数据挖掘在学习管理系统中应用的研究进展综述

数据挖掘和远程教育是当前两大热点领域,基于前者的学习管理系统是远程教育领域研究的热点和方向。文章首先剖析了近年来高等教育面临的形势和发生的变革,在此基础上引出了学习管理系统和数据挖掘的价值和必要性。随后重点分析了学习管理系统在高校中的使用情况,揭示了在线学习模式对教育领域的新启示,并介绍了数据挖掘在学习管理系统中的成功案例,从中可以看出学习管理系统的发展历程、现状和趋势。通过调研,研究者认为高等教育机构更多地采用学习管理系统进行在线教学的方式是未来的趋势,同时数据挖掘技术的采用是成功的关键。     

基于在线学习行为数据的学习者群体特征挖掘研究

教育信息化促使越来越多的学习者选择在线学习,基于学习行为数据的研究也逐渐增多,然而对学习行为的研究普遍基于学习者个人,涉及学习者相似群体特征挖掘的研究较少。选取阿里云天池中的公开数据集,通过对不同个性特征和认知能力的行为数据进行相关性分析,以学习成绩为依据聚类不同的学习者群体,挖掘群体的典型行为特征。研究表明,群体行为特征存在显著差异,借助群体特征挖掘可以帮助学生与他人对比,发现自身不足并及时调整。这样既能在个性化学习基础上充分利用群体智慧,也能避免因学生过多使教学工作者负担过重。     

A portrait of academic life:

The process of constructing A Portrait of Academic Life web resource has included careful evidence gathering and analysis of student performance necessary to assess learning and give useful feedback to increase the students’ ability to use information effectively in education. The students, too, develop self-assessment and reflective skills as they create online research portfolios. The online resources model new technologyenhanced strategies for teaching and learning that support standards-based teacher education programs in higher institutions. Other artifacts contained in A Portrait of Academic Life include digital video vignettes of students actively completing course assignments and reflecting on the learning process, and instructor reflections on teaching strategies to improve learning outcomes. As a culminating course activity, students showcase their online research portfolios at a gallery walk. The students were tremendously excited to present the wealth of information they have so carefully collected using the powerful technology tools available for their use in the teacher education program at Towson University. The innovation and originality presented in the form of student online research portfolios offered fresh perspectives to the honored guests. Likewise, it will enormously help students and faculty to see examples of the process of transforming traditional research papers into rich, informative online research portfolios.     

Place and Space in the Design of New Learning Environments

The development of online and virtual teaching and learning environments to augment formal face-to-face environments raises questions about the way the new communication and information technologies (CITs) are being incorporated into the on-campus environment. More importantly, this development challenges the meaning of the on-campus student learning experience. The new CITs require institutions, teachers and researchers to reconsider the relationship of the physical setting to the student learning experience. This paper highlights examples of recent developments of new learning environments which have been enhanced by the contribution of educational developers at several Australian universities. It also proposes a set of pedagogically informed principles to guide the development of on-campus teaching and learning environments which may feature the use of CITs.     

教育资源共享网络中教师聚类的提取与应用

教育资源共享网络中,教师间因对相同主题教育资源感兴趣而形成教师聚集现象,即教师聚类。文章分析了教师聚类形成几种原因,利用"k-核"分析法及其扩展提取教师聚类,特别讨论了在没有完整信息情况下,基于信息漫游的教师聚类提取策略。最后讨论教师聚类的应用。     

MOOC对高等教育教学模式的影响

大数据时代的到来,为各领域带来了新的数据研究方法,人们开始将数据作为一种基础性资源并注重研究其潜在价值,引导研究从单纯关注因果关系向关注相关关系转变。教育领域大规模开放网络课程的诞生及发展,在产生的海量学习数据的同时,为学习分析及教育数据挖掘提供了研究基础。作为一种新型在线课程资源,MOOC使开放教育从单纯的资源共享转变到课程与教学模式的革新,通过对学习者在线学习过程的追踪和实时分析,实现个体层面的课程定制,对我国高校教学模式改革提供了一定启示。     

Beyond engagement analytics: which online mixed-data factors predict student learning outcomes?

