基于观众对话的博物馆学习研究新视角——来自苏·艾伦研究成果的启发          下载免费PDF全文

胡龙超 《自然科学博物馆研究》2023,(2):15-22

观众在博物馆中如何学习、学习效果如何评量等问题长期受到研究者的关注。观众对话作为参观学习的体现,是探究博物馆学习过程的重要材料。基于此,苏·艾伦采用社会文化视角,透过参观过程中的观众对话寻找学习的证据。本文主要目的是介绍该研究的研究问题、研究发现、方法论框架、数据收集与分析等方面的内容,以期为国内博物馆观众研究领域提供一种新的视角。  相似文献   

Measuring the promise of Big Data syllabi     

Alon Friedman 《Technology, Pedagogy and Education》2018,27(2):135-148

Growing interest in Big Data is leading industries, academics and governments to accelerate Big Data research. However, how teachers should teach Big Data has not been fully examined. This article suggests criteria for redesigning Big Data syllabi in public and private degree-awarding higher education establishments. The author conducted a survey of 35 Big Data syllabi across different academic institutions in the USA using Palmer, Bach, and Streifer’s rubric criteria. The role of syllabi in higher education has an established tradition in summarising topics covered in a single course and textbook, and in referencing the instructor’s resources. Yet, despite the central role of course resources, the present study did not find a common textbook. The majority of resources referenced were academic articles and blog postings used by the instructors and other professionals in the field. Based on Palmer et al.’s score rubric, this study found that many of the syllabi broke down the main ideas of Big Data into smaller content items using interpretations of the instructor’s subject knowledge. The study recommends that Big Data instructors need to provide a better breakdown of each component of the syllabus to reflect a clear understanding of grades and resources available on the subject. Future studies also need to examine students’ expectations of those classes.  相似文献   

The data scientist profile and its representativeness in the European e-Competence framework and the skills framework for the information age     

《International Journal of Information Management》2017,37(6):726-734

The activities in our current world are mainly supported by data-driven web applications, making extensive use of databases and data services. Such phenomenon led to the rise of Data Scientists as professionals of major relevance, which extract value from data and create state-of-the-art data artifacts that generate even more increased value. During the last years, the term Data Scientist attracted significant attention. Consequently, it is relevant to understand its origin, knowledge base and skills set, in order to adequately describe its profile and distinguish it from others like Business Analyst. This work proposes a conceptual model for the professional profile of a Data Scientist and evaluates the representativeness of this profile in two commonly recognized competences/skills frameworks in the field of Information and Communications Technology (ICT), namely in the European e-Competence (e-CF) framework and the Skills Framework for the Information Age (SFIA). The results indicate that a significant part of the knowledge base and skills set of Data Scientists are related with ICT competences/skills, including programming, machine learning and databases. The Data Scientist professional profile has an adequate representativeness in these two frameworks, but it is mainly seen as a multi-disciplinary profile, combining contributes from different areas, such as computer science, statistics and mathematics.  相似文献   

Open data: Quality over quantity     

《International Journal of Information Management》2017,37(3):150-154

Open data aims to unlock the innovation potential of businesses, governments, and entrepreneurs, yet it also harbours significant challenges for its effective use. While numerous innovation successes exist that are based on the open data paradigm, there is uncertainty over the data quality of such datasets. This data quality uncertainty is a threat to the value that can be generated from such data. Data quality has been studied extensively over many decades and many approaches to data quality management have been proposed. However, these approaches are typically based on datasets internal to organizations, with known metadata, and domain knowledge of the data semantics. Open data, on the other hand, are often unfamiliar to the user and may lack metadata. The aim of this research note is to outline the challenges in dealing with data quality of open datasets, and to set an agenda for future research to address this risk to deriving value from open data investments.  相似文献   

关于中国微生物组数据中心建设的思考          下载免费PDF全文

马俊才  赵方庆  苏晓泉  徐健  吴林寰 《中国科学院院刊》2017,32(3):290-296

近年来,美国、欧盟都陆续启动了微生物组相关的研究项目。但微生物组大数据的收集、存储、功能挖掘和开发利用一直是制约微生物组发展的核心问题。文章分析了我国目前在微生物组数据管理中存在着标准不统一、缺乏跨领域的数据整合、高质量的参考数据库和数据的深度挖掘技术等问题,提出适时启动"中国微生物组"计划,建立中国微生物组数据中心,在微生物组数据标准化的基础上,建立微生物组大数据计算、存储和共享平台,开发微生物组大数据挖掘的新方法,实现我国微生物组数据资源的系统管理和高效利用。  相似文献   

