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"IN-SPIRE™ -- an information visualization software application -- provides a wealth of tools for exploring textual information, including query, subset, and trend analysis tools. Through visual representations of information, users can rapidly discover hidden information relationships from a variety of data sources such as technical and patent literature, marketing and business documents, web data, accident and safety reports, newswire feeds and e-mail message traffic."

Information has gone from scarce to superabundant. That brings huge new benefits, says Kenneth Cukier (interviewed here)-but also big headaches

Learning analytics is the use of intelligent data, learner-produced data, and analysis models to discover information and social connections, and to predict and advise on learning. EDUCAUSE's Next Generation learning initiative offers a slightly different definition "the use of data and models to predict student progress and performance, and the ability to act on that information". Their definition is cleaner than the one I offer, but, as I'll detail below, is intended to work within the existing educational system, rather than to modify it. I'm interested in how learning analytics can restructure the process of teaching, learning, and administration.

As the integration of community-centred teaching practices intensifies, an understanding of the types of relationships that manifest in this network and the associated impact on student learning is required. This paper explores the relationship between a student's position in a classroom social network and their reported level of sense of community. Quantitative methods, such as Rovai's (2002b) Classroom Community Scale and social network centrality measures, were incorporated to evaluate an individual's level of sense of community and their position within the classroom social network. Qualitative methods such as discussion forum content analysis and student interviews were adopted to clarify and further inform this relationship. The results demonstrate that the centrality measures of  closeness and  degrees are positive predictors of an individual's reported sense of community whereas,  betweenness indicates a negative correlation. Qualitative analyses indicate that an individual's pre-existing external social network influences the type of support and information exchanges an individual requires and therefore, the degree of sense of community ultimately experienced. The paper concludes by discussing future recommendations for teaching practices incorporating computer-mediated communications. 

"This study analyzes the outcomes at more than 380 higher education institutions. It looks at what the chosen strategies have accomplished, in what ways institutions use the data they collect, whether institutions are investing more resources in tools that enable them to collect and manipulate management information, and the degree to which information and analysis are being used to support institutional decision making."

Social network analysis [SNA] is the mapping and measuring of relationships and flows between people, groups, organizations, computers, URLs, and other connected information/knowledge entities. The nodes in the network are the people and groups while the links show relationships or flows between the nodes. SNA provides both a visual and a mathematical analysis of human relationships. Management consultants use this methodology with their business clients and call it Organizational Network Analysis [ONA].

Among the greatest innovations might be the advent of real-time analytics, which allow the processing of information in real time to enable instantaneous decision-making.

Data analytics is shorthand for the method of warehousing, organizing, and interpreting the massive amounts of data accrued by online learning platforms and student information systems - now as elemental to higher education as classrooms and filing cabinets - in hopes of learning more about what makes students successful, then giving instructors (and the platforms themselves) the chance to nudge those students accordingly.

With so many websites to join, users must decide where to invest significant time in adding their same connections over and over. For developers, this means it is difficult to build successful web applications that hinge upon a critical mass of users for content and interaction. With the Social Graph API, developers can now utilize public connections their users have already created in other web services. It makes information about public connections between people easily available and useful.

Goodhart's law states that once a social or economic indicator or other surrogate measure is made a target for the purpose of conducting social or economic policy, then it will lose the information content that would qualify it to play such a role.

Data is present in all the systems and processes in the world. IBM helps analyze this multitude of information to make intelligent decisions, while enabling business efficiency and adding value to many industries.

With so much technology and networking available at such low cost, what wouldn't you enhance? What wouldn't you connect? What information wouldn't you mine for insight? What service wouldn't you provide a customer, a citizen, a student or a patient?

Today, we measure the size of the Web in exabytes and are uploading to it 15 times more data than we were 3 years ago. Technologies for sensing, storing, and sharing information are driving innovation in the tools available to help us understand our world in greater detail and accuracy than ever before. The implications of analyzing data on a massive scale transcend the tech industry, impacting the environmental sector, social justice issues, health and science research, and more. When coupled with astute technical insight, data is dynamic, accessible, and ultimately, creative. Marissa Mayer will speak to the power of data and the role it plays in Google's innovation. She will present on the technology trends that are changing our relationship with data, discuss fresh Google products that creatively put data to work, and offer her vision for the future of data in driving the Web forward.

Hilary Mason presents the history of machine learning covering some of the most significant developments taking place over the last two decades, especially the fundamental math and algorithmic tools employed. She also exemplifies how machine learning is used by bit.ly to discover various statistical information about users.

Last week ReadWriteWeb asked: "Is Linked Data Gaining Acceptance?" Our answer: definitely yes. Projects like DBPedia, a community effort to structure the information from Wikipedia and provide it as Linked Open Data, have come a long way and work really well. For example, you can search for all scientists born in Zürich, Switzerland.

The British universities, Oxford and Cambridge included, are under siege from a system of state control that is undermining the one thing upon which their worldwide reputation depends: the caliber of their scholarship. The theories and practices that are driving this assault are mostly American in origin, conceived in American business schools and management