具是公民数字能力框架（DigComp），由联合研究中心开发。最新版本DigComp 2.2（2022年发布）提供了250多个新的知识、技能和态度示例，组织在五个领域的21项能力中：信息与数据素养、沟通与协作、数字内容创建、安全以及问题解决。值得注意的是，2022年更新纳入了与人工智能系统和数据驱动技术相关的示例，反映了对数字能力如今涵盖AI素养作为核心组成部分的认识（Vuorikari、Kluzer和Punie 2022）。
DigComp 2.2 is explicitly citizen-oriented. Its competence descriptors are designed to be applicable to all individuals regardless of professional context, and it serves as the reference framework for the EU’s Digital Decade target of 80 percent of citizens with at least basic digital skills by 2030. The framework has been adopted or adapted by numerous member states for national curricula, teacher training programs, and digital skills assessment tools.	DigComp 2.2明确以公民为导向。其能力描述旨在适用于所有个人而不论其专业背景，并作为欧盟"数字十年"目标——到2030年80%的公民具备至少基本数字技能——的参考框架。该框架已被众多成员国采用或改编，用于国家课程、教师培训项目和数字技能评估工具。
The Digital Education Action Plan 2021–2027 provides the strategic context for DigComp’s implementation in education. The plan establishes 14 actions across two priority areas — fostering a high-performing digital education ecosystem and enhancing digital skills and competences — with specific targets for updating DigComp to incorporate AI and data skills and for establishing a European Digital Skills Certificate (European Commission 2020).	《数字教育行动计划2021–2027》为DigComp在教育中的实施提供了战略背景。该计划在两个优先领域——促进高性能数字教育生态系统和提升数字技能和能力——下确立了14项行动，包括更新DigComp以纳入AI和数据技能以及建立欧洲数字技能证书等具体目标（European Commission 2020）。
2.2 The Chinese Approach: Centralized Digital Literacy Campaigns	2.2 中国方法：集中式数字素养运动
China‘s approach to digital literacy differs fundamentally in its institutional architecture. Rather than a single citizen-oriented framework, China deploys digital literacy through centralized government-led initiatives coordinated across multiple ministries. The 2025 Plan for Enhancing National Digital Literacy and Skills, jointly issued by the Office of the Central Cyberspace Affairs Commission, the Ministry of Education, the Ministry of Industry and Information Technology, and the Ministry of Human Resources and Social Security, establishes priorities including developing digital talent cultivation systems, expanding AI application and governance, building an inclusive digital society, and promoting international cooperation (CNNIC 2025; Central Cyberspace Affairs Commission et al. 2025).	中国的数字素养方法在制度架构上有着根本性的不同。中国不是采用单一的公民导向框架，而是通过跨多个部委协调的集中式政府主导倡议来推动数字素养。《2025年提升全民数字素养与技能行动计划》由中央网信办、教育部、工信部和人社部联合发布，确立了包括发展数字人才培养体系、扩大人工智能应用与治理、建设包容性数字社会以及促进国际合作在内的优先事项（CNNIC 2025；中央网信办等 2025）。
The Education Informatization 2.0 Action Plan, launched in 2018, set targets for teaching applications covering all teachers, learning applications covering all students, and digital campus construction covering all schools (Yan and Yang 2021). The results have been dramatic in infrastructure terms: by 2025, 99.9 percent of all Chinese schools have 100 Mbps or faster broadband, 99.5 percent have multimedia classrooms, and over 75 percent offer wireless campus internet. The National Smart Education Platform connects 519,000 schools, serving 18.8 million teachers and 293 million students (Ma 2025).	《教育信息化2.0行动计划》（2018年启动）设定了教学应用覆盖全体教师、学习应用覆盖全体学生、数字校园建设覆盖全部学校的目标（Yan和Yang 2021）。在基础设施方面的成果是显著的：到2025年，99.9%的中国学校拥有100Mbps或更快的宽带，99.5%拥有多媒体教室，超过75%提供校园无线网络。国家智慧教育平台连接了519,000所学校，服务1,880万教师和2.93亿学生（Ma 2025）。
Wang and d’Haenens (2025), in what appears to be the first direct comparison of the EU’s State of the Digital Decade 2024 report and China‘s National Digital Literacy and Skills Development Survey Report 2024, identify a characteristic pattern: China’s progress is attributable to centralized government-led initiatives that achieve rapid infrastructure deployment and standardization, while the EU’s approach emphasizes individual competence development through framework-based assessment. Both face persistent challenges — China with the urban-rural divide, the EU with inter-state variation — but the nature of those challenges reflects their different institutional models.	Wang和d'Haenens（2025）在首次直接比较欧盟《2024年数字十年状况》报告和中国《2024年全民数字素养与技能发展调查报告》的研究中发现了特征性模式：中国的进展归功于实现快速基础设施部署和标准化的集中政府主导倡议，而欧盟的方法则强调通过基于框架的评估实现个人能力发展。两者都面临持续性挑战——中国在城乡差距方面，欧盟在成员国间差异方面——但这些挑战的性质反映了各自不同的制度模式。
Wu (2024) proposes a Digital Literacy Framework for Chinese College Students structured as a progressive „Skills–Competencies–Awareness“ relationship, identifying 15 descriptors validated through empirical research. This framework reflects a growing recognition in Chinese educational research that infrastructure deployment alone is insufficient: students need structured competence development, not merely access to technology.	Wu（2024）提出了一个中国大学生数字素养框架，结构为渐进式的"技能—能力—意识"关系，确定了经实证研究验证的15项描述指标。该框架反映了中国教育研究界日益增长的认识：仅靠基础设施部署是不够的——学生需要的是结构化的能力发展，而非仅仅是技术接入。
3. AI Literacy Across Borders	3. 跨国界的人工智能素养
3.1 Policy Landscape	3.1 政策格局
The rapid deployment of AI systems in education and the workplace has generated a parallel demand for AI literacy — the ability to critically evaluate AI technologies, communicate and collaborate effectively with AI, and use AI as a tool (Long and Magerko 2020). Yang and colleagues (2025), in a comparative analysis of 41 AI literacy policies across the European Union, the United States, India, and China, find convergent strategies — all four jurisdictions are expanding AI and STEM programs in higher education — alongside significant divergences that reflect different labor market conditions and strategic priorities.	人工智能系统在教育和工作场所的快速部署产生了对AI素养的并行需求——批判性评估AI技术、与AI有效沟通和协作以及将AI作为工具使用的能力（Long和Magerko 2020）。Yang等人（2025）在对欧盟、美国、印度和中国41项AI素养政策的比较分析中发现了趋同的策略——四个辖区都在扩大高等教育中的AI和STEM项目——同时也存在反映不同劳动力市场条件和战略优先事项的显著分歧。
