A content analysis of top-ranked universities’ mission statements from five global regions

In general, a mission statement reflects the context in which a higher education institution operates. It’s also a direction setting statement indicating the direction required for effective strategic and operational decisions. This study examines how the highest ranked universities in Europe, Asia, Latin America, Africa, and North America compare in terms of their mission statements and how they communicate to their stakeholders and to the public about what their main purposes, values, goals, and objectives are. Having downloaded each university’s mission statement from the Internet, we then classified them into five main categories of Asian, African, European, Latin American, and North American universities and analyzed them separately using the text mining and analysis tools available in SAS Enterprise Miner, a powerful commercial business analytics program. Results show that although we found similar terms and themes in the mission statements across the five different regions, there is great variability in the mission statements with respect to how they communicate their core values, main purposes, and value propositions.     

Causal aware parameterized quantum stochastic gradient descent for analyzing marketing advertisements and sales forecasting

Nowadays, all marketing companies are focusing on advertisements to maximize their sales and profit. Media mix models are used by advertisers to measure how advertisements would effectively, attract and motivate the consumers to buy their brands. However, due to large number of media mix variables, it is difficult to use these media mix models for producing reliable approximation, extending these approximations to infer causation (not as correlation), and parameterizing these models to handle the complex marketing interactions between consumers. In this work, we develop a novel model integrating causal inference analysis with a parameterized quantum stochastic gradient descent model to assess the relation between the marketing advertisements and sales forecasting. The proposed causal aware PQSGD model is experimented on two different media mix variables datasets. The proposed model outperforms the existing quantum approaches (Quantum linear/lasso regression, Quantum decision tree, Quantum LightGBM, Quantum random forest regressor) by achieving the MSE values of 4.36 for Dataset 1 and 19.24 for Dataset 2.     

Efficient querying of multidimensional RDF data with aggregates: Comparing NoSQL,RDF and relational data stores

This paper proposes an approach to tackle the problem of querying large volume of statistical RDF data. Our approach relies on pre-aggregation strategies to better manage the analysis of this kind of data. Specifically, we define a conceptual model to represent original RDF data with aggregates in a multidimensional structure. A set of translations rules for converting a well-known multidimensional RDF modelling vocabulary into the proposed conceptual model is then proposed. We implement the conceptual model in six different data stores: two RDF triple stores (Jena TDB and Virtuoso), one graph-oriented NoSQL database (Neo4j), one column-oriented data store (Cassandra), and two relational databases (MySQL and PostGreSQL). We compare the querying performance, with and without aggregates, in these data stores. Experimental results, on real-world datasets containing 81.92 million triplets, show that pre-aggregation allows for reducing query runtime in all data stores. Neo4j NoSQL and relational databases with aggregates outperform triple stores speeding up to 99% query runtime.     

Data entry: towards the critical study of digital data and education

The generation and processing of data through digital technologies is an integral element of contemporary society, as reflected in recent debates over online data privacy, ‘Big Data’ and the rise of data mining and analytics in business, science and government. This paper outlines the significance of digital data within education, arguing for increased interest in the topic from educational researchers. Building on themes from the emerging sub-field of ‘digital sociology’, the paper outlines a number of ways in which digital data in education could be questioned along social lines. These include issues of data inequalities, the role of data in managerialist modes of organisation and control, the rise of so-called ‘dataveillance' and the reductionist nature of data-based representation. The paper concludes with a set of suggestions for future research and discussion, thus outlining the beginnings of a framework for the future critical study of digital data and education.     

学习分析：教育信息化的新浪潮

教育信息化经历了学习管理系统（LMS）以及Web2.0应用的变革。新技术的深入应用带来了教育＂大数据＂的高速增长,挖掘这些教育数据潜在价值的迫切需求,使得学习分析应运而生。通过文献分析法,对国内外学习分析文献进行了分析和综述,首先对学习分析进行了概念界定和历史溯源,比较了与学习分析相关概念的区别和联系,之后针对学习分析作为教育信息化新热点,对其研究、发展、技术策略等方面进行了较系统地阐释,最后总结了学习分析目前面临的挑战和愿景,以期可以对学习分析进行全方位的阐述和梳理,并促进该领域的深入研究。     

