【摘要】：伴隨我國(guó)教育領(lǐng)域的改革和發(fā)展，現(xiàn)代計(jì)算機(jī)技術(shù)和通信技術(shù)在教育領(lǐng)域的應(yīng)用，促使現(xiàn)代教育越來(lái)越關(guān)注學(xué)習(xí)主體的特征和需要，在現(xiàn)代教育理論的影響下，人們把關(guān)注點(diǎn)都轉(zhuǎn)向了學(xué)生。教學(xué)管理過(guò)程中產(chǎn)生的大量學(xué)生數(shù)據(jù)在傳統(tǒng)的分析方式下很少對(duì)學(xué)生本身的行為因素或者以學(xué)生為主體的學(xué)習(xí)方式的隱含影響因素做深層的分析，，因此將數(shù)據(jù)挖掘技術(shù)應(yīng)用到學(xué)生信息的分析中，將具有重要的研究意義和實(shí)用價(jià)值。 本文主要工作如下： 1.利用聚類(lèi)技術(shù)中的K-means算法分析學(xué)生行為數(shù)據(jù)與學(xué)生學(xué)業(yè)成績(jī)之間潛在的關(guān)系。在對(duì)數(shù)據(jù)挖掘中的聚類(lèi)分析技術(shù)及其實(shí)際應(yīng)用進(jìn)行了較詳盡的分析的基礎(chǔ)上，根據(jù)大量學(xué)生數(shù)據(jù)以及采集到的學(xué)生學(xué)業(yè)成績(jī)，挖掘?qū)W生行為與學(xué)業(yè)成績(jī)之間隱藏的關(guān)系。分析結(jié)果表明學(xué)生行為對(duì)學(xué)生成績(jī)有很大的影響，這不僅為學(xué)生提供有價(jià)值有意義的依據(jù)，最終實(shí)現(xiàn)學(xué)生的自我約束、自我教育、自我管理、自我發(fā)展和自我完善，也為校方更好的實(shí)踐學(xué)生主體的教學(xué)方式提供更多信息與參考。 2.設(shè)計(jì)并實(shí)現(xiàn)了綜合校情分析系統(tǒng)，將學(xué)生行為與學(xué)生成績(jī)的關(guān)系分析應(yīng)用到綜合校情分析系統(tǒng)中。綜合校情分析系統(tǒng)的建設(shè)是為了使校方能夠從客觀(guān)實(shí)際出發(fā)，了解本校的綜合情況和優(yōu)劣勢(shì)，及時(shí)發(fā)現(xiàn)問(wèn)題和主要矛盾，促進(jìn)管理決策的科學(xué)化。系統(tǒng)多方位、多層次，更高效地對(duì)眾多紛雜數(shù)據(jù)進(jìn)行分析、展示各類(lèi)需要的信息，深度挖掘后呈現(xiàn)出來(lái)，為校方管理人員的決策提供數(shù)據(jù)支持。綜合校情分析系統(tǒng)的主要功能模塊有學(xué)生綜合分析系統(tǒng)模塊、消費(fèi)情況統(tǒng)計(jì)和學(xué)生行為分析。
[Abstract]:With the reform and development of educational field in our country, the application of modern computer technology and communication technology in the field of education makes modern education pay more and more attention to the characteristics and needs of the main body of learning, under the influence of modern educational theory. People turned their attention to students. A large number of student data produced in the course of teaching management rarely make deep analysis of the students' own behavior factors or the implicit influence factors of student-centered learning style under the traditional analysis method. Therefore, it is of great significance and practical value to apply data mining technology to the analysis of student information. The main work of this paper is as follows: 1. The K-means algorithm in clustering technology is used to analyze the potential relationship between student behavior data and students' academic achievement. Based on the detailed analysis of clustering analysis technology and its practical application in data mining, the hidden relationship between student behavior and academic achievement is explored according to a large number of student data and student academic achievements collected. The results show that student behavior has a great influence on students' achievement, which not only provides a valuable and meaningful basis for students, but also realizes students' self-restraint, self-education, self-management, self-development and self-improvement. It also provides more information and reference for the school to better practice the main teaching methods of students. 2. The comprehensive school situation analysis system is designed and implemented. The relationship analysis between student behavior and student achievement is applied to the comprehensive school situation analysis system. The construction of the comprehensive school situation analysis system is to enable the school authorities to understand the comprehensive situation and the advantages and disadvantages of the school from the objective reality, to find out the problems and the main contradictions in time, and to promote the scientific management decision. The system is multi-directional, multi-level, more efficient to analyze the numerous and complicated data, display all kinds of information needed, and show them after deep mining, which can provide data support for school administrators to make decisions. The main function modules of the comprehensive school situation analysis system include student comprehensive analysis system module, consumption statistics and student behavior analysis.
【學(xué)位授予單位】：河南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：G647

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