The EU AI Act (Regulation 2024/1689) introduced a specific AI literacy obligation. Article 4, which took effect on 2 February 2025, mandates that providers and deployers of AI systems „shall take measures to ensure, to their best extent, a sufficient level of AI literacy of their staff“ (European Parliament and Council 2024). This provision applies directly to universities deploying AI tools for teaching, assessment, or administration, creating a legal obligation for AI literacy training that has no direct equivalent in Chinese law.	欧盟《人工智能法》（第2024/1689号条例）引入了特定的人工智能素养义务。第4条于2025年2月2日生效，要求人工智能系统的提供者和部署者"采取措施，尽最大努力确保其工作人员具备足够的人工智能素养水平"（欧洲议会和理事会 2024）。这一条款直接适用于部署AI工具用于教学、评估或管理的大学，为AI素养培训创造了在中国法律中没有直接对应条款的法律义务。
China‘s approach integrates AI literacy into its broader digital literacy campaigns and, from September 2025, into mandatory AI education in all primary and secondary schools. The 2025 Plan for Enhancing National Digital Literacy and Skills explicitly addresses AI application and governance as a priority area. Hilliard and colleagues (2026), in a comparative analysis of AI policies across eight jurisdictions, document China’s distinctive approach: sector-specific regulation combined with centralized deployment of AI education at scale.	中国的方法将AI素养整合到更广泛的数字素养运动中，并从2025年9月起纳入所有中小学的强制性AI教育。《2025年提升全民数字素养与技能行动计划》明确将AI应用与治理列为优先领域。Hilliard等人（2026）在对八个辖区AI政策的比较分析中，记录了中国的独特方法：行业特定监管与大规模集中部署AI教育相结合。
3.2 Empirical Findings	3.2 实证发现
Empirical studies reveal significant variation in AI literacy across national contexts. Hornberger and colleagues (2025), in a multinational assessment of 1,465 university students across Germany, the United Kingdom, and the United States, find that German students demonstrate higher AI literacy, UK students hold more negative attitudes toward AI, and US students report greater AI self-efficacy. These differences persist even after controlling for demographic variables, suggesting that national educational and cultural contexts shape AI literacy in ways that generic frameworks do not capture.	实证研究揭示了不同国家背景下AI素养的显著差异。Hornberger等人（2025）对德国、英国和美国1,465名大学生的多国评估发现，德国学生展示了更高的AI素养，英国学生对AI持有更消极的态度，美国学生报告了更大的AI自我效能感。这些差异在控制人口统计学变量后仍然存在，表明国家教育和文化背景以通用框架无法捕捉的方式影响着AI素养。
In the Chinese context, Pan and Wang (2025) present a latent profile analysis of 782 Chinese EFL teachers that identifies four distinct AI literacy profiles: poor AI literacy (12.1 percent), moderate (45.5 percent), good (28.4 percent), and excellent (14.1 percent). Age and teaching experience significantly predict profile membership, with younger teachers generally demonstrating higher AI literacy but not uniformly so. The finding that nearly 58 percent of teachers fall in the poor or moderate categories has significant implications for AI literacy education: if teachers themselves lack AI competence, their capacity to develop it in students is necessarily limited.	在中国背景下，Pan和Wang（2025）对782名中国EFL教师的潜在类别分析确定了四种不同的AI素养类别：差（12.1%）、中等（45.5%）、良好（28.4%）和优秀（14.1%）。年龄和教学经验是类别归属的显著预测因素，年轻教师通常展示更高的AI素养，但并非普遍如此。近58%的教师属于差或中等类别的发现对AI素养教育具有重大意义：如果教师自身缺乏AI能力，他们在学生中培养这种能力的能力必然受限。
Zhang, Ganapathy Prasad, and Schroeder (2025), in a systematic review of reviews on AI literacy, synthesize the rapidly growing field and identify a persistent gap between policy ambitions and educational practice. The review confirms that AI literacy education remains in its early stages in both European and Chinese universities, with most initiatives focused on awareness rather than critical evaluation or practical competence.	Zhang、Ganapathy Prasad和Schroeder（2025）在对AI素养综述的系统综述中，综合了这一快速增长的领域，并指出政策雄心与教育实践之间存在持续差距。该综述确认，在欧洲和中国的大学中，AI素养教育仍处于早期阶段，大多数举措聚焦于意识层面而非批判性评估或实践能力。
The foundational work of Long and Magerko (2020) provides a conceptual framework for addressing this gap. Their definition of AI literacy — „a set of competencies that enables individuals to critically evaluate AI technologies; communicate and collaborate effectively with AI; and use AI as a tool“ — identifies 17 competencies across five themes. This framework has been widely adopted but not yet systematically implemented in either European or Chinese curricula. The gap between framework availability and educational practice is a recurring theme across both jurisdictions: sophisticated competence descriptions exist on paper, but translation into classroom practice remains the fundamental challenge.	Long和Magerko（2020）的基础性工作为弥合这一差距提供了概念框架。他们对AI素养的定义——"使个人能够批判性评估AI技术、与AI有效沟通和协作以及将AI作为工具使用的一组能力"——确定了五个主题下的17项能力。该框架已被广泛采用，但尚未在欧洲或中国的课程中系统实施。框架可用性与教育实践之间的差距是两个辖区反复出现的主题：精细的能力描述在纸面上已经存在，但转化为课堂实践仍是根本性挑战。
The cross-national variations documented in these studies have important implications for the design of international educational programs. A joint EU-China degree program cannot assume that students from both contexts arrive with equivalent digital and AI competences. German students’ higher AI literacy (Hornberger et al. 2025) and Chinese teachers’ AI literacy deficits (Pan and Wang 2025) suggest that international programs must diagnose and address digital competence asymmetries as a prerequisite for effective collaboration — a finding that connects directly to the data protection and ethical challenges discussed in the companion chapters of this anthology (Woesler, this volume).	这些研究中记录的跨国差异对国际教育项目的设计具有重要意义。一个欧中联合学位项目不能假设来自两种背景的学生具有同等的数字和AI能力。德国学生更高的AI素养（Hornberger等人 2025）和中国教师的AI素养不足（Pan和Wang 2025）表明，国际项目必须将诊断和弥合数字能力的不对称作为有效合作的前提——这一发现直接关联到本论文集相关章节中讨论的数据保护和伦理挑战（Woesler，本卷）。
4. The Digital Divide	4. 数字鸿沟
4.1 China: The Urban-Rural Gap	4.1 中国：城乡差距