MOOCs的本土化诉求及其应对

近年来,简称为MOOCs的大规模开放在线课程受到国内外教育研究者的普遍关注。由Coursera、edX和Udacity等组成的MOOCs联盟几乎成为了聚集国际顶级大学的俱乐部,给世界各国高等教育带来极大冲击以及参与的压力。在中国的知名高校开始加入这些顶级大学俱乐部的同时,更多的是跃跃欲试地进行大规模开放在线课程的本土化尝试。面对MOOCs的这一本地化发展态势和现状,审视当前大规模开放在线课程的本地化吁求,对如何实现本土化的大规模开放在线课程进行了分析,并针对大规模开放在线课程所引发的真正的挑战以及如何应对这些挑战等问题展开了讨论。     

An overview of learning analytics

Learning analytics, the analysis and representation of data about learners in order to improve learning, is a new lens through which teachers can understand education. It is rooted in the dramatic increase in the quantity of data about learners and linked to management approaches that focus on quantitative metrics, which are sometimes antithetical to an educational sense of teaching. However, learning analytics offers new routes for teachers to understand their students and, hence, to make effective use of their limited resources. This paper explores these issues and describes a series of examples of learning analytics to illustrate the potential. It argues that teachers can and should engage with learning analytics as a way of influencing the metrics agenda towards richer conceptions of learning and to improve their teaching.     

LIBRARY SERVICE TO THE DISABLED

Recent legislation has mandated equal rights for disabled people and an appropriate education for all disabled children. All professions are upgrading service, making architectural adaptations for the physically disabled, and adapting programs to the needs of this important segment of the population. The library profession needs to deuelop information and referral collections for disabled persons, learn about special curriculum materiales for disabled children, and deuelop the new field of "Rehabilitation Librarianship," since many rehabilitation facilities do not yet haue trained librarians on their staffs. Most important information is to be found in periodicals and newsletters. This bibliography offers a basic listing of journals in the fields of medical and uocational rehabilitation, special education, and journals written for disabled people themsleues. Existing data bases are mentioned and the continuing need for a central information clearinghouse cited.     

Measuring Law Library Catalog Web Site Usability: A Web Analytic Approach

ABSTRACT

Although there is a proliferation of information available on the Web, and law professors, students, and other users have a variety of channels to locate information and complete their research activities, the law library catalog still remains an important source for offering users access to information that has been evaluated and cataloged by experts. The usability of the catalog needs to be effectively measured before any necessary improvements can be made. This study was undertaken to investigate the information retrieval patterns of users of the Rutgers Law Library Online Public Access Catalog and to develop the catalog into a more effective search tool for these users. This study used an experimental approach to measure the usability of our catalog by analyzing the transaction logs from the OPAC system and the results from Google Analytics. The findings provided not only important information on user demographics and their computer systems, but also more insight on the search behaviors of users. The specific findings included the following:

1. As a Web-analytic tool Google Analytics provided extensive information on the OPAC and the navigational behaviors of users.

2. Fifty-eight percent of our users visited the Web site regularly.

3. The most popular search method, which was employed by 37% of our users, was by title.

4. Most patrons used computer systems with a high resolution and color depth monitor and visited the catalog Web site with a high-speed Internet connection.

5. Suggestions were made by the authors to improve the users’ search experience of the catalog Web site.

This study is significant to libraries with Web catalogs because it demonstrates the potential value of using Google Analytics as a Web analytics tool in combination with the OPAC transaction logs to measure catalog usability.     

Networked Learning and Learning Analytics: A Study on the Employment of Facebook in a Virtual Training Program

The growing popularity of Social Networking Sites (SNS) that are embedded with networked infrastructures serves as an ideal platform for developing a networked learning environment connecting geographically dispersed learners. Unlike the traditional learning systems which provide only limited sources of data, the learners engaged in virtual networked social environments tend to produce huge volumes of digital footprints that cannot be analyzed using conventional analytical techniques. Two new branches of analytical sciences – Educational Data Mining (EDM) and Learning Analytics (LA) – are being employed for processing digital data derived from online educational platforms in order to obtain meaningful inferences and data-driven insights.

Hence, the present experimental study involving a small group of geographically dispersed learners intend to examine the engagement level and interaction patterns that occur within a feminist networked learning environment created in Facebook using popular EDM and learning analytical techniques such as K-means Clustering, Social network analysis and correlation mining. Upon analysis, it was found that the peer network influence played a vital role in activating passive learners, eventually leading to the development of a closely bound networked learning community over time.