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论文编号：	16039
作者编号：	2120243879
上传时间：	2026/6/3 16:17:45
中文题目：	科研任务下AIGC用户信息采纳行为研究——基于HSM模型
英文题目：	Research on AIGC Users’ Information Adoption Behavior in Research Tasks: Based on the Heuristic-Systematic Model
指导老师：	李颖
中文关键字：	AIGC；科研新手；信息采纳行为；启发式—系统式模型
英文关键字：	AIGC；Research Novices；Information Adoption Behavior；Heuristic-Systematic Model
中文摘要：	在AIGC深度嵌入科研活动的现实背景下，本研究聚焦科研新手在科研任务中对AIGC信息的判断、信任与采纳，以启发式—系统式模型（HSM）为理论基础，采用混合研究方法。研究首先对22名具有AIGC科研使用经验的科研新手开展半结构化深度访谈，通过质性数据编码分析，提炼出任务复杂性、时间压力、AI素养、系统式加工、启发式加工、感知信任与信息采纳行为7个核心变量；在此基础上，构建“任务特征/用户特征—双路径加工—感知信任—信息采纳行为”的研究模型，并基于302份有效问卷对模型进行实证检验。 研究结果表明任务复杂性同时正向影响系统式加工与启发式加工；时间压力负向影响系统式加工，并正向影响启发式加工；AI素养正向影响系统式加工，并负向影响启发式加工；系统式加工与启发式加工均正向影响感知信任；感知信任正向影响信息采纳行为；模型整体拟合良好，各项研究假设均得到支持。研究还发现，科研新手在科研情境中的AIGC信息采纳并非简单的“采纳—不采纳”二元选择，而是呈现出“有限信任—有限采纳”的分层结构与边界特征。 本研究围绕任务情境、用户能力、认知加工、信任形成与行为决策之间的完整链条，揭示了科研任务情境下AIGC信息采纳的内在机制，一定程度上拓展了启发式—系统式模型在AIGC科研应用研究中的解释范围，可为科研新手AI素养培养、高校图书馆科研支持服务及AIGC学术应用场景优化提供理论依据与实践参考。
英文摘要：	Against the backdrop of the deep integration of AIGC into research activities, this study focuses on novice researchers’ evaluation, trust, and adoption of AIGC information in research tasks. Grounded in the Heuristic–Systematic Model (HSM) and employing a mixed-methods approach, this study first conducted semi-structured, in-depth interviews with 22 novice researchers who had experience using AIGC in research contexts. Through qualitative coding and analysis, seven core variables were identified: task complexity, time pressure, AI literacy, systematic processing, heuristic processing, perceived trust, and information adoption behavior. Based on these findings, a research model was constructed following the pathway of “task characteristics/user characteristics—dual-path processing—perceived trust—information adoption behavior,” and was subsequently empirically tested using 302 valid questionnaire responses. The results show that task complexity positively affects both systematic processing and heuristic processing; time pressure negatively affects systematic processing and positively affects heuristic processing; AI literacy positively affects systematic processing and negatively affects heuristic processing; both systematic processing and heuristic processing positively affect perceived trust; and perceived trust positively affects information adoption behavior. The overall model fit was satisfactory, and all research hypotheses were supported. The study further reveals that novice researchers’ adoption of AIGC information in research contexts is not a simple binary choice between “adoption” and “non-adoption,” but rather demonstrates a layered structure and boundary features characterized by “limited trust—limited adoption.” By examining the complete chain linking task context, user characteristics, cognitive processing, trust formation, and behavioral decision-making, this study reveals the underlying mechanism of AIGC information adoption in research task contexts. It extends, to a certain extent, the explanatory scope of the Heuristic-Systematic Model in research on AIGC-assisted academic work, and provides a theoretical basis and practical reference for cultivating AI literacy among novice researchers, enhancing research support services in university libraries, and optimizing academic application scenarios of AIGC.
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