大数据治理的概念与要素探析   总被引：1，自引：0，他引：1  

郑大庆 《科技管理研究》2017,(15)

随着信息、连接和计算能力这三大要素变得更加经济和便利,大数据应用将会变得越来越普及,如何发挥大数据应用的作用正是大数据治理关注的问题。从目的、权利层次、对象和解决的实际问题4个方面深入探析大数据治理的内涵,分析大数据治理应重点关注的领域,构建大数据治理框架,并进一步讨论大数据治理面临的挑战。论文在大数据治理内涵剖析和大数据要素框架构建方面作出新的尝试,以期为后续研究提供参考。  相似文献   

人力资本与欧盟区域创新活动研究——基于探索性空间数据分析和地理加权回归模型     

张涵 《科技管理研究》2017,(19)

运用探索性空间数据分析和地理加权回归方法,实证分析2008—2015年欧盟28个成员国人力资本要素的空间相关性及其对欧盟区域创新产出的影响。研究发现:第一,虽然人力资本要素存在空间相关性,但是正呈现扩散趋势;第二,不同国家的人力资本要素存在不同空间集聚模式;第三,欧盟多数国家的人力资本对专利申请量有正向作用,25~34岁博士毕业生数/千人对欧盟区域创新产出的正向作用最为突出,其次是非欧洲籍博士生比重和30~34岁受过高等教育人口比重,而20~24岁高中以上学历人口比重的推动作用有限,甚至会产生抑制作用。  相似文献   

所得税优惠对高新技术企业R&D的影响——以福建省上市高新技术企业为分析对象     

刘效梅 《科技管理研究》2017,(21)

用面板数据模型分析福建省上市高新技术企业2010—2015年的年度数据,以研究所得税优惠对企业RD的影响,发现所得税优惠总体上对企业研发投入强度的促进作用较小,对劳动力密集型企业和国有及国有控股企业的研发强度有一定的消极作用,对企业申请的专利数无影响。所得税优惠对RD的激励效果与企业年龄负相关。为了增强优惠政策效果,需要严格高新技术企业的认定和管理,协调好具有重叠效果的激励政策,激励方案要考虑企业的主要投入要素、所有制性质以及存续年限等差异。  相似文献   

Exploring benchmark corporations in the semiconductor industry based on efficiency     

Chia-Han Tsai  Hung-Yi Wu  I-Shuo Chen  Jui-Kuei Chen  Rih-Wei Ye 《The Journal of High Technology Management Research》2017,28(2):188-207

The aim of this study is to explore benchmark corporations in the semiconductor industry based on efficiency. In this study, perspectives of intellectual capital and corporate governance are taken into account for the input data, whereas firm value is considered as the output data. Data envelope analysis (DEA), including CCR and BCC models, is utilized to ensure that the benchmark standards are precisely selected. Based on the result, suggestions for both semiconductor corporations and future research are provided at the end of this article.  相似文献   

Using information gain to improve multi-modal information retrieval systems     

M.T. Martín-Valdivia  M.C. Díaz-GalianoA. Montejo-Raez  L.A. Ureña-López 《Information processing & management》2008

Nowadays, access to information requires managing multimedia databases effectively, and so, multi-modal retrieval techniques (particularly images retrieval) have become an active research direction. In the past few years, a lot of content-based image retrieval (CBIR) systems have been developed. However, despite the progress achieved in the CBIR, the retrieval accuracy of current systems is still limited and often worse than only textual information retrieval systems. In this paper, we propose to combine content-based and text-based approaches to multi-modal retrieval in order to achieve better results and overcome the lacks of these techniques when they are taken separately. For this purpose, we use a medical collection that includes both images and non-structured text. We retrieve images from a CBIR system and textual information through a traditional information retrieval system. Then, we combine the results obtained from both systems in order to improve the final performance. Furthermore, we use the information gain (IG) measure to reduce and improve the textual information included in multi-modal information retrieval systems. We have carried out several experiments that combine this reduction technique with a visual and textual information merger. The results obtained are highly promising and show the profit obtained when textual information is managed to improve conventional multi-modal systems.  相似文献