心理学报2025，Vol.57Issue(6)：967-986,20.DOI:10.3724/SP.J.1041.2025.0967
基于生成式人工智能的认知外包:交互行为模式与认知结构特征分析
Cognitive outsourcing based on generative artificial intelligence:An Analysis of interactive behavioral patterns and cognitive structural features
摘要
Abstract
The emergence of generative AI has profoundly impacted the field of education by enabling individuals to enhance both the efficiency and quality of cognitive tasks by delegating part of the tasks to generative AI.This process is referred to as cognitive outsourcing.However,individuals' effectiveness in using AI varies.Empirical research on the educational applications of generative AI remains limited,primarily focusing on evaluating technical capabilities and the effects of learning support.At present,the cognitive and behavioral prerequisites for effective cognitive outsourcing remain unclear.Furthermore,the differences in prior knowledge,behavioral patterns,and cognitive structures among individuals with varying performances have yet to be thoroughly explored. In this study,we designed a cognitive outsourcing activity for graduate students involving a sample of 46 participants(10 males,36 females;age:M=26.39,SD=6.91).The activity consisted of two sessions.In the first session,participants were allotted 30 minutes to independently construct a concept map on the topic"Artificial Intelligence and Teachers"using pen and paper,which served as a measure of their prior knowledge.In the second session,participants engaged with a generative AI system to compose an essay on the same topic within a 100-minute time frame using a computer.The entire process was video-recorded.Based on expert evaluations,participants were categorized into high-performance and low-performance groups according to their essay scores.Interactive behaviors and contents were coded,and behavioral sequence transitions between the two groups were mapped using Lag Sequence Analysis.Additionally,Epistemic Network Analysis was employed to construct cognitive structure mappings,followed by a comparative analysis of the differences between the two groups. The results indicate that the high-performance group exhibited significantly higher prior domain knowledge compared to the low-performance group.Significant differences were observed between the two groups,including the frequency of different interactive behaviors,the frequency of different cognitive elements,the behavioral sequences,and the cognitive network structures.From the behavioral perspective,the high-performance group demonstrated significantly more diversified behavioral transitions,forming a distinctive pattern characterized by"rapid and autonomous task comprehension and planning,efficient and precise human-computer interaction,selective information extraction and deep processing."From the cognitive perspective,the high-performance group exhibited a well-balanced and comprehensive cognitive structure characterized by diverse and tightly interconnected cognitive elements.In contrast,the low-performance group displayed an unbalanced and loosely connected cognitive structure,primarily engaging with lower cognitive-level interaction.Overall,the findings indicate that effective cognitive outsourcing is a multifaceted process that necessitates active participation and profound cognitive processing.It demands proficient integration between internal cognitive frameworks and external technological tools. These findings highlight the distinct behavioral patterns and cognitive structures of individuals with varying levels of success in cognitive outsourcing activities and elucidate the cognitive and behavioral requirements for effective cognitive outsourcing.By focusing on individuals' prior knowledge and interactive processes,this study examines the influence of cognitive and behavioral characteristics on the efficacy of generative AI-assisted writing,thus contributing to empirical research on generative AI-supported education.Additionally,it extends the theoretical understanding of cognitive outsourcing and provides insight for future research and educational practices.Furthermore,the interactive behavior and content coding framework established in this study,along with the application of Lag Sequence Analysis and Epistemic Network Analysis,provide valuable methodological references.Future research should further investigate the long-term and deep-seated effects of cognitive outsourcing on individuals with different characteristics,as well as the intrinsic neural mechanisms underlying effective cognitive outsourcing.关键词
认知外包/人机协同/认知网络分析/滞后序列分析/内外部认知的连接Key words
cognitive outsourcing/human-computer collaboration/epistemic network analysis/lag sequence analysis/internal and external cognitive connections分类
心理学引用本文复制引用
汪凡淙,汤筱玙,余胜泉..基于生成式人工智能的认知外包:交互行为模式与认知结构特征分析[J].心理学报,2025,57(6):967-986,20.基金项目
"十四五"国家重点研发计划项目"农村地区教师教学能力智能评测与教学精准辅助技术研究"(2022YFC3303600). （2022YFC3303600）
