基于粗糙集的高校学生实践能力因素研究

学生实践能力是衡量一个高校学生综合能力的重要指标,但是由于影响学生实践能力的因素很多,没有统一的标准去衡量一个高校学生实践能力的好坏。因此,高校师生也无法采取针对性措施提高高校学生的实践能力。为了准确分析影响高校学生实践能力的因素,设计了影响高校学生实践能力的问卷,向大一至大四学生发放,采集数据,然后采用粗糙集理论中基于信息熵的启发式属性约简算法计算各个属性的属性重要度,找出影响高校学生学习实践能力的关键因素。再采用粗糙集理论中基于分辨矩阵的属性值约简算法,挖掘出影响高校学生实践能力的关键因素,导出规则集。通过实验验证了该规则集的有效性。研究成果可以对高校教学工作的开展提供参考,继而提高学生的实践能力。     

早开的玫瑰花——高校恋情案例分析

爱情是人类永恒的话题,正值青春妙龄的高校学生对于这个话题总是觉得既神秘又刺激,但他们对爱情的理解往往比较片面,恋爱中缺乏责任感。本文从具体案例入手,对高校校园恋情的各个方面进行了分析,给思政工作者以启发和借鉴,引导恋爱中的学生树立正确的人生观和恋爱观,帮助学生健康地成长成才。     

数据挖掘在高校学生心理问题中的应用

随着高校学生的心理问题越来越多,越来越复杂,使得传统的对学生心理问题的统计分析方法已不适应深入分析的需要。应用数据挖掘技术中的C4.5算法对学生心理数据库进行了情况分类,并对得到的结果进行了分析,得出了影响高校学生心理的因素,对高校学生进行心理健康状况预测,为高校学生心理健康教育提供决策支持。     

数据挖掘技术在成才因素分析中的应用研究

如何在高校有效地开展素质教育是一个迫切的问题,而通过对高校学生数据库的挖掘,有可能在这方面获得一些科学依据。文中介绍了数据仓库及数据挖掘基本技术,并将数据挖掘技术应用到成才因素分析之上,通过大量的实际数据测试,获取了感兴趣度较大的规则模式,在高校素质教育的具体应用中起到了促进的作用。最后给出了一个基于MSAnalysis Server的多维数据集及数据挖掘结果分析可视化平台。     

一种改进的多因素语义相似度计算方法

词语语义相似度计算是计算机自然语言处理中的关键问题,而相似度计算仅考虑单一的距离因素显然不够合理。通过分析概念网深度和密度因素对相似度计算的影响,提出一种改进的多因素相似度计算方法。实验结果表明,该方法能够根据概念网中节点对的分布状态,调整各影响因素的分配比例,从而使相似度计算结果更趋于合理判断。     

浅析高校学生干部创新能力的培养

高校学生干部是大学生中的高素质群体,相对而言,他们更具有创造性、能动性和号召力。他们的思想和行为会对其他学生产生深远的影响。重视学生干部创新能力的培养必将推动高校学生工作的不断发展。本文从高校学生干部创新能力的现状表现出发,分析高校学生干部创新能力的限制因素,进一步探讨如何培养学生干部的创新精神和创新能力。     

从多维角度谈高校学生信息焦虑的防治策略

该文通过高校学生信息焦虑的影响因素着手分析,从图书馆、读者个人、馆员三维角度,包括信息素质教育、多元化绿色导读模式的构建、建立平和的信息观和良好的个人生活习惯、摆脱手机依赖、以及心理咨询馆员与读者的互动等方面,阐述了对信息焦虑的防治策略,旨在解除高校学生的信息焦虑,优化信息行为,更有效地获取信息。     

