农业图书情报学报2025，Vol.37Issue(5)：40-57,18.DOI:10.13998/j.cnki.issn1002-1248.25-0274
生成式人工智能环境下的搜索即学习:技术路径、行为演化与伦理挑战
Searching as Learning in the Context of Generative Artificial Intelligence:Technological Pathways,Behavioral Evolution,and Ethical Challenges
摘要
Abstract
[Purpose/Significance]This paper investigates how generative artificial intelligence(GenAI)is reshaping the Searching as Learning(SAL)paradigm,focusing on its implications,challenges,and prospects in Library and Information Science(LIS).Traditional SAL emphasizes the cognitive and metacognitive processes by which users acquire and construct knowledge through information retrieval.However,the advent of GenAI-especially large language models(LLMs)-introduces a transformative shift from keyword-based querying to dynamic,dialogic,and multimodal interactions.This study aims to clarify the conceptual and practical significance of GenAI-driven SAL,explore its technical trajectories,and evaluate its impact on learners'behavior,learning strategies,and information literacy.It also highlights the emerging ethical and epistemological challenges posed by GenAI systems in learning-oriented search contexts.[Method/Process]Using the PRISMA-ScR framework,this study conducted a scoping review of academic and gray literature published between January 2023 and May 2025.A total of 1 681 records were retrieved from major academic databases and preprint repositories.After screening titles,abstracts,and full texts,22 studies were selected for in-depth qualitative analysis.Thematic coding and synthesis were conducted to extract recurring patterns and theoretical insights across three key dimensions:GenAI-enhanced search technologies,evolving user behaviors in SAL contexts,and normative concerns associated with credibility,agency,and transparency.The analysis was grounded in LIS theories,including information behavior,metacognitive models of learning,and digital/information literacy frameworks.[Results/Conclusions]The results reveal that GenAI is fundamentally reshaping SAL in three key areas.First,in terms of technology,GenAI systems(e.g.,GPT-based chat interfaces)provide conversational,context-aware,and multimodal assistance,transforming SAL from reactive searching to proactive co-learning.These systems scaffold learning through adaptive query reformulation,real-time content summarization,and source triangulations supporting iterative reflection and cognitive engagement.Such affordances mirror the functions traditionally associated with human tutors,thereby expanding learners'capacity for critical inquiry and self-directed exploration.Second,user behaviors in SAL are undergoing a paradigm shift.Learners increasingly engage in human-AI co-construction of knowledge,participating in iterative query-dialogue loops that facilitate concept clarification and knowledge synthesis.While this enhances engagement,personalization,and perceived learning efficiency,it also raises concerns.Over-reliance on AI-generated content may undermine learners'critical thinking,reduce information discernment,and promote passive consumption.The study identifies a dual effect.While GenAI augments higher-order thinking and strategic learning,it can also lead to superficial comprehension when learners lack the skills to critically evaluate AI output.Third,the review underscores the urgency of addressing ethical and pedagogical challenges.Issues such as AI hallucination,algorithmic opacity,and biased content threaten the credibility of GenAI-enhanced learning environments.From an LIS perspective,this necessitates a reconfiguration of information literacy education to include AI literacy.Students must be equipped not only to retrieve and evaluate information,but also to interrogate algorithmic sources,verify provenance,and triangulate AI outputs with authoritative references.GenAI should be positioned as a cognitive assistant,not a definitive knowledge authority.GenAI holds substantial promise in enhancing SAL through greater interactivity,personalization,and cognitive scaffolding.However,these benefits must be balanced with informed practices that mitigate risks to learner autonomy,critical reasoning,and information ethics.This work establishes an analytical foundation for future research and practices at the intersection of AI,learning,and information behavior.关键词
生成式人工智能/搜索即学习/人机协同认知/信息素养重构/人工智能伦理Key words
Generative artificial intelligence(GenAI)/Searching as Learning(SAL)/human-AI cognitive collaboration/information literacy restructuring/AI ethics分类
社会科学引用本文复制引用
施栩婕,袁帆,李佳..生成式人工智能环境下的搜索即学习:技术路径、行为演化与伦理挑战[J].农业图书情报学报,2025,37(5):40-57,18.基金项目
国家留学基金委2024年度"国家建设高水平大学公派研究生项目"(202406140022) （202406140022）
上海第二工业大学图书馆2025科研基金项目"生成式人工智能驱动的研究型图书馆员AI素养框架构建与应用研究"(TSG25KJX02) （TSG25KJX02）
