信息资源管理学报2025，Vol.15Issue(5)：116-130,15.DOI:10.13365/j.jirm.2025.05.116
个性化推荐情境下算法素养知识启发措施与提升模式识别研究
Identifying Knowledge Heuristic Intervention and Enhancement Patterns for Algo-rithmic Literacy in Personalized Recommendation Contexts
摘要
Abstract
Personalized recommendations significantly influence daily life and represent a key shift in in-formation control toward algorithms.This change necessitates new skills for individuals to perceive,under-stand,and utilize these algorithms effectively,highlighting an urgent need for research on algorithmic literacy within the context of personalized recommendations.This study concentrated on personalized recommenda-tion contexts,developing a knowledge heuristic intervention to enhance algorithmic literacy.A 4-week longi-tudinal user experiment involving 30 participants was conducted,with statistical comparisons and analyses of chan-ges in algorithmic literacy,as well as the identification of enhancement patterns through cluster analysis.Before and after the experiment,users showed significant improvements in different dimensions of algorithmic literacy,confir-ming the effectiveness of the knowledge heuristic intervention.Cluster analysis identified three enhancement patterns of algorithmic literacy:gradual improvement with weak foundations pattern,Knowledge-Skill enhancement with weak motivation pattern,and awareness enhancement with strong motivation pattern.This study further analyzed user characteristics associated with each pattern and proposed tailored knowledge heuristic strategies for enhancing algorithmic literacy based on these characteristics.关键词
算法素养/个性化推荐/知识启发/启发措施/提升模式Key words
Algorithmic literacy/Personalized recommendation/Knowledge heuristic/Heuristic interven-tion/Enhancement patterns引用本文复制引用
刘静,白芳睿,吴丹..个性化推荐情境下算法素养知识启发措施与提升模式识别研究[J].信息资源管理学报,2025,15(5):116-130,15.基金项目
本文系国家自然科学基金"可解释、可通用的下一代人工智能方法"重大研究计划培育项目"人机交互视角下数据与知识双驱动的可解释智能决策方法研究"(92370112)及湖北省自然科学基金创新群体项目"以人为本的人工智能创新应用"(2023AFA012)的阶段性成果之一.(This paper is one of the outcomes of the Major Research Program"Explainable and Universal Next-Generation Artificial Intelligence Methods"(92370112)supported by National Natural Sci-ence Foundation of China,and the Innovation Group Project"Human-Centered Innovative Applications of Artificial Intelli-gence"(2023AFA012)supported by Hubei Natural Science Foundation.) （92370112）
