个性服务视域下的高校档案数据库建设     

沙敏 《档案管理》2020,(3):115-116

本文通过研究当前高校档案管理的重要性,结合实际的档案需求情况,分析了档案专题数据库基本的几种类型,来满足高校群体对档案信息的个性化需求,并通过对档案专题数据库模式的分析,制定了具体的应用措施,以便能够为相关人员提供信息参考。  相似文献   

智能搜索引擎与数字图书馆个性化服务   总被引：13，自引：0，他引：13  

邹凯  汪全莉 《情报科学》2004,22(7):874-877

智能搜索引擎基于知识(概念)层面实行信息检索，以较强的自然语言理解和知识处理能力，表现出良好的个性化信息服务特色。因此，智能搜索引擎应用于数字图书馆个性化服务体系，不仅有效发挥前者数据挖掘、知识发现的功能，同时能较大地加深后者的主动性、智能性优势。  相似文献   

小学生到底喜欢什么样的学习资源*--梅耶多媒体学习原则对数字原住民适用性的实证研究     

孙众  骆力明 《中国电化教育》2015,(7)

根据资源偏好和学习难度为学习者提供个性化资源,是数字教材应该具备的功能。上世纪末梅耶等人提出的多媒体学习原则,曾在学习资源设计与开发中发挥了重要的指导作用。那么为数字原住民设计数字教材时,这些原则是否依然适用？该文以72名小学生作为被试,研究他们对资源类型、组合方式和难度的学习偏好,从而验证梅耶理论对数字原住民的适用性。结果发现被试的偏好选择与梅耶的多媒体学习原则基本吻合,但也出现了一些偏差。该文的结论为数字教材中个性化学习资源推送策略提供了实证基础。  相似文献   

基于Web2.0的高校图书馆个性化信息服务:现有模式、存在问题及服务优化   总被引：3，自引：0，他引：3  

李育嫦 《新世纪图书馆》2011,(4)

论文从基于Web2.0的个性化信息服务的内涵、特征出发,系统介绍国内高校图书馆开展Web2.0个性化信息服务的模式,分析其中存在的问题,最后从Web2.0个性化信息服务所涉及的人、信息资源、技术和服务等方面提出了进一步优化的建议。  相似文献   

SCORM排序策略在远程教育中的运用     

龚玉凤 《现代教育技术》2008,18(3):71-74

满足学生的个性化学习需求和提高他们的学习体验质量是网络教师和学校遵循的重要目标。如何在远程教学中用相同的内容实施不同的学习策略呢?SCORM排序策略可以帮助我们有效实现这种需求,并且在国际远程教育中有成功的实践。我们可以对SCORM的排序和导航规则进行研究和完善,制作出符合我国网络教学的策略模板,让网络教师套用,从而为学生提供配有灵活教学策略的个性化学习体验。  相似文献   

个性化课件生成系统的设计与实现   总被引：4，自引：0，他引：4  

马晓兰  吴永和 《现代教育技术》2004,14(2):49-52

该文从我国网络教育技术标准入手,从静态和动态二个方面深入系统地分析了影响网络化学习的一些个性化参数,并在此基础上提出了个性化课件生成系统的总体架构,详细阐述了个性化课件生成系统的关键技术和解决方案。  相似文献   

Distributed leadership for personalized learning     

Julie M. Kallio  Richard Halverson 《Journal of Research on Technology in Education》2020,52(3):371-390

Abstract

Personalized learning refers to a collection of practices designed to place student interests and needs at the heart of schooling. Schools that implement personalized learning need leaders that support educators and students in redesigning the core practices of teaching and learning in K-12 schools. To answer the question of how leaders support this redesign, we use distributed leadership theory to focus on the macrotasks and microtasks that leaders enact to create the conditions for personalized learning practices. Drawing on a five-year, qualitative study of 11 personalized learning programs in the Midwest, we identify three macrotasks supporting personalized learning: reorganizing learning environments to support student voice and choice, assembling idiosyncratic technology ecosystems to distribute teaching and learning tasks, and redesigning instructional time to prioritize student’s interests, agency, and learning relationships. After we describe a number of microtasks associated with each macrotask, we discuss how a consideration of these kinds of leadership tasks can open the contemporary discussion of personalized learning from a narrow focus on learning technologies to an expansive vision of student-centered school reform.  相似文献   

Personalized learning in iSTART: Past modifications and future design     

Kathryn S. McCarthy  Micah Watanabe  Jianmin Dai  Danielle S. McNamara 《Journal of Research on Technology in Education》2020,52(3):301-321

Abstract

Computer-based learning environments (CBLEs) provide unprecedented opportunities for personalized learning at scale. One such system, iSTART (Interactive Strategy Training for Active Reading and Thinking) is an adaptive, game-based tutoring system for reading comprehension. This paper describes how efforts to increase personalized learning have improved the system. It also provides results of a recent implementation of an adaptive logic that increases or decreases text difficulty based on students’ performance rather than presenting texts randomly. High school students who received adaptive text selection showed increased sense of learning. Adaptive text selection also resulted in greater pre-training to post-training comprehension test gains, especially for less-skilled readers. The findings demonstrate that system-driven, just-in-time support consistent with the goals of personalized learning benefit the efficacy of computer-based learning environments.  相似文献   

Multimedia augmented m-learning: Issues,trends and open challenges     

《International Journal of Information Management》2016,36(5):784-792

The advancement in mobile technology and the introduction of cloud computing systems enable the use of educational materials on mobile devices for a location- and time-agnostic learning process. These educational materials are delivered in the form of data and compute-intensive multimedia-enabled learning objects. Given these constraints, the desired objective of mobile learning (m-learning) may not be achieved. Accordingly, a number of m-learning systems are being developed by the industry and academia to transform society into a pervasive educational institute. However, no guideline on the technical issues concerning the m-learning environment is available. In this study, we present a taxonomy of such technical issues that can impede the life cycle of multimedia-enabled m-learning applications. The taxonomy is devised based on the issues related to mobile device heterogeneity, network performance, content heterogeneity, content delivery, and user expectation. These issues are discussed, along with their causes and measures, to achieve solutions. Furthermore, we identify several trending areas through which the adaptability and acceptability of multimedia-enabled m-learning platforms can be increased. Finally, we discuss open challenges, such as low complexity encoding, data dependency, measurement and modeling, interoperability, and security as future research directions.  相似文献   

显式评分的重启动随机游走推荐算法研究     

俞琰  邱广华 《现代图书情报技术》2012,(3):8-14

针对目前重启动随机游走推荐算法偏重隐式评分而忽略显式评分的问题,采用监督重启动随机游走算法,使得用户喜爱的项目被访问的概率大于用户不喜爱的项目的概率,从而做出推荐。实验表明,该算法可以有效地提高推荐的准确性。  相似文献