数据挖掘技术在成才因素分析中的应用研究

如何在高校有效地开展素质教育是一个迫切的问题，而通过对高校学生数据库的挖掘，有可能在这方面获得一些科学依据。文中介绍了数据仓库及数据挖掘基本技术，并将数据挖掘技术应用到成才因素分析之上，通过大量的实际数据测试，获取了感兴趣度较大的规则模式，在高校素质教育的具体应用中起到了促进的作用。最后给出了一个基于MS Analysis Server的多维数据集及数据挖掘结果分析可视化平台。     

基于本体结构的概念间语义相似度算法

针对本体模型的结构特点,从模型概念间的宽度、深度、密度等方面分析本体概念相似度的计算,将其合并为结构因素。结合语义重合度、语义距离等影响相似度的因素综合考虑,提出一种基于本体结构的计算概念间语义相似度的算法。通过建立本体模型并进行实验分析,总结出本体结构方面各因素对本题概念语义相似度的影响。     

基于灰色关联分析的中文新闻事件关联性识别

针对中文新闻事件关联性识别准确率较低的问题,提出一种基于灰色关联分析(GRA)的中文新闻事件关联性识别算法,该算法是一种多因素分析法。首先,通过分析中文新闻事件的特性,提出三个影响事件关联性的因素,分别为触发词的共现性、事件的共享名词以及事件句的相似度;其次,对多个影响因素进行量化处理,计算每个影响因素的影响权值;最后,运用GRA将多个影响因素结合在一起,建立事件之间的灰色关联性分析模型,实现事件关联性识别。通过实验验证了三个影响因素对事件关联性识别的有效性,而且相对于只考虑单一影响因素的关联性识别算法,所提算法提高了事件关联性识别的准确率。     

Re-visiting college students’ attitudes toward the Internet-based on a 6-T model: Gender and grade level difference

The purpose of this study is to propose a 6-T model (Tool, Toy, Telephone, Territory, Treasure of Information, and Trade) to explore college students’ Internet-related attitudes, and to examine whether gender and grade level make any difference in their attitudes. Data from 1069 participants were collected from 96 Taiwanese universities and colleges. A Confirmatory Factor Analysis validated the proposed 6-T model and shows that it can well explain the 6-T factors. Each T’s magnitude of path coefficient shows that for these college students, the most recognized factors were Tool and Toy, followed by Treasure of information, Territory, and Trade, and that the least weighted factor was Telephone. Male students seem to have had a more positive attitude toward the Internet-related Toy and Telephone dimensions than did female students, and graduate students seem to have had a more positive attitude toward the Internet-related Tool, Information, and Trade dimensions than did undergraduate students. This study discusses limitations, future research directions, and implications for college educators and administrators.     

网络暴力事件中大学生的信息传播行为研究

随着社交网络的普及,新浪微博逐渐成为中国最大且最有价值的社交平台。然而网络的隐蔽性导致网络暴力事件层出不穷,大学生在社交平台发表看法和释放压力的同时却有可能不自觉中产生网络暴力的传播行为。本文以大学生为调查对象,基于新浪微博,进行网络暴力事件中信息传播行为的研究,设计了关于网络暴力事件信息传播行为的调查问卷,并构建用户传播行为回归模型,分析不同因素对信息传播行为的影响。本文通过因子分析与回归分析的方法,对大学生的信息传播行为进行研究,以期提高大学生对网络暴力事件的理性认知意识。     

Five facets of social presence in online distance education

Social presence in online learning environments refers to the degree to which a learner feels personally connected with other students and the instructor in an online learning community. Based on a 19 item Online Social Presence Questionnaire (OSPQ) given to college students in two different online learning courses, a series of exploratory and confirmatory factor analyses consistently revealed five factors representing facets of social presence in online learning environments: social respect (e.g. receiving timely responses), social sharing (e.g., sharing information or expressing beliefs), open mind (e.g., expressing agreement or receiving positive feedback), social identity (e.g., being called by name), and intimacy (e.g., sharing personal experiences). Together, the five factors accounted for 58% of the variance and were based on 19 items. Although much previous research focuses on cognitive aspects of learning in online environments, understanding the role of the learner’s sense of presence may be particularly important in distance learning situations in which students and the instructor are physically separated.     

