Facilitating flexible learning by replacing classroom time with an online learning environment: A systematic review of blended learning in higher education

Higher education institutions are trying to provide more flexibility and individualization, which is mainly realized through the use of new technologies and implemented in online or blended learning designs. This systematic review aims to investigate the impact of replacing classroom time with an online learning environment. The meta-analysis (k = 21 effect sizes) applied strict inclusion criteria concerning research design, measurement of learning outcomes and implementation of blended learning. The estimated effect size (Hedge's g) was positive, although not significantly different from zero and the confidence interval [-0.13, 0.25], suggesting that overall differences between blended and conventional classroom learning are small, and, at best, very small negative or moderate positive effects are plausible. This means that despite a reduction in classroom time between 30 and 79 per cent, equivalent learning outcomes were found. Consequently, blended learning with reduced classroom time is not systematically more or less effective than conventional classroom learning.     

Educators’ experiences in special education institutions during the COVID-19 outbreak

The COVID-19 outbreak has had a profound impact on education worldwide. As a result of the educational institutions closures, it is likely that the impact on special education would be more detrimental since special education population becomes more vulnerable in the aftermath of an outbreak. In the scope of this study, a researcher created survey was used to examine educators’ teaching experiences and their perceptions about the impact of COVID-19 outbreak on special education students. The sample included 215 educators working in the Special Education and Rehabilitation Centers (SERCs) in Turkey. Results indicated that a large majority of the SERCs were not able to continue their education during the COVID-19 outbreak. In addition, there was a difference in educators’ experiences by their educational practices (normal weekly schedule, reduced schedule, most of the educational activities are suspended, and all of the educational activities are suspended). Perceived level of COVID-19 outbreak impact on special education students were found to be significantly higher for autism spectrum disorders, intellectual disabilities, attention deficit and hyperactivity disorders, visual impairments, hearing impairments, specific learning disabilities and gifted students, respectively. The conclusion highlights the need of global collaboration, disaster preparation and management for students with special needs.     

The RIX Wiki: the use of multimedia advocacy to support person-centred planning in a special needs secondary school – implications for current policy and practice

The article documents findings from a pilot study undertaken in 2012–2013 in a special needs secondary school in the England, that trialled the use of a multimedia advocacy tool, “The RIX Wiki”. The trial was part of the pathfinder programme, which aimed to reform existing Special Education Needs provision, from the system of statementing to one of developing education health care plans. The reforms became enshrined in the Children and Families Act (2014). The findings were overall positive and helped with person-centred planning processes. The discussion is framed within current and future policy directives. We argue that multimedia advocacy approaches and software tools, like the “RIX Wiki” will have a continued role to play in ensuring the needs, aspirations and choices of children and young people with learning disabilities remain central.     

新冠肺炎疫情下专业图书馆科研新媒体服务探究——以中国科学院文献情报中心“中国科讯”为例

[目的/意义] 以中国科学院文献情报中心"中国科讯"为例，分析专业图书馆应急科学传播服务的举措及成效，为应急事件下专业图书馆科学传播服务提供借鉴。[方法/过程] 梳理新冠肺炎疫情期间"中国科讯"微信公众号推送的服务内容，从日均用户增长和阅读量分析用户对不同类型内容的关注程度，提出应急科学传播服务的思考。[结果/结论] 疫情期间，"中国科讯"日均用户增长明显，电子资源保障类内容阅读量最高，其次为新冠病毒科技攻关进展相关内容、科普类直播和信息素养教育直播观看人数达到数万人。应急事件下，专业图书馆应加强特色服务的宣传、加强信息甄选和审核机制，重大公共卫生事件下应急科学传播工作预案缺失也需引起重视。     

高职院校学习预警平台的构建及其实证分析

开展信息化、智慧化预警工作是实现全面精准育人的重要途径,而预警应用平台无疑是预警工作的有力工具和实践载体,其设计方案应用效果的好坏直接决定着学习预警信息化愿景的达成度。文章在分析高职院校学习预警工作现状的基础上,从工作流程设计、平台框架设计和平台建设方法等3个方面提出了解决方案,并对平台的应用效果进行了实证分析,结果表明:平台的应用扩展了预警范围、提升了预警的精准度和时效性、提高了工作效率,且干预更为灵活、个性化,可为当前高职院校学习危机的实践改革提供新思路。     