China‘s digital divide is primarily geographic. The 55th Statistical Report on China’s Internet Development, published by the China Internet Network Information Center (CNNIC) in 2025, reports 1.099 billion internet users as of December 2024, representing a national penetration rate of 79.0 percent. However, rural internet penetration stands at 69.5 percent, nearly ten percentage points below the national average, and urban users constitute 71.3 percent of total internet users (CNNIC 2025).	中国的数字鸿沟主要是地理性的。中国互联网络信息中心（CNNIC）2025年发布的第55次《中国互联网络发展状况统计报告》显示，截至2024年12月，中国网民规模达10.99亿，全国互联网普及率为79.0%。然而，农村互联网普及率为69.5%，低于全国平均水平近十个百分点，城市用户占网民总数的71.3%（CNNIC 2025）。
The infrastructure achievements are nonetheless remarkable. With 99.9 percent of schools connected to broadband and the National Smart Education Platform serving 293 million students, the physical prerequisites for digital education are largely in place (Ma 2025). The challenge has shifted from access to quality: ensuring that rural students receive the same quality of digital education as their urban counterparts, despite differences in teacher competence, institutional resources, and cultural capital.	基础设施成就尽管如此仍然令人瞩目。99.9%的学校连通宽带、国家智慧教育平台服务2.93亿学生，数字教育的物理前提条件基本到位（Ma 2025）。挑战已从接入转向质量：确保农村学生获得与城市同龄人同等质量的数字教育，尽管在教师能力、机构资源和文化资本方面存在差异。
The Regulations on the Protection of Minors in Cyberspace, effective 1 January 2024, add a regulatory dimension to the digital divide. The regulations require mandatory internet addiction prevention measures, „minor modes“ on platforms, and screen time limits — provisions that reflect Chinese policymakers’ awareness that digital access without digital literacy and parental oversight can produce harm rather than benefit (State Council 2023). Zheng and colleagues (2025), in a comprehensive meta-analysis of 164 epidemiological studies involving 737,384 Chinese adolescents, find a pooled internet addiction prevalence of 10.3 percent, with rural adolescents showing higher rates — a finding that underscores the need for digital literacy education that addresses risks as well as opportunities.	2024年1月1日生效的《未成年人网络保护条例》为数字鸿沟增添了监管维度。该条例要求强制实施网络成瘾预防措施、平台"未成年人模式"和屏幕时间限制——这些规定反映了中国政策制定者的认识：没有数字素养和家长监督的数字接入可能产生危害而非收益（国务院 2023）。Zheng等人（2025）在涵盖737,384名中国青少年的164项流行病学研究的综合荟萃分析中发现，互联网成瘾的合并患病率为10.3%，农村青少年比率更高——这一发现强调了数字素养教育需要同时应对风险和机遇。
4.2 Europe: Socioeconomic and Inter-State Variation	4.2 欧洲：社会经济和成员国间差异
The European digital divide operates along different axes: socioeconomic status, educational attainment, age, and — critically — member state. The European Commission’s State of the Digital Decade 2025 report documents that only 55.6 percent of the EU population possesses at least basic digital skills, far short of the 80 percent target for 2030. At the current pace of progress, the target will not be met. The Netherlands (83 percent) and Finland (82 percent) lead in basic digital skills, while Romania (28 percent) and Bulgaria (36 percent) lag far behind (European Commission 2025; Eurofound 2025).	欧洲数字鸿沟沿不同轴线运作：社会经济地位、教育程度、年龄以及——关键的——成员国。欧盟委员会《2025年数字十年状况》报告记录，仅55.6%的欧盟人口拥有至少基本数字技能，远低于2030年80%的目标。按当前的进展速度，该目标将无法实现。荷兰（83%）和芬兰（82%）在基本数字技能方面领先，而罗马尼亚（28%）和保加利亚（36%）大幅落后（European Commission 2025；Eurofound 2025）。
Eurofound’s 2025 report on the digital divide documents that historically lower-performing member states have been catching up with digital leaders, but significant inequalities persist. Vulnerable groups — low-income, older, less educated populations — remain disproportionately affected. The digital divide in Europe is thus not primarily a generational divide but a socioeconomic one, further undermining the digital native assumption that age cohort is the primary determinant of digital competence.	Eurofound的2025年数字鸿沟报告记录，历史上表现较弱的成员国正在追赶数字化领先者，但显著的不平等仍然存在。弱势群体——低收入、老年、受教育程度较低的人群——受到不成比例的影响。因此，欧洲的数字鸿沟主要不是代际鸿沟，而是社会经济鸿沟，这进一步削弱了年龄群体是数字能力首要决定因素的数字原住民假设。
PISA 2022 data provide an educational lens on the divide. Students spending up to one hour per day on digital devices for learning scored 14 points higher in mathematics, but students distracted by others’ device use scored 15 points lower. Only 60 percent of students expressed confidence in their ability to manage their own motivation for digital schoolwork (OECD 2023). These findings suggest that the relationship between digital technology and educational outcomes is mediated by context, pedagogy, and self-regulation — not by generational membership.	PISA 2022数据从教育视角展示了这一鸿沟。每天用数字设备学习不超过一小时的学生在数学成绩上高出14分，但经常被他人设备使用所干扰的学生则低15分。只有60%的学生表示对自己管理数字学习动力的能力有信心（OECD 2023）。这些发现表明，数字技术与教育结果之间的关系受到情境、教学法和自我调节的中介——而非代际成员身份。
5. Screen Time, Digital Habits, and Platform Ecosystems	5. 屏幕时间、数字习惯与平台生态系统
The digital environments inhabited by young people in China and Europe differ not only in scale but in kind. Chinese youth primarily use WeChat (95.76 percent), QQ (72.25 percent), Douyin (65.57 percent), and Little Red Book (Xiaohongshu, 36.50 percent). Zhao, Wang, and Hu (2025) document a pattern of „platform-swinging“ — spontaneous movement between platforms driven by peer resonance, self-management needs, and content discovery — that challenges the assumption of stable digital identities.	中国和欧洲年轻人所处的数字环境不仅在规模上而且在性质上存在差异。中国青年主要使用微信（95.76%）、QQ（72.25%）、抖音（65.57%）和小红书（36.50%）。Zhao、Wang和Hu（2025）记录了一种"平台漂移"模式——由同伴共鸣、自我管理需求和内容发现驱动的在不同平台之间的自发迁移——这挑战了对稳定数字身份的假设。
European youth inhabit a different platform ecosystem. The Flash Eurobarometer Youth Survey 2024, covering 25,933 young EU citizens aged 16–30 across 27 member states, finds that social media platforms (42 percent) are the most commonly used sources of news among young Europeans (European Parliament 2025). The platform landscape is more fragmented than in China, with Instagram, TikTok, YouTube, and Snapchat competing for attention alongside nationally specific platforms.	欧洲青年栖息在不同的平台生态系统中。《2024年Flash Eurobarometer青年调查》覆盖了27个成员国25,933名16–30岁的年轻欧盟公民，发现社交媒体平台（42%）是年轻欧洲人最常使用的新闻来源（European Parliament 2025）。平台格局比中国更为碎片化，Instagram、TikTok、YouTube和Snapchat与各国特有平台竞相争夺注意力。
