基于iData的大学生自主学习能力预测模型研究

发布时间：2018-02-10 11:13

本文关键词： iData 大学生自主学习能力预测评估马尔科夫链预测模型模糊综合评判法　出处：《大连海事大学》2017年硕士论文　论文类型：学位论文

【摘要】：当今世界,对于大学生来说,自主学习能力的培育举足轻重,而对自主学习能力进行预测评估则是提升自主学习能力的有效方法。iData被称为"小数据"或"我数据",是以个人为中心的数据。小数据以单人为唯一对象,可以被全方位、全天候、深入、准确地挖掘和利用,且重点放在深度上。自主学习能力的预测评估是以个人为研究对象的,本文将大学生自主学习能力的预测评估与iData技术相结合,研究基于iData的大学生自主学习能力预测模型,具有重要的实际应用价值。针对自主学习能力评估的目前研究状况,在分析和研究iData、大学生自主学习能力相关理论与技术的基础上,给出了预测的总体框架。设计了基于马尔科夫链的大学生自主学习能力预测模型及预测误差的检验方法,同时给出了大学生自主学习能力评估方法。针对马尔科夫链预测模型,状态转移概率矩阵的求解是重点研究对象。针对大学生自主学习能力综合评估及单项指标评估方法,主要使用模糊综合评判法。本文实现了大学生自主学习能力预测总体框架的主要功能模块,包括基于马尔科夫预测链模型的自主学习能力预测模块、自主学习能力预测误差检验模块、基于模糊综合评判法的自主学习能力评估模块。最后,基于该框架设计并实现了大学生自主学习能力预测评估平台,该平台实现了一体化的大学生自主学习能力预测、评估全过程,并采用直观的图表方式对结果进行展现,该平台包括问卷调查、自主学习情况统计、自主学习能力预测、自主学习能力比较以及自主学习能力分析等。通过该平台,大学生可以不断地对自我学习能力进行检测、调整,最终达到提高自主学习能力的目的。
[Abstract]:In today's world, for college students, the cultivation of autonomous learning ability plays an important role. And predicting and evaluating autonomous learning is an effective way to improve autonomous learning. IData is called "small data" or "my data," and it's individual-centric data. The prediction and evaluation of autonomous learning ability is aimed at individuals. This paper combines the prediction and evaluation of autonomous learning ability of college students with iData technology. It is of great practical value to study the prediction model of autonomous learning ability of college students based on iData. On the basis of analyzing and studying the theory and technology of iDataand college students' autonomous learning ability, this paper gives the overall framework of prediction, and designs the prediction model of college students' autonomous learning ability based on Markov chain and the test method of prediction error. At the same time, the evaluation method of college students' autonomous learning ability is given. For Markov chain prediction model, the solution of state transition probability matrix is the key research object, and the comprehensive evaluation of college students' autonomous learning ability and the single index evaluation method. In this paper, the main functional modules of the overall framework for predicting autonomous learning ability of college students are realized, including the prediction module of autonomous learning ability based on Markov predictive chain model. The prediction error test module of autonomous learning ability, the evaluation module of autonomous learning ability based on fuzzy comprehensive evaluation method. Finally, the prediction and evaluation platform of autonomous learning ability of college students is designed and implemented based on the framework. The platform realizes the integrated prediction of college students' autonomous learning ability, evaluates the whole process, and presents the results by using intuitive chart. The platform includes questionnaire survey, statistics of autonomous learning, prediction of autonomous learning ability. Through this platform, college students can constantly test and adjust their self-learning ability, and finally achieve the goal of improving their autonomous learning ability.
【学位授予单位】：大连海事大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：G642.0;O211.62

【参考文献】