本文選題：網(wǎng)絡(luò)教育　切入點(diǎn)：網(wǎng)絡(luò)學(xué)院　出處：《河南大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：自1999年教育部開始大力興辦遠(yuǎn)程教育試點(diǎn)以來(lái)，網(wǎng)絡(luò)學(xué)院在發(fā)揮他積極作用的同時(shí)也暴露出一些不足：由于網(wǎng)絡(luò)教育學(xué)習(xí)者來(lái)源復(fù)雜，環(huán)境不固定，會(huì)造成精力投入的不夠和學(xué)習(xí)時(shí)間不能保證等問(wèn)題，以至于輟學(xué)、滯學(xué)等未完成學(xué)業(yè)的現(xiàn)象成為網(wǎng)絡(luò)教育者面臨的一個(gè)嚴(yán)重問(wèn)題。目前關(guān)于網(wǎng)絡(luò)教育學(xué)業(yè)影響因素的研究仍處于教育統(tǒng)計(jì)的層面，許多研究仍然建立在體會(huì)和感想等較低層次的基礎(chǔ)上；運(yùn)用的實(shí)證研究方法不夠科學(xué)規(guī)范，如調(diào)查問(wèn)卷的設(shè)計(jì)、抽樣的代表性，數(shù)據(jù)的統(tǒng)計(jì)推理等方面不夠嚴(yán)格，缺乏本土化的輟學(xué)理論的建構(gòu)和理論上的提升。 本文從幾個(gè)方面對(duì)網(wǎng)絡(luò)學(xué)院未完成學(xué)業(yè)的情況進(jìn)行分析并得出易于決策的模型:首先，明確本研究的研究背景、研究現(xiàn)狀、研究目的、論文的結(jié)構(gòu)等；其次，簡(jiǎn)述我國(guó)網(wǎng)絡(luò)高等教育的發(fā)展現(xiàn)狀，并通過(guò)文獻(xiàn)調(diào)研和理論分析，，了解“成人網(wǎng)絡(luò)學(xué)習(xí)”、“數(shù)據(jù)挖掘”和“決策樹”等相關(guān)概念和技術(shù)；接著改進(jìn)了Kember模型，提出了適應(yīng)我國(guó)特點(diǎn)的“網(wǎng)絡(luò)教育學(xué)業(yè)完成影響因素模型”，并以此設(shè)計(jì)調(diào)查問(wèn)卷，得出學(xué)生學(xué)習(xí)過(guò)程的相關(guān)信息；最后結(jié)合遠(yuǎn)程學(xué)習(xí)系統(tǒng)中的信息組成我們要研究的數(shù)據(jù)對(duì)象，引入決策樹技術(shù)，利用Weka數(shù)據(jù)挖掘軟件進(jìn)行分析，找出每個(gè)因素對(duì)網(wǎng)絡(luò)學(xué)習(xí)者完成學(xué)業(yè)的影響程度，并利用分析結(jié)果對(duì)可能有輟學(xué)危險(xiǎn)的在讀者和新入學(xué)者實(shí)施相應(yīng)對(duì)策，有目的給予指導(dǎo)，提高預(yù)警轉(zhuǎn)化率。 本課題的主要任務(wù)是根據(jù)研究所在地的某網(wǎng)絡(luò)學(xué)院的學(xué)生網(wǎng)絡(luò)學(xué)習(xí)行為等信息，利用數(shù)據(jù)挖掘技術(shù)分析他們與學(xué)業(yè)完成之間的關(guān)系，得出一種最優(yōu)的基于學(xué)業(yè)影響因素的決策樹規(guī)則。通過(guò)數(shù)據(jù)分析得出最值得我們警惕的影響網(wǎng)絡(luò)教育學(xué)業(yè)完成的因素，研究所形成的數(shù)據(jù)分析模型，使教育決策者對(duì)在讀學(xué)習(xí)者和新入學(xué)者的干預(yù)管理提供了一個(gè)有力的手段，對(duì)提高網(wǎng)絡(luò)高等教育質(zhì)量有重大的意義。
[Abstract]:Since 1999, when the Ministry of Education began to set up a distance education pilot project, the network college has brought into play its positive role and also exposed some shortcomings: because of the complexity of the sources of online education learners, the environment is not fixed. It can cause problems such as lack of effort and lack of assurance of study time, so that they drop out of school. The phenomenon of uncompleted education, such as school delay, has become a serious problem for network educators. At present, the research on the influencing factors of online education is still at the level of education statistics. Many studies are still based on lower levels of experience and perception, and the empirical research methods used are not scientific enough, such as the design of questionnaires, the representativeness of sampling, the statistical reasoning of data, etc. Lack of localization of the theory of school dropout construction and theoretical promotion. In this paper, we analyze the uncompleted study of network college from several aspects and get the model which is easy to make decision: first, make clear the research background, research actuality, research purpose, structure of the paper, etc.; second, make clear the research background, the research purpose, the structure of the thesis, etc. This paper briefly introduces the current situation of the development of network higher education in our country, and through literature investigation and theoretical analysis, understands the related concepts and technologies, such as "adult network learning", "data mining" and "decision tree", and then improves the Kember model. This paper puts forward a "model of influencing factors of academic achievement of network education" adapted to the characteristics of our country, and designs a questionnaire to obtain the relevant information of the students' learning process. Finally, combining the information in the distance learning system, it constitutes the data object that we want to study. The decision tree technology is introduced, and the Weka data mining software is used to analyze the influence of each factor on the completion of the study. The results of the analysis are used to implement the corresponding countermeasures to the readers and new scholars who may drop out of school. Aim to give guidance to improve the early warning conversion rate. The main task of this paper is to analyze the relationship between students and their academic completion by using data mining technology according to the information of students' online learning behavior in a certain network college where they are located. Get an optimal decision tree rule based on academic factors. Through data analysis, we can get the most alarming factors that affect the academic completion of network education, the data analysis model formed by the research, It provides a powerful means for educational decision makers to intervene in the management of learners in reading and new scholars. It is of great significance to improve the quality of network higher education.
【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】：2013
【分類號(hào)】：G434

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本文編號(hào)：1562914