Livingstone, Mascheroni, and Stoilova (2023), in a systematic evidence review of digital skills outcomes for young people aged 12–17, find a double-edged relationship: greater digital skills are positively associated with online opportunities and information benefits, but they also correlate with greater exposure to online risks. This finding has important implications for digital literacy education in both contexts: the goal cannot be simply to increase digital skills but to develop the critical judgment needed to navigate digital environments safely and productively.	Livingstone、Mascheroni和Stoilova（2023）在对12–17岁青少年数字技能成果的系统性证据综述中发现了双重关系：更高的数字技能与在线机会和信息利益正相关，但也与更大的在线风险暴露相关。这一发现对两种情境下的数字素养教育具有重要意义：目标不能仅仅是提高数字技能，而必须培养安全且高效地驾驭数字环境所需的批判性判断力。
The mental health implications of intensive digital engagement are increasingly documented. Research on short-video platforms such as Douyin and TikTok reveals themes of anxiety, sleep disruption, digital addiction, and body image concerns across Chinese, American, and British contexts. The scale of concern in China is quantified by Zheng and colleagues’ (2025) meta-analysis: 10.3 percent internet addiction prevalence among adolescents, with rural youth disproportionately affected. China’s regulatory response — the mandatory „minor modes“ and screen time limits introduced in the Regulations on the Protection of Minors in Cyberspace (effective January 2024) — represents a more interventionist approach than the EU’s reliance on digital literacy education and platform self-regulation (State Council 2023).	密集数字参与的心理健康影响日益受到记录。对抖音和TikTok等短视频平台的研究在中国、美国和英国的背景下都揭示了焦虑、睡眠障碍、数字成瘾和身体形象担忧等主题。中国的担忧规模通过Zheng等人（2025）的荟萃分析得到量化：青少年互联网成瘾患病率为10.3%，农村青少年受影响不成比例。中国的监管应对——《未成年人网络保护条例》（2024年1月生效）中的强制"未成年人模式"和屏幕时间限制——代表了比欧盟依赖数字素养教育和平台自律更具干预性的方法（国务院 2023）。
The PISA 2022 findings add nuance to the screen time debate. Students who spent up to one hour per day on digital devices for learning scored 14 points higher in mathematics than those who did not, but students frequently distracted by others’ device use scored 15 points lower. Only 60 percent of students expressed confidence in their self-motivation for digital schoolwork (OECD 2023). These data suggest that the relationship between screen time and educational outcomes is not linear but mediated by the quality and purpose of engagement — a finding that argues for pedagogical guidance rather than simple time restrictions.	PISA 2022的发现为屏幕时间讨论增添了细微差别。每天用数字设备学习不超过一小时的学生数学成绩高出14分，但经常被他人设备使用干扰的学生则低15分。只有60%的学生对自己在数字学习中的自我激励表示有信心（OECD 2023）。这些数据表明，屏幕时间与教育结果之间的关系不是线性的，而是受到参与质量和目的的中介——这一发现支持教学指导而非简单的时间限制。
The platform ecosystems themselves differ in ways that shape digital literacy demands. Chinese platforms operate within a regulated ecosystem where content moderation, algorithmic recommendation, and data collection are governed by a combination of the Cyberspace Administration of China, platform-specific regulations, and the PIPL. European users navigate a more fragmented ecosystem where the Digital Services Act, the GDPR, and national regulations create a patchwork of protections. Students in both contexts need the critical capacity to understand how algorithmic recommendation shapes their information environment — a competence that neither DigComp 2.2 nor China’s digital literacy campaigns currently address with sufficient depth.	平台生态系统本身的差异影响着数字素养需求。中国平台在受监管的生态系统中运作，内容审核、算法推荐和数据收集由中央网信办、平台特定法规和《个人信息保护法》（PIPL）共同管控。欧洲用户在更碎片化的生态系统中导航，《数字服务法》、GDPR和各国法规构成了保护措施的拼接。两种情境下的学生都需要具备理解算法推荐如何塑造其信息环境的批判性能力——这是DigComp 2.2和中国数字素养运动目前都未充分深入涉及的一项能力。
6. Digital Competence and Innovation Capability	6. 数字能力与创新能力
A critical question for both European and Chinese policymakers is whether digital literacy translates into innovation capability — the ability to create new solutions, not merely to consume digital content. Zhou and colleagues (2025), in a study of 1,334 students at 12 universities in Ningbo, China, find a strong positive correlation between digital literacy and innovation capability (beta = 0.76, p < 0.001), with cognitive emotion and responsibility literacy showing the strongest associations (r = 0.72–0.73). These findings suggest that digital literacy is not merely a consumption skill but a foundation for the creative and critical thinking that both economies need.	中欧政策制定者面临的一个关键问题是，数字素养是否能转化为创新能力——创造新解决方案而非仅仅消费数字内容的能力。Zhou等人（2025）在对宁波12所大学1,334名学生的研究中发现，数字素养与创新能力之间存在强正相关（β = 0.76, p < 0.001），其中认知情感和责任素养显示出最强的关联（r = 0.72–0.73）。这些发现表明，数字素养不仅仅是一种消费技能，而是两个经济体都需要的创造性和批判性思维的基础。
Wu’s (2024) Digital Literacy Framework for Chinese College Students, structured as a progressive „Skills–Competencies–Awareness“ relationship, offers a complementary perspective. The framework identifies 15 descriptors validated through empirical research, reflecting a growing recognition in Chinese educational research that mere access to technology does not translate into innovation capacity. The framework’s emphasis on „awareness“ as the highest level of digital literacy — beyond skills and competences — resonates with the European DigComp framework’s attention to attitudes and values alongside knowledge and skills.	Wu（2024）的中国大学生数字素养框架，结构为渐进式的"技能—能力—意识"关系，提供了互补的视角。该框架确定了经实证研究验证的15项描述指标，反映了中国教育研究界日益增长的认识：仅有技术接入并不能转化为创新能力。该框架将"意识"定位为数字素养的最高层次——超越技能和能力——与欧洲DigComp框架对知识和技能之外的态度和价值观的关注相呼应。