Promoting online learners’ continuance intention: An integrated flow framework

Despite the rapid growth and significant benefits of online learning, retaining students in online courses remains a key challenge. This study empirically tests an integrated model that simultaneously examines factors influencing students’ attainment of flow experience in online learning and the impacts of flow on their online learning continuance intention. The results identified telepresence as the most significant factor influencing students’ flow experience in online learning. Perceived hedonic value played the most important mediating role transmitting the effects of flow on students’ continuance intention. The implications of the study for both research and practice are discussed.     

Features and predictors of problematic internet use in Chinese college students

This study was set to investigate the prevalence of problematic internet use (PIU) among college students and the possible factors related to this disorder. About 4400 college students, ranging from freshmen to juniors, from eight different universities in Wuhan, China were surveyed. Young's Diagnostic Questionnaire for Internet Addiction (YDQ) and the Zung Self-rating Depression Scale were used to define PIU and depression accordingly. Data was analysed with chi-squared testing and logistic regression. Out of the 3496 participants, 9.58% (male 13.54%, female 4.88%) met the criteria of PIU. Factors such as heavy internet use habits, poor academic achievement, lack of love from the family, etc. were found to be significantly associated with PIU. About 48.51% (1696) of the students were light internet users, who use the internet <5 h/week, while 16.36% (572) were heavy users who use it more than 15 h/week, though heavy users were more likely to develop PIU. Also, 25.53% of the students with depression developed PIU, in comparison with 8.91% of PIU among those without depression (p < 0.001). Being male, frequent internet use, poor academic achievement, poor family atmosphere and lack of love from parents were predictors of PIU among college students. The habit and purpose of using the internet is diverse, which influences the susceptibility of PIU as well. There was a correlation between depression and the development of PIU as well.     

Exploring factors of media characteristic influencing flow in learning through virtual worlds

This study aims to find out factors of media characteristic which are considered to influence flow in learning through virtual worlds. One hundred ninety eight elementary students who are eleven to twelve years old participated in this study. After the exploratory factor analysis, to extract media characteristics of virtual worlds, seventy-eight elementary students who are eleven years old were used in the analysis of exploring relationships between factors influencing flow.     

大学生就业的影响因素分析——以驻青大学为例

文章通过运用问卷调查的实证研究方法,分析了当前影响大学生就业的因素,其中涉及到大学生个人因素、学校因素、社会因素和工作环境因素等多方面,并分析归纳出影响大学生就业的重要因素,结合分析结果,提出了几点建议供大学生、高校以及政府等参考,以改善大学生就业现状。     

基于元胞自动机的股票价格宏观变化的研究

为了研究股票价格在宏观上的变化趋势以及产生这些变化的主要因素.提出了一种新的基于元胞自动机的模型分析股票价格宏观变化,构建了新的股票价格变化规则以及新的股票交易量的变化模型,假设了两大类影响股票价格宏观变化趋势的肉素,同时也细化了股票交易量的函数.模拟了当影响因素都利好,影响因素都利空以及影响因素利好利空交替出现的情况下,股票价格在宏观上的变化情况.仿真结果在一定程度上模拟了股票价格的宏观变化情况和股票价格变化的波动壤集性,说明了假设的两大类因素的合理性以及演化模型的正确性.     

高校新生社团推荐系统的开发及设计

高校学生的综合素质是影响高校毕业生就业的一个关键因素,高校社团是素质教育的一个重要途径,可以提高高校学生职业规划意识和职业素养。如何让新入学的高校新生选择合适的社团,是本文需要研究解决的问题。从用户的角度出发,推荐系统可有效地帮助用户做出决策。本文把学生的相似度计算、K-中心点算法聚类分析以及招收指数结合在一起,最终得到社团的推荐排序值,并将其推荐给新生用户。本系统能够实现为新生推荐社团服务,具有一定的应用价值。