图书馆为区域服务的定位分析与选择

[目的/意义]梳理图书馆与区域的关系,不以简单的服务与被服务进行限定,而从两者包含与互动来认识图书馆为区域服务。[方法/过程]图书馆为区域服务应该从环境与定位入手,重新分析认识图书馆社会职责、重点任务、服务工作内容。[结果/结论]图书馆是区域的组成部分,应以主体意识来发展自己,完善区域构成。图书馆应遵循定位,选准重点建设,筑牢专业的服务基础,为区域的政府决策、科研开发、产业经济、民众生活等提供信息服务。     

Quality flaw prediction in Spanish Wikipedia: A case of study with verifiability flaws

In this work, we present the first quality flaw prediction study for articles containing the two most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any references or sources at all (denominated Unreferenced) and articles that need additional citations for verification (so-called Refimprove). Based on the underlying characteristics of each flaw, different state-of-the-art approaches were evaluated. For articles not citing any references, a well-established rule-based approach was evaluated and interesting findings show that some of them suffer from Refimprove flaw instead. Likewise, for articles that need additional citations for verification, the well-known PU learning and one-class classification approaches were evaluated. Besides, new methods were compared and a new feature was also proposed to model this latter flaw. The results showed that new methods such as under-bagged decision trees with sum or majority voting rules, biased-SVM, and centroid-based balanced SVM, perform best in comparison with the ones previously published.     

基于深度学习的中文专利自动分类方法研究

[目的/意义] 面向当前国内专利审查和专利情报分析工作中对于海量专利分类的客观需求，设计了7种基于深度学习的专利自动分类方法，对比各种方法的分类效果，从而助力专利分类效率和效果的提升。[方法/过程] 针对传统机器学习方法存在的缺陷，基于Word2Vec、CNN、RNN、Attention机制等深度学习技术，考虑专利文本语序特征、上下文特征以及分类关键特征，设计Word2Vec+TextCNN、Word2Vec+GRU、Word2Vec+BiGRU、Word2Vec+BiGRU+TextCNN等7种深度学习模型，以中国专利为例，选取IPC主分类号的"部"作为分类依据，对比这7种模型与3种传统分类模型在中文专利分类任务中的效果。[结果/结论] 实证研究效果显示，采用考虑语序特征、上下文特征及强化关键特征的深度学习方法进行中文专利分类具有更优的分类效果。     

An analysis of review content and reviewer variables that contribute to review helpfulness

Review helpfulness is attracting increasing attention of practitioners and academics. It helps in reducing risks and uncertainty faced by users in online shopping. This study examines uninvestigated variables by looking at not only the review characteristics but also important indicators of reviewers. Several significant review content and two reviewer variables are proposed and an effective review helpfulness prediction model is built using stochastic gradient boosting learning method. This study derived a mechanism to extract novel review content variables from review text. Six popular machine learning models and three real-life Amazon review data sets are used for analysis. Our results are robust to several product categories and along three Amazon review data sets. The results show that review content variables deliver the best performance as compared to the reviewer and state-of-the-art baseline as a standalone model. This study finds that reviewer helpfulness per day and syllables in review text strongly relates to review helpfulness. Moreover, the number of space, aux verb, drives words in review text and productivity score of a reviewer are also effective predictors of review helpfulness. The findings will help customers to write better reviews, help retailers to manage their websites intelligently and aid customers in their product purchasing decisions.     

专题情报数据管理与智能分析平台的构建

[目的/意义] 面对多学科领域、多类型用户的专题情报服务需求，建立专题情报数据管理与智能分析平台。实现专题情报分析的流程化和智能化，同时对融入专家智慧的专题情报分析过程数据进行管理，丰富服务模式，提升服务需求响应速度。[方法/过程] 在调研已有相关研究与实践分析基础上，提出平台设计思路、建设框架，对平台主要功能和关键技术进行剖析。[结果/结论] 专题情报数据管理与智能分析平台已建设完成。平台集成了多来源多类型数据，打通了从数据到分析的服务链条。嵌入了多种情报分析方法和深度学习算法，实现了多维多层次分析服务。能够对分析过程和情报分析人员历史积累数据进行管理，实现数据共享和重复利用。