However, the EU Education and Training Monitor 2024 presents a more sobering picture for Europe. Only 42 percent of young Europeans report having had a good opportunity to learn about sustainability in school — a proxy for the kind of structured, interdisciplinary learning that connects digital competence to real-world challenges. While 84 percent of young people believe in the value of environmental change, only 30 percent act on sustainability daily. Over 40 percent of 13- and 14-year-olds lack basic digital skills (European Commission 2024). The gap between belief and action, and between access and competence, mirrors the broader digital native myth: being surrounded by technology does not automatically produce the ability — or the inclination — to use it productively.	然而，欧盟《2024年教育与培训监测》为欧洲呈现了一幅更令人清醒的图景。仅42%的年轻欧洲人表示曾在学校获得过关于可持续发展的良好学习机会——这是将数字能力与现实挑战相结合的结构化、跨学科学习的一个代理指标。虽然84%的年轻人相信环境改变的价值，但只有30%在日常生活中践行可持续行为。超过40%的13至14岁青少年缺乏基本数字技能（European Commission 2024）。信念与行动之间、接入与能力之间的差距，映射了更广泛的数字原住民神话：被技术包围并不自动产生有效——或有意愿——使用技术的能力。
Roh, Yoo, and Ok (2025), in a cross-national text mining analysis of national curriculum standards using the DigComp framework, find that „information and data literacy“ and „communication and collaboration“ are the most emphasized digital competences across compared nations, but digital literacy keywords have low centrality in curricula overall. This finding suggests that even when digital literacy is nominally part of the curriculum, it often remains peripheral to the core educational mission — a problem that will only intensify as AI becomes more central to both education and employment.	Roh、Yoo和Ok（2025）在使用DigComp框架对国家课程标准进行跨国文本挖掘分析中发现，"信息与数据素养"和"沟通与协作"是被比较国家中最受强调的数字能力，但数字素养关键词在课程中的整体中心度较低。这一发现表明，即使数字素养名义上是课程的一部分，它往往仍处于核心教育使命的边缘——这一问题只会随着AI在教育和就业中变得更加核心而加剧。
7. Implications for Curriculum Design	7. 对课程设计的启示
The evidence reviewed in this article points to several implications for curriculum design in both European and Chinese universities.	本文审阅的证据为中欧大学的课程设计指明了若干方向。
First, digital literacy education must be structured and explicit, not assumed. The digital native myth’s most pernicious legacy is the assumption that young people arrive at university already digitally competent. The empirical evidence — 55.6 percent basic digital skills in the EU, 12.1 percent of Chinese EFL teachers with poor AI literacy, over 40 percent of European young teenagers lacking basic digital skills — refutes this assumption decisively. Universities must provide systematic digital literacy education as part of the core curriculum, not as an optional supplement.	第一，数字素养教育必须是结构化和明确的，而非假定的。数字原住民神话最有害的遗产是认为年轻人到达大学时已经具备数字能力的假设。实证证据——欧盟55.6%的基本数字技能率、12.1%的中国EFL教师AI素养差、超过40%的欧洲青少年缺乏基本数字技能——决定性地反驳了这一假设。大学必须将系统性的数字素养教育纳入核心课程，而非作为可选补充。
Second, AI literacy requires specific pedagogical attention. The EU AI Act‘s Article 4 mandate for AI literacy among AI system deployers applies directly to universities. The finding that German, British, and American students differ significantly in AI literacy (Hornberger et al. 2025) suggests that national educational contexts matter, and that generic AI literacy frameworks must be adapted to local conditions. China‘s decision to mandate AI education from September 2025 represents a more direct approach, but its effectiveness will depend on teacher competence — a concern highlighted by Pan and Wang’s (2025) finding that 57.6 percent of Chinese EFL teachers have poor or moderate AI literacy.	第二，人工智能素养需要特定的教学关注。欧盟《人工智能法》第4条关于AI系统部署者AI素养的要求直接适用于大学。德国、英国和美国学生在AI素养方面存在显著差异的发现（Hornberger等人 2025）表明，国家教育背景至关重要，通用的AI素养框架必须根据当地条件加以调整。中国从2025年9月起强制实施AI教育的决定代表了一种更为直接的方法，但其有效性将取决于教师的能力——Pan和Wang（2025）关于57.6%的中国EFL教师AI素养处于差或中等水平的发现凸显了这一关切。
Third, digital literacy education must address risks as well as opportunities. Livingstone, Mascheroni, and Stoilova’s (2023) finding that greater digital skills correlate with greater exposure to online risks, and Zheng and colleagues’ (2025) documentation of 10.3 percent internet addiction prevalence among Chinese adolescents, underscore the need for digital literacy curricula that develop critical judgment, self-regulation, and awareness of digital wellbeing — competences that neither the DigComp framework nor China‘s infrastructure-focused approach currently emphasizes sufficiently.	第三，数字素养教育必须同时关注风险和机遇。Livingstone、Mascheroni和Stoilova（2023）关于更高数字技能与更大在线风险暴露相关的发现，以及Zheng等人（2025）关于中国青少年10.3%互联网成瘾患病率的记录，强调了数字素养课程需要培养批判性判断力、自我调节能力和数字健康意识——这些是DigComp框架和中国以基础设施为重点的方法目前都未充分强调的能力。
Fourth, the digital divide must be addressed as a socioeconomic and geographic challenge, not a generational one. Both the EU’s inter-state variation (55 percentage points between the Netherlands and Romania in basic digital skills) and China‘s urban-rural gap (nearly ten percentage points in internet penetration) demand targeted interventions that go beyond universal frameworks. Curriculum design must account for the reality that students arrive with vastly different levels of digital access, competence, and cultural capital.	第四，数字鸿沟必须作为社会经济和地理挑战而非代际挑战来应对。欧盟成员国间的差异（荷兰与罗马尼亚在基本数字技能方面相差55个百分点）和中国的城乡差距（互联网普及率相差近十个百分点）都需要有针对性的干预措施，这些干预措施超越了普遍性框架。课程设计必须考虑到学生在数字接入、能力和文化资本方面存在巨大差异的现实。
Fifth, digital literacy frameworks must evolve to address the algorithmic dimension of digital life. Current frameworks — including DigComp 2.2 — emphasize information literacy, communication, and content creation but give insufficient attention to algorithmic literacy: the capacity to understand how recommendation systems, content moderation algorithms, and AI-driven personalization shape the information environment. As students in both China and Europe spend increasing proportions of their time in algorithmically mediated environments, this competence becomes essential for informed citizenship.	第五，数字素养框架必须发展以应对数字生活的算法维度。当前的框架——包括DigComp 2.2——强调信息素养、沟通和内容创建，但对算法素养的关注不足：理解推荐系统、内容审核算法和AI驱动的个性化如何塑造信息环境的能力。随着中国和欧洲的学生在算法中介环境中花费越来越多的时间，这种能力对于知情公民身份变得至关重要。
