基于综合数据平台分析的在线学习评估与预测算法设计

打开文本图片集

关键词：综合数据平台；多源融合技术；递归神经网络；在线学习平台；数据预测；数据评估中图分类号：TN919-34；TP183 文献标识码：A 文章编号：1004-373X（2025）20-0171-05

Design of online learning evaluation and prediction algorithm based on comprehensivedataplatform analysis

ZHUKai’，LI Peng²，WANG Qinyong1， TONGFeng1， ZHU Ge³ （1.Network and Digital ResourceCenter，Beijing Open University，Beijing1Ooo81，China; 2.SafetySensingusinessDepartmentBeijingSmart-chipicroelectroncsTechnologyCo.，Ltd.，BeijingO92Cina; 3.CollgeofArchitectureandEngineering，Zhengzhou Business University，Zhengzhou 451299，China）

Abstract：Inorder toachieveaccurateevaluation，predictionand intellgent processingof various typesof data inthe onlinelearning platform，adataevaluationandpredictionalgorithmbasedoncomprehensivedataplatformanalysisisproposed. Themulti-sourceacquisition technologyisusedtocolectvariousdata，andmulti-sourcefusiondataanalysisisconducted，which canlaythefoundationforinteligentdataevaluationandprediction.Therecursiveneuralnetworkalgorithmisintroducedinto thedata platformforthedynamicallyanalysis，soastorealize intellgentprocessngofvarious typesofdata.Byestablishing two layerhiddenlayerstructureofrecursiveneuralnetwork，thedataisevaluatedandpredictedaccordingtotherecursiveflow，soas to improve theevaluationaccuracyand predictionaccuracyofmulti-sourcedata.Theexperimentsontheproposedalgorithmare conductedandcompared withothersimilardata processing algorithms.Theresultsshowthatthealgorithmcanrealizeadata evaluation accuracy of 88.6% andadata prediction accuracy of 87.8%，providing a solution for the auxiliary analysis and processing of data on online learning platforms.

Keywords：integrateddataplatform；multi-source fusion technology；recursiveneuralnetwork；online learningplatform; dataprediction;data evaluation

0 引言

近年来，随着信息技术的飞速发展和“互联网 + 教育”模式的深入推进，在线教育迎来了前所未有的发展机遇，成为新时代推动教育公平与质量提升的重要力量。（剩余4497字）