基于多源数据融合的大学生创新能力评估方法研究

——基于人工智能赋能的新质生产力视角

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中图分类号：G64 文献标识码：A文章编号：1672-3791（2026）02-0028-03

Research on Evaluation Method of College Students' Innovation Ability Based on Multi-Source Data Fusion 一From the Perspective of New Quality Productive Forces Empowered by Artificial Intelligence

OUYANG Leqian YU Qian WANG Yibo

Hunan University of Finance and Economics，Changsha，Hunan Province，41o2O5 China

Abstract： The current traditional evaluation methods for innovation capability have problems such as strong static natureand single evaluation dimensions，which are dificult toadapt to the diverse innovation ability portrait needs of colege students under the background of newquality productive forces.Basedon this，this article designs a college student innovation ability evaluation method based on multi-source data fusion to improve the accuracy and dynamicadaptabiltyof the evaluation results.The method integrates multiple heterogeneous data sources such as scientific research projects，clasroom experiments，andacademic socialization，proposes corresponding data fusion strategies and key feature extraction paths，and comprehensively evaluates the innovation abilityof college students. Experimental results show thatthis evaluation method issuperiorto traditional evaluation methods in terms of comprehensivenessandresult stabilityverifyingtheefectivenessofthedesignedmethod.Onthisbasis，furthermprovement of evaluation methods willbe made from aspects such as algorithm optimization，privacy protection，and fairness constraints，providing support for its practical application and promotion..

Keywords： Artificial intelligence; Multi-source data fusion; Innovation ability evaluation; Data security

当前，大学生创新能力评估普遍依赖传统量表打分、教师主观评价或档案静态记录等方式，存在评价维度狭窄、反馈滞后、缺乏动态追踪等问题，难以真实刻画学生在复杂应用场景中的创新表现，也难以满足新质生产力对高素质复合型人才的培养要求。（剩余2846字）