Sixth, cross-cultural digital literacy education must resist the temptation to treat one system as the standard against which others are measured. Roh, Yoo, and Ok’s (2025) cross-national analysis of curriculum standards using DigComp as the analytical framework illustrates both the utility and the limitations of this approach: the framework provides a common vocabulary for comparison, but the low centrality of digital literacy keywords in curricula across all compared nations suggests that the challenge is not framework design but implementation — a challenge that both Europe and China share, despite their different institutional contexts.	第六，跨文化数字素养教育必须抵制将一个体系作为衡量其他体系标准的诱惑。Roh、Yoo和Ok（2025）使用DigComp作为分析框架的跨国课程标准分析说明了这种方法的效用和局限：该框架提供了比较的共同词汇，但数字素养关键词在所有被比较国家的课程中整体中心度较低，表明挑战不在于框架设计而在于实施——这是欧洲和中国尽管制度背景不同但共同面临的挑战。
8. Conclusion	8. 结论
The digital native is a myth that has outlived its usefulness. Twenty-five years after Prensky’s original essay, the empirical evidence is unambiguous: growing up with technology does not produce digital competence. Digital literacy, like any other form of literacy, must be taught, practiced, and assessed. AI literacy adds a new dimension to this challenge, requiring not merely the ability to use AI tools but the critical capacity to evaluate their outputs, understand their limitations, and navigate their ethical implications.	数字原住民是一个已经过了其有用期的神话。在Prensky原始论文发表二十五年后，实证证据是明确无误的：在技术中成长并不产生数字能力。数字素养如同任何其他形式的素养一样，必须被教授、练习和评估。人工智能素养为这一挑战增添了新维度，不仅要求使用AI工具的能力，还要求批判性评估其输出、理解其局限性以及驾驭其伦理含义的能力。
The comparison of European and Chinese approaches reveals complementary strengths and weaknesses. The EU’s framework-based approach — DigComp 2.2 with its 250+ competence examples, the Digital Education Action Plan, the AI Act’s literacy mandate — provides conceptual clarity and individual rights protection but struggles with implementation: 55.6 percent basic digital skills against an 80 percent target tells its own story. China‘s centralized, infrastructure-led approach achieves remarkable deployment speed — 99.9 percent school broadband, 293 million students on a single platform, mandatory AI education within two years of policy announcement — but faces challenges in teacher competence, urban-rural equity, and the gap between access and critical use.	欧中方法的比较揭示了互补的优势和弱点。欧盟基于框架的方法——DigComp 2.2及其250多个能力示例、数字教育行动计划、《人工智能法》的素养要求——提供了概念清晰度和个人权利保护，但在实施方面面临困境：55.6%的基本数字技能率相对于80%的目标不言自明。中国集中化的、基础设施主导的方法实现了惊人的部署速度——99.9%的学校宽带覆盖、2.93亿学生在单一平台上、政策宣布两年内即实施强制AI教育——但在教师能力、城乡公平以及接入与批判性使用之间的差距方面面临挑战。
The implications extend beyond education policy to questions of democratic citizenship and social cohesion. In Europe, where the Flash Eurobarometer Youth Survey 2024 finds that 42 percent of young people use social media as their primary news source (European Parliament 2025), the capacity to critically evaluate algorithmically curated information is not merely an educational desideratum but a democratic necessity. In China, where the state plays a more active role in content curation, digital literacy includes the capacity to navigate between domestic and global information ecosystems — a skill that Yang and colleagues’ (2025) comparative analysis of AI literacy policies suggests is receiving increasing policy attention.	这些启示超越教育政策延伸到民主公民身份和社会凝聚力的问题。在欧洲，《2024年Flash Eurobarometer青年调查》发现42%的年轻人将社交媒体作为主要新闻来源（European Parliament 2025），批判性评估算法策展信息的能力不仅是一项教育期望，更是民主的必需。在中国，国家在内容策展中发挥更积极作用的背景下，数字素养包含在国内和全球信息生态系统之间导航的能力——Yang等人（2025）的AI素养政策比较分析表明，这一技能正日益受到政策关注。
Neither approach has solved the fundamental problem that the digital native myth was supposed to address: how to prepare young people for a world in which digital technology is ubiquitous but digital competence is unevenly distributed. We argue that the most promising path forward combines European rigor in competence definition and assessment with Chinese speed in deployment and scaling — a synthesis that is easier to propose than to achieve, but that both systems are, in their different ways, beginning to explore. The companion chapters in this anthology on AI ethics (Woesler, this volume), data protection (Woesler, this volume), and the university of the future (Woesler, this volume) address the institutional, regulatory, and pedagogical dimensions of this challenge.	两种方法都未解决数字原住民神话本应解决的根本问题：如何让年轻人为一个数字技术无处不在但数字能力分布不均的世界做好准备。我们认为，最有前景的前进道路将欧洲在能力定义和评估方面的严谨性与中国在部署和规模化方面的速度相结合——这种综合提出容易但实现不易，不过两个体系正以各自的方式开始探索。本论文集关于AI伦理（Woesler，本卷）、数据保护（Woesler，本卷）和未来大学（Woesler，本卷）的相关章节分别从制度、监管和教学维度探讨了这一挑战。
Acknowledgments	致谢
This research was conducted within the framework of the Jean Monnet Centre of Excellence „EUSC-DEC“ (EU Grant 101126782, 2023–2026). The author thanks the members of Research Group 4 (Cross-Cultural Perspectives on Digital Education) for their contributions to the comparative analysis.	本研究在让·莫内卓越中心"EUSC-DEC"（欧盟资助 101126782，2023–2026年）框架内进行。作者感谢第四研究组（跨文化数字教育视角）成员对比较分析的贡献。
References	参考文献
Bennett, S., Maton, K. & Kervin, L. (2008). The ‘digital natives’ debate: A critical review of the evidence. British Journal of Educational Technology, 39(5), 775–786. DOI: 10.1111/j.1467-8535.2007.00793.x	Bennett, S., Maton, K. & Kervin, L. (2008). The 'digital natives' debate: A critical review of the evidence. British Journal of Educational Technology, 39(5), 775–786.
