灰色马尔科夫模型在高校招生中的应用研究

本研究深入剖析了灰色马尔科夫模型在高校招生中的应用,由于高校生源变动的随机性、波动性以及复杂性,给招生预测工作带来了很多瓶颈。为了更准确地预测招生人数,我们将试图把灰色动态预测与马尔科夫预测模型融为一体,对高校招生人数进行预测。选取河南师范大学部分新生历年录取入学情况为研究对象,采用数据收集法、实验分析法、灰色马尔科夫模型等技术发掘数据中隐藏的规律和模式,从而为高校招生工作提供科学的依据。     

Making sense of learner and learning Big Data: reviewing five years of Data Wrangling at the Open University UK

Most distance learning institutions collect vast amounts of learning data. Making sense of this ‘Big Data’ can be a challenge, in particular when data are stored at different data warehouses and require advanced statistical skills to interpret complex patterns of data. As a leading institute on learning analytics, the Open University UK instigated in 2012 a Data Wrangling initiative. This provided every Faculty with a dedicated academic with expertise data analysis and whose task is to provide strategic, pedagogical and sense-making advice to staff and senior management. Given substantial changes within the OU (e.g. new Faculty structure, real-time dashboards, two large-scale adoptions of predictive analytics approaches, increased reliance on analytics), this embedded case study provides an in-depth review of lessons learned of five years of data wrangling. We will elaborate on the design of the new structure, its strengths and potential weaknesses, and affordances to be adopted by other institutions.     

Objectivity as standardization in data-scientific education policy,technology and governance

ABSTRACT

New data-driven technologies appear to promise a new era of accuracy and objectivity in scientifically-informed educational policy and governance. The data-scientific objectivity sought by education policy, however, is the result of practices of standardization and quantification deployed to settle controversies about the definition and measurement of human qualities by rendering them as categories and numbers. Focusing on the emerging policy agenda of ‘social and emotional learning and skills,’ this paper examines the practices of ‘objectivity-making’ underpinning this new field. Objectivity-making depends on three translations of (1) scientific expertise into standardized and enumerable definitions, (2) standardization into measurement technologies, and (3) the data produced through measurement technologies into objective policy-relevant knowledge, which consolidates a market in SEL technologies. The paper sheds light on knowledge-making practices in the era of big data and policy science, and their enduring reliance on the precarious construction of objectivity as a key legitimator of policy-relevant scientific knowledge and ‘evidence-based’ education governance.     

电子政务大厅功能结构分析

分析了电子政务大厅功能和组成结构，对构建电子政务大厅电子公文流转系统、信息发布系统、并联审批系统的功能和原理进行了分析。     

Web日志挖掘技术在校园网信息处理中的应用研究

随着校园网的快速发展,产生了海量信息,怎样利用数据挖掘技术根据校园网用户的访问日志挖掘出有价值的信息,是值得深入研究的。作者首先介绍了Web日志挖掘技术的主要内容,再深入研究在校园网信息处理方面的应用,重点以遵义师范学院校园网为实例,使用关联规则进行研究分析,探讨出用户的兴趣与偏好,从而更好地为学校教学管理服务。     

FARMER: A novel approach to file access correlation mining and evaluation reference model

File semantic has proven effective in optimizing large scale distributed file system. As a consequence of the elaborate and rich I/O interfaces between upper layer applications and file systems, file system can provide useful and insightful information about semantic. Hence, file semantic mining has become an increasingly important practice in both engineering and research community. Unfortunately, it is a challenge to exploit file semantic knowledge because a variety of factors could affect this information exploration process. Even worse, the challenges are exacerbated due to the intricate interdependency between these factors, and make it difficult to fully exploit the potentially important correlation among various semantic knowledges. This article proposes a file access correlation miming and evaluation reference (FARMER) model, where file is treated as a multivariate vector space, and each item within the vector corresponds a separate factor of the given file. The selection of factor depends on the application, examples of factors are file path, creator and executing program. If one particular factor occurs in both files, its value is non-zero. It is clear that the extent of inter-file relationships can be measured based on the likeness of their factor values in the semantic vectors. Benefit from this model, FARMER represents files as structured vectors of identifiers, and basic vector operations can be leveraged to quantify file correlation between two file vectors. FARMER model leverages linear regression model to estimate the strength of the relationship between file correlation and a set of influencing factors so that the “bad knowledge” can be filtered out. To demonstrate the ability of new FARMER model, FARMER is incorporated into a real large-scale object-based storage system as a case study to dynamically infer file correlations. In addition FARMER-enabled optimize service for metadata prefetching algorithm and object data layout algorithm is implemented. Experimental results show that is FARMER-enabled prefetching algorithm is shown to reduce the metadata operations latency by approximately 30%–40% when compared to a state-of-the-art metadata prefetching algorithm and a commonly used replacement policy.     

基于数据挖掘的图书馆的读者借阅行为分析

图书馆数字化发展,使数据挖掘技术在读者借阅行为分析方面得到了广泛使用。利用图书馆的借阅数据及调查结果,可形成一个关于读者需求的数据仓库,挖掘出读者需求的规则和模式,提取出有价值的内在信息,以便为图书馆建设服务。     

基于视频的数据挖掘系统的研究

研究了一种视频数据挖掘的系统结构.介绍了该系统中各主要模块的功能;描述了视频数据预处理和视频数据立方体;讨论了视频数据挖掘方法并探讨了典型的视频挖掘技术.     

Metaphors we’re colonised by? The case of data-driven educational technologies in Brazil

ABSTRACT

This article discusses issues concerning the spread of data-driven educational technologies in Brazil. Here, as elsewhere, educational technology continues to be promoted optimistically as the bearer of a panacea for historically-rooted social problems. Whilst some of these technologies have indeed contributed to important widening-participation programmes in the last two decades, widespread advocacy of technological ‘solutionism’, reflected in gradually stronger policy demands for efficiencies to be improved through ‘innovation’, has supported a relentless marketisation of the country’s educational systems. As transnational corporations position themselves to take control of key areas of these systems, threatening to restructure the whole sector, data-driven educational technologies provide the latest example in a series of ‘new’ ideas offered in an ever-expanding market. Based on the notion of ‘conceptual metaphors’, which encapsulate specific ways of perceiving, thinking and relating with the world, this article examines key metaphors underpinning discourses surrounding data-driven educational technologies in Brazil. In particular, the article analyses ways in which these specific metaphors may be promoting perspectives that ignore difference and obscure broader questions concerning education, thus contributing to the reproduction of previously existing problems and supporting new forms of colonisation.     

远程教育中的流媒体技术

众所周知,远程教育已经成为教育开放的四个领域之一.而随着我国现代化教育水平的提高,一个新的历史机遇正出现在面前.目前,我国的远程教育尤其是现代远程教育正在蓬勃发展.随着网络技术的发展及网络环境的完善,流媒体(stream Media)技术作为互联网中视音频传输的核心技术越来越普及,而这一新技术的在远程教育中的应用,必将给网络教育带来了新的活力和生机.