This mixed-method study focuses on online learning analytics, a research area of importance. Several important student attributes and their online activities are examined to identify what seems to work best to predict higher grades. The purpose is to explore the relationships between student grade and key learning engagement factors using a large sample from an online undergraduate business course at an accredited American university (n = 228). Recent studies have discounted the ability to predict student learning outcomes from big data analytics but a few significant indicators have been found by some researchers. Current studies tend to use quantitative factors in learning analytics to forecast outcomes. This study extends that work by testing the common quantitative predictors of learning outcome, but qualitative data is also examined to triangulate the evidence. Pre and post testing of information technology understanding is done at the beginning of the course. First quantitative data is collected, and depending on the hypothesis test results, qualitative data is collected and analyzed with text analytics to uncover patterns. Moodle engagement analytics indicators are tested as predictors in the model. Data is also taken from the Moodle system logs. Qualitative data is collected from student reflection essays. The result was a significant General Linear Model with four online interaction predictors that captured 77.5 % of grade variance in an undergraduate business course.     

模糊聚类分析在数据挖掘中的应用

聚类分析是数据挖掘的主要方法之一,而且能够作为一个独立的工具获得数据的分布状况,集中对特定的聚簇集合作进一步的分析。介绍了数据挖掘过程中常见的数据聚类算法,讨论了聚类分析最新的研究方向——模糊聚类方法。     

分类挖掘及其在学生保持工程中的应用

随着教育市场化与信息化进程的推进,学生保持越来越受人关注了,而传统的学生资源管理方法已经很难适应新的教育环境。在此篇文章中我们简述了分类挖掘技术并分析了学生保持工程中的学生流失问题,在此基础上,我们将决策树分类模型运用到学生资源数据仓库的挖掘系统中,并取得了较好的效果。     

数据挖掘技术在远程教育中的应用

通过数据挖掘技术可以有效地对远程教育中大量的信息资源进行整合统计分析,从而更好地促进远程教育的发展。该文以《现代英语语法》课程为例,运用路径分析、兴趣关联规则分析、聚类分析、序列模式分析等数据挖掘技术,处理学生在线学习该课程的大量数据,以可视化的方式把挖掘结果反馈给学习者和教学管理者,从而实现双赢的结果。     

A reflective learning taxonomy for an educational tour

This study is to investigate the reflective learning in a group of secondary school students who participated in an educational tour to Liannan, which is located in a rural area in Guangdong Province, Mainland China. The specific aim is to develop a framework to describe the learning in an educational tour. For this purpose, data were collected through students?? reflective writing in daily journals and end-of-trip sharing passages, triangulated with participant observation and interviews. The data analysis involved the use of grounded theory??s constant-comparative technique??an inductive method for generating hypotheses that are grounded in data. During the analysis of the data, the types of student learning which emerged were categorized in a Reflective Learning Taxonomy for an educational tour, comprising seven levels which are developmental in nature. The interpretative framework based on such a taxonomy of reflective learning reveals the rich context of learning in an educational tour and so makes a contribution to research on learning outside the classroom.     

信息资源辅助英语写作的应用原则和措施

该文以维护学习者动机的理论为依据,结合教学实际,提出了以易用、代价低、互动好、可选择作为信息资源应用于英语写作活动的原则,指出应用于英语写作的信息资源是一种综合性资源。随后提出了五项激励此类活动的措施。     

Instructor-provided summary infographics to support online learning

Infographics are a visualisation tool that can be used to improve retention, comprehension and appeal of complex concepts. The rise of infographic use in education has facilitated new forms of application and design of these tools. Instructor-provided summary infographics are a new form of infographic, whereby key learning objectives and content are summarised in graphical form at the end of a lesson. However, it is unknown whether these types of infographics can support learning in online environments. This exploratory research investigates student perceptions, retention, applications and activity generation of instructor-provided summary infographics in a massive online learning environment. Using both post-course learner survey data (n = 1,899) and text mining analysis (n = 72,490 words), results present how learners perceived instructor-provided summary infographics as useful and appealing for retaining, clarifying and understanding learning concepts. The research contributes a novel understanding of summary infographics in online learning environments, and supports their use as a design tool for educational delivery in the online space.     