Central Cyberspace Affairs Commission, Ministry of Education, MIIT & MOHRSS. (2025). 2025 Plan for Enhancing National Digital Literacy and Skills. Beijing.	Central Cyberspace Affairs Commission, Ministry of Education, MIIT & MOHRSS. (2025). 2025 Plan for Enhancing National Digital Literacy and Skills. Beijing.
China Internet Network Information Center (CNNIC). (2025). The 55th Statistical Report on China’s Internet Development. Beijing: CNNIC.	China Internet Network Information Center (CNNIC). (2025). The 55th Statistical Report on China's Internet Development. Beijing: CNNIC.
Eurofound. (2025). Narrowing the digital divide: Economic and social convergence in Europe’s digital transformation. Publications Office of the European Union, Luxembourg.	Eurofound. (2025). Narrowing the digital divide: Economic and social convergence in Europe's digital transformation. Publications Office of the European Union, Luxembourg.
European Commission. (2020). Digital Education Action Plan 2021–2027: Resetting education and training for the digital age. COM(2020) 624 final, 30 September 2020.	European Commission. (2020). Digital Education Action Plan 2021–2027: Resetting education and training for the digital age. COM(2020) 624 final, 30 September 2020.
European Commission. (2024). Education and Training Monitor 2024. Publications Office of the European Union.	European Commission. (2024). Education and Training Monitor 2024. Publications Office of the European Union.
European Commission. (2025). State of the Digital Decade 2025. COM(2025) 262 final.	European Commission. (2025). State of the Digital Decade 2025. COM(2025) 262 final.
European Parliament. (2025). Flash Eurobarometer 556: Youth Survey 2024. February 2025.	European Parliament. (2025). Flash Eurobarometer 556: Youth Survey 2024. February 2025.
European Parliament and Council. (2024). Regulation (EU) 2024/1689 of 13 June 2024 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Official Journal of the European Union, L series.	European Parliament and Council. (2024). Regulation (EU) 2024/1689 of 13 June 2024 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Official Journal of the European Union, L series.
Hilliard, A., Gulley, A., Kazim, E. & Koshiyama, A. S. (2026). Artificial intelligence policy worldwide: a comparative analysis. Royal Society Open Science, 13(2), 242234. DOI: 10.1098/rsos.242234	Hilliard, A., Gulley, A., Kazim, E. & Koshiyama, A. S. (2026). Artificial intelligence policy worldwide: a comparative analysis. Royal Society Open Science, 13(2), 242234.
Hornberger, M., Bewersdorff, A., Schiff, D. S. & Nerdel, C. (2025). A multinational assessment of AI literacy among university students in Germany, the UK, and the US. Computers in Human Behavior: Artificial Humans, 4, 100132. DOI: 10.1016/j.chbah.2025.100132	Hornberger, M., Bewersdorff, A., Schiff, D. S. & Nerdel, C. (2025). A multinational assessment of AI literacy among university students in Germany, the UK, and the US. Computers in Human Behavior: Artificial Humans, 4, 100132.
Livingstone, S., Mascheroni, G. & Stoilova, M. (2023). The outcomes of gaining digital skills for young people’s lives and wellbeing: A systematic evidence review. New Media and Society, 25(5), 1176–1202. DOI: 10.1177/14614448211043189	Livingstone, S., Mascheroni, G. & Stoilova, M. (2023). The outcomes of gaining digital skills for young people's lives and wellbeing: A systematic evidence review. New Media and Society, 25(5), 1176–1202.
Long, D. & Magerko, B. (2020). What is AI Literacy? Competencies and Design Considerations. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–16). ACM. DOI: 10.1145/3313831.3376727	Long, D. & Magerko, B. (2020). What is AI Literacy? Competencies and Design Considerations. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–16). ACM.
Ma, C. (2025). China‘s Achievements in Digital Education in the Wake of Education Informatization 2.0 Action Plan. Science Insights Education Frontiers, 27(1), 4435–4451. DOI: 10.15354/sief.25.re488	Ma, C. (2025). China's Achievements in Digital Education in the Wake of Education Informatization 2.0 Action Plan. Science Insights Education Frontiers, 27(1), 4435–4451.
Mertala, P., Lopez-Pernas, S., Vartiainen, H., Saqr, M. & Tedre, M. (2024). Digital natives in the scientific literature: A topic modeling approach. Computers in Human Behavior, 152, 108076. DOI: 10.1016/j.chb.2023.108076	Mertala, P., Lopez-Pernas, S., Vartiainen, H., Saqr, M. & Tedre, M. (2024). Digital natives in the scientific literature: A topic modeling approach. Computers in Human Behavior, 152, 108076.
