| 司莉,刘尧,郭思成.AI4S范式下科研人员AI素养框架构建与内容分析[J].中国图书馆学报,2026,52(4):81~103 |
| AI4S范式下科研人员AI素养框架构建与内容分析 |
| Construction and Content Analysis of an AI Literacy Framework for Researchers Under the AI4S Paradigm |
| 投稿时间：2026-02-25 修订日期：2026-05-20 |
| DOI： |
| 中文关键词: AI4S 科研人员 AI素养框架 科研生命周期 信息资源管理 |
| 英文关键词: AI4S Researchers AI literacy framework Research lifecycle Information resource management |
| 基金项目: |
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| 摘要点击次数: 162 |
| 全文下载次数: 119 |
| 中文摘要: |
构建AI4S范式下的科研人员AI素养框架,对适应科研数智化转型、科学测评与提升科研人员AI素养具有重要价值。本研究分析AI4S特征及其对科研人员能力的要求；运用扎根理论系统分析81份国内外相关文本,归纳AI素养框架的内容维度；根据科研启动、实施、传播与评价三个阶段匹配AI素养维度,并根据专家意见进行优化,构建了包含认知、思维、应用与伦理四个维度的科研人员AI素养框架。该框架包括基础认知、价值理解与批判性认知、数据思维、计算思维、AI使用、提示素养、AI创新、学术道德、隐私保护、公平包容、人本理念、知识产权、透明可信13个核心能力,在AI素养测评指标构建、AI素养水平评估与分级分类方案制定三个方面具有应用价值。图1。表5。参考文献63。
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| 英文摘要: |
Under the AI for Science（AI4S） paradigm,constructing an AI literacy framework for researchers is essential for adapting to the intelligent transformation of scientific research and for supporting the assessment and improvement of researchers AI literacy. In this study,we first analyze the characteristics of AI4S and the corresponding requirements for researchers. AI4S is characterized by human AI collaboration,integration and convergence,as well as controversy. These characteristics entail four competency requirements for researchers:foundational cognitive competence,data driven thinking,integrated application competence,and a sense of responsibility which leads to trustworthy and responsible use of AI.
Second,this study develops an AI literacy framework for researchers by integrating grounded theory with expert consultation. We systematically collect 81 documents issued by international organizations,government agencies,higher education institutions,and high quality academic journals. Grounded theory is then used to derive the framework's dimensional structure. Drawing on research lifecycle theory,the derived dimensions are aligned with three stages of research:initiation,implementation,dissemination and evaluation. Expert feedback further refines the framework into four dimensions:cognition,thinking,application,and ethics.
Subsequently,we further analyze the framework's core competencies,including foundational cognition,value understanding and critical thinking,computational thinking,data driven thinking,AI application,prompt literacy,AI enabled innovation,academic ethics,privacy protection,fairness and inclusiveness,human centered orientation,intellectual property awareness,and transparency and trustworthiness awareness.
Finally,we discuss three application scenarios of the framework. The first scenario concerns the development of assessment indicators,including the construction of the framework and criteria,and their contextualized application. The second scenario concerns the assessment of researchers AI literacy,involving AI enabled assessment systems,diversified evaluation methods,and periodic assessments. The third scenario involves formulating differentiated improvement strategies,including literacy level classification and personalized training programs.
AI literacy is no longer limited to tool use； rather,it has evolved into a core research competence that supports researchers in advancing scientific inquiry and innovation. This study delves into the AI literacy framework and its elements,thereby providing a conceptual basis for assessing and improving researchers AI literacy and fostering effective human AI collaboration. One limitation of this study is that it does not examine the relative importance of the core competencies or their interrelationships. Further research will assign weights to these competencies through questionnaire surveys and the Delphi method,thereby providing more targeted guidance for the measurement and improvement of researchers AI literacy. 1 fig. 5 tabs. 63 refs
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