教育支出日益成为农村家庭消费结构中的重要组成部分，其后蕴含着家庭对人力资本投资的策略选择与消费观念的转变。为深入了解农村居民在教育投入与消费偏好方面的真实状况，研究团队于2024年6－7月在河南省5个县15个乡镇开展了大规模入户问卷调查，形成了2024年河南省农村教育投入与消费偏好调查统计数据集。该问卷涵盖了家庭人口与收入信息、教育支出结构、线上教育使用情况、教育观念与焦虑感知等多个维度，共回收问卷3 169份，经缺失值与逻辑一致性审查后剔除67份，最终保留有效样本3 102份。问卷设计结合专家访谈与文献调研，数据采集过程中采用实地入户访问与随机抽样相结合，并通过双录入校验、异常值剔除和逻辑一致性审查等方式严格控制质量。与以往侧重宏观统计的研究不同，本数据集在微观层面揭示了农村家庭教育支出行为、消费偏好选择及教育焦虑特征，为实证检验“教育支出挤出效应”、探讨线上教育对教育公平的作用机制、分析不同收入群体的消费差异提供了坚实的数据支撑。同时，该数据集也为教育资源精准配置、农村家庭教育负担评估及数字教育产品推广提供了实践参考。

Educational expenditure has increasingly become an important component of rural household consumption structures, reflecting strategic choices in human capital investment and shifts in consumption perceptions. To gain an in-depth understanding of the actual situation of rural residents in terms of educational investment and consumption preferences, our research team conducted a large-scale household survey from June to July 2024 in 15 townships across five counties in Henan Province, resulting in the creation of the 2024 Henan Province Rural Education Investment and Consumption Preference Statistical Dataset. The questionnaire covered multiple dimensions, including household demographics and income, the structure of educational expenditures, online education usage, educational perceptions, and anxiety awareness. A total of 3,169 questionnaires were collected, of which 67 were excluded after checks for missing values and logical consistency, leaving 3,102 valid samples. The survey design was informed by expert interviews and literature reviews, and data collection was carried out through on-site household visits combined with random sampling, with strict quality control measures such as double-entry verification, outlier elimination, and logical consistency checks. Unlike previous studies focusing primarily on macro-level statistics, this dataset reveals at the micro level the educational expenditure behaviors, consumption preference choices, and anxiety characteristics of rural households. It provides solid empirical support for testing the applicability of the “education expenditure crowding-out effect,” examining the role of online education in promoting educational equity, and analyzing consumption differences across income groups. At the same time, the dataset offers practical references for the targeted allocation of educational resources, the assessment of rural household educational burdens, and the promotion of digital education products.