我国电子资源引进的发展策略研究

针对电子资源采购的国际发展动态 ,分析我国电子资源引进的现状 ,根据电子资源自身的类型和特点 ,提出多元化、分层次引进电子资源的构想 ,并根据我国的实际情况提出相应的对策     

教师参与 分类选择 集中收藏--论高校馆图书采购工作和经费分配制度改革

高校馆图书收藏工作的困难及其原因是多层面的，走出困境的出路在于：以学校管理体制改革保障图书收藏体制改革，实行“教师参与，分类选择，集中收藏”和经费“四级分配，专款专用”制度。     

文献资源的网络采集策略

文献资源的网络采集是图书馆采访的新形式。图书馆采访人员必须掌握与文献网络采集有关的信息获取、网上书店选择、书目数据判选、转换与利用策略，熟悉网络采集环节，逐步向文献采集网络化过度。     

图书馆联盟电子资源采购

本论述了目前电子资源采购的新模式——图书馆联盟采购，探讨了其兴起的原因，以SLCC中国集团为例分析了联盟采购的特点和所带来的效益，并谈了对组织图书馆联盟采购的几点体会。     

Collecting women’s archives at the ANU Archives

The Australian National University Archives holds both the archives of the University and a large collection of business and labour archives in the Noel Butlin Archives Centre. Both are governed by collecting policies, and neither of these policies mention gender. The relative absence of women’s voices in both collections raises the question about whether archival policies should seek to redress past silences.     

历史地理信息的获取与标准化——以上海交通大学馆藏地方历史文献为例

上海交通大学图书馆针对近年来收集的地方历史文献开展了数字化加工工作。如何有效地提取文献蕴含的地理信息并使其标准化,最终实现数字化的展示、利用与分析是工作的难点之一。地理信息经由人工获取,根据研究需求按照分段揭示的原则著录到地域相关的元数据字段中。基于可统计的文献来源,分布集中的文献优先编写代码转换规则,可机读代码避免了语义识别等程序的繁冗。鉴于明清时期行政区划的特点,代码采用"省-县-都-图-村"五级格式,遵照标准化、兼容性、求同性与扩展性的编制原则,以期实现文献关联聚类、信息自动获取与空间可视化等数据化效果,还原地域视角下的历史原貌。     

Age Factor in Second Language Acquisition

In the second language acquisition, the study focus of linguistics is the influence of age factors which has always been considered as one of the most controversial issues. Some experts hold that the y...     

基于微信辅助下的成人本科阶段英语阅读能力提升实践

分析了成人本科阶段学生在英语阅读理解方面存在的问题,采用“微信打卡”小程序和“微信公众号”帮助学生每天坚持阅读技能训练。参与的学生可以进行文字、语音、图片等方式的打卡操作,分享自己完成该篇阅读的时长、答案、收获、困惑等,教师次日在“微信公众号”中发布阅读理解的答案、译文、解析、阅读技巧等,并根据学生的提问进行个别化的辅导。实践证明,基于微信辅助下的阅读方式能有效帮助成人学生坚持阅读训练,分享阅读心得,提高阅读技能,提升阅读兴趣。     

Multimodal data as a means to understand the learning experience

Most work in the design of learning technology uses click-streams as their primary data source for modelling & predicting learning behaviour. In this paper we set out to quantify what, if any, advantages do physiological sensing techniques provide for the design of learning technologies. We conducted a lab study with 251 game sessions and 17 users focusing on skill development (i.e., user's ability to master complex tasks). We collected click-stream data, as well as eye-tracking, electroencephalography (EEG), video, and wristband data during the experiment. Our analysis shows that traditional click-stream models achieve 39% error rate in predicting learning performance (and 18% when we perform feature selection), while for fused multimodal the error drops up to 6%. Our work highlights the limitations of standalone click-stream models, and quantifies the expected benefits of using a variety of multimodal data coming from physiological sensing. Our findings help shape the future of learning technology research by pointing out the substantial benefits of physiological sensing.