OECD. (2023). PISA 2022 Results (Volume I): The State of Learning and Equity in Education. PISA, OECD Publishing, Paris. DOI: 10.1787/53f23881-en	OECD. (2023). PISA 2022 Results (Volume I): The State of Learning and Equity in Education. PISA, OECD Publishing, Paris.
Pan, Z. & Wang, Y. (2025). From Technology-Challenged Teachers to Empowered Digitalized Citizens: Exploring the Profiles and Antecedents of Teacher AI Literacy in the Chinese EFL Context. European Journal of Education, 60(1), e70020. DOI: 10.1111/ejed.70020	Pan, Z. & Wang, Y. (2025). From Technology-Challenged Teachers to Empowered Digitalized Citizens: Exploring the Profiles and Antecedents of Teacher AI Literacy in the Chinese EFL Context. European Journal of Education, 60(1), e70020.
Prensky, M. (2001). Digital Natives, Digital Immigrants, Part 1. On the Horizon, 9(5), 1–6. DOI: 10.1108/10748120110424816	Prensky, M. (2001). Digital Natives, Digital Immigrants, Part 1. On the Horizon, 9(5), 1–6.
Reid, L., Button, D. & Brommeyer, M. (2023). Challenging the Myth of the Digital Native: A Narrative Review. Nursing Reports, 13(2), 573–600. DOI: 10.3390/nursrep13020052	Reid, L., Button, D. & Brommeyer, M. (2023). Challenging the Myth of the Digital Native: A Narrative Review. Nursing Reports, 13(2), 573–600.
Roh, D., Yoo, J. & Ok, H. (2025). Mapping digital literacy in language education: A comparative analysis of national curriculum standards using text as data approach. Education and Information Technologies, 30, 6287–6313. DOI: 10.1007/s10639-024-13056-5	Roh, D., Yoo, J. & Ok, H. (2025). Mapping digital literacy in language education: A comparative analysis of national curriculum standards using text as data approach. Education and Information Technologies, 30, 6287–6313.
State Council of the People’s Republic of China. (2023). Regulations on the Protection of Minors in Cyberspace. Effective 1 January 2024.	State Council of the People's Republic of China. (2023). Regulations on the Protection of Minors in Cyberspace. Effective 1 January 2024.
Vuorikari, R., Kluzer, S. & Punie, Y. (2022). DigComp 2.2: The Digital Competence Framework for Citizens — With new examples of knowledge, skills and attitudes. EUR 31006 EN, Publications Office of the European Union, Luxembourg. DOI: 10.2760/115376	Vuorikari, R., Kluzer, S. & Punie, Y. (2022). DigComp 2.2: The Digital Competence Framework for Citizens — With new examples of knowledge, skills and attitudes. EUR 31006 EN, Publications Office of the European Union, Luxembourg.
Wang, C. & d’Haenens, L. (2025). Report-Based Interpretation of 2024 Digital Literacy and Skills in China and the EU. In: Communications in Computer and Information Science (CCIS, vol. 2537). Springer.	Wang, C. & d'Haenens, L. (2025). Report-Based Interpretation of 2024 Digital Literacy and Skills in China and the EU. In: Communications in Computer and Information Science (CCIS, vol. 2537). Springer.
Wu, D. (2024). Exploring digital literacy in the era of digital civilization: A framework for college students in China. Information Services and Use, 44(2), 69–91. DOI: 10.3233/ISU-230199	Wu, D. (2024). Exploring digital literacy in the era of digital civilization: A framework for college students in China. Information Services and Use, 44(2), 69–91.
Yan, S. & Yang, Y. (2021). Education Informatization 2.0 in China: Motivation, Framework, and Vision. ECNU Review of Education, 4(2), 291–302. DOI: 10.1177/2096531120944929	Yan, S. & Yang, Y. (2021). Education Informatization 2.0 in China: Motivation, Framework, and Vision. ECNU Review of Education, 4(2), 291–302.
Yang, H., Xu, J., Zeng, X. & Gu, X. (2025). Comparing AI literacy policies in the European Union, the United States, India, and China. Telecommunications Policy. DOI: 10.1016/j.telpol.2025.102939	Yang, H., Xu, J., Zeng, X. & Gu, X. (2025). Comparing AI literacy policies in the European Union, the United States, India, and China. Telecommunications Policy.
Zhang, S., Ganapathy Prasad, P. & Schroeder, N. L. (2025). Learning About AI: A Systematic Review of Reviews on AI Literacy. Journal of Educational Computing Research. DOI: 10.1177/07356331251342081	Zhang, S., Ganapathy Prasad, P. & Schroeder, N. L. (2025). Learning About AI: A Systematic Review of Reviews on AI Literacy. Journal of Educational Computing Research.
Zhao, H., Wang, J. & Hu, X. (2025). „A Wandering Existence“: Social Media Practices of Chinese Youth in the Context of Platform-Swinging. Social Media + Society, 11(1). DOI: 10.1177/20563051251315265	Zhao, H., Wang, J. & Hu, X. (2025). "A Wandering Existence": Social Media Practices of Chinese Youth in the Context of Platform-Swinging. Social Media + Society, 11(1).
Zheng, M.-R. et al. (2025). Prevalence of internet addiction among Chinese adolescents: A comprehensive meta-analysis of 164 epidemiological studies. Asian Journal of Psychiatry, 105, 104458. DOI: 10.1016/j.ajp.2025.104458	Zheng, M.-R. et al. (2025). Prevalence of internet addiction among Chinese adolescents: A comprehensive meta-analysis of 164 epidemiological studies. Asian Journal of Psychiatry, 105, 104458.
Zhou, Y., Sun, X., Zhu, Y., Feng, Z., Sun, Q. & Zhong, X. (2025). The impact of digital literacy on university students’ innovation capability: evidence from Ningbo, China. Frontiers in Psychology, 16, 1548817. DOI: 10.3389/fpsyg.2025.1548817	Zhou, Y., Sun, X., Zhu, Y., Feng, Z., Sun, Q. & Zhong, X. (2025). The impact of digital literacy on university students' innovation capability: evidence from Ningbo, China. Frontiers in Psychology, 16, 1548817.
Part IV: Future Directions	第四部分：未来方向