学习分析:大学教学信息化研究与实践的新领域

随着大学教学信息化进程的不断深化与发展,如何测量、挖掘、分析与利用在学习平台中积累的大量数据,以更好地支持教学与学习,进而改善和提升教与学的质量与效能,已成为摆在大学教学信息化研究者与实践者面前的现实课题。学习分析的兴起则为解决这一难题,提供了一系列的方法、工具和手段。文章将基于国内外学者的已有研究,通过对学习分析的发展脉络的梳理,对学习分析的内涵、过程、工具和方法作较为深入的解读,并尝试从推动大学教学创新的视角,阐释学习分析对促进大学教学信息化深入发展的重要价值和深远影响。     

利用MOODLE构建信息技术主题学习资源的平台

Moodle是一个源代码开放的、基于建构主义教育理论而开发的免费软件,在国际上已得到广泛应用。根据目前国内网络教学中存在的问题,探讨如何利用moodle构建信息技术主题学习资源的平台,促进学生信息技术的应用,提高信息素养。     

大规模网络开放课程（MOOC）典型项目特征分析及启示

从2012年开始,以在线课程为核心的互联网公司纷纷涌现并获得飞速发展。大规模网络开放课程（MOOC）为学习者提供了一种新的知识获取渠道和学习模式,成为网络时代人们学习的新途径。通过梳理和总结MOOC发展的历史,并对MOOC初步分析的基础上,选择七个国外典型的MOOC项目作为分析对象,根据对各项目的基本信息进行内容分析确定关键词,从组织机制、平台定位、课程组织、课程资源、教学方式和质量认证六个方面,归纳大规模网络开放课程项目的主要特点,并从运营机制、课程开发、学生参与和学习评价四个方面提出指导我国开放教育资源进一步发展的启示。     

If and When Money Matters: The Relationships Among Educational Expenditures, Student Engagement and Students�� Learning Outcomes

Calls for accountability in higher education are prompted in part by questions concerning whether colleges and universities use their resources effectively to promote student learning. Unfortunately, too little is known about whether money matters to desired outcomes of college. Using students?? responses to the 2004 administration of the National Survey of Student Engagement (NSSE) in concert with institutional data from the Integrated Postsecondary Education Data System (IPEDS) and the College Board, this study examined the relationships between educational expenditures, student engagement and selected student self-reported learning outcomes, controlling for student and institutional characteristics. Results indicated that expenditures were modestly related to student engagement and learning outcomes. However, the nature of these relationships differed, depending on the engagement/outcome measure and student year in school.     

Application of learning analytics using clustering data Mining for Students’ disposition analysis

Learning Analytics (LA) is an emerging field in which sophisticated analytic tools are used to improve learning and education. It draws from, and is closely tied to, a series of other fields of study like business intelligence, web analytics, academic analytics, educational data mining, and action analytics. The main objective of this research work is to find meaningful indicators or metrics in a learning context and to study the inter-relationships between these metrics using the concepts of Learning Analytics and Educational Data Mining, thereby, analyzing the effects of different features on student’s performance using Disposition analysis. In this project, K-means clustering data mining technique is used to obtain clusters which are further mapped to find the important features of a learning context. Relationships between these features are identified to assess the student’s performance.     

学习分析技术:挖掘大数据时代下教育数据的价值

当前,大数据时代已经来临,教育领域同样积累了海量数据。教育领域已经部署了众多的学习管理系统,在这些软件系统中存储着海量的学习者信息及学习过程数据。如何利用这些数据,使这些数据转变为信息、知识,并为教学决策、学习优化服务,已成为教育工作者以及学习者们所关注的内容。学习分析技术有助于发挥学习过程数据的价值,使数据成为审慎决策、过程优化的重要依据。该文介绍了国内外学习分析技术研究现状,归纳出学习分析技术的关键技术及分析模式,并以实例从不同用户视角包括管理者、辅导教师、学习者展示了学习分析技术在网络学习过程分析中的应用过程。     

基于高校信息技术课程的虚拟学习社区构建研究

随着计算机技术的发展及互联网在现代教学中的应用,基于互联网的虚拟学习社区在课程教学中将得到广泛应用.为了提高高校信息技术课程的教学效果,采用PHP与MySQL开发了基于高校信息技术课程的虚拟学习社区,该社区以论坛为主模式,具有发帖与回帖、提问与交流、教学资料与课程资源呈现等功能.虚拟学习社区在课程教学中的应用改变了传统教学中以教师为中心的"灌输式"教学手段,让学生主动参与到课程学习中,并在教师的指导下完成建构学习、自主学习和交流互动,并直接参与社区课程资源的构建,增强学生的学习积极性与主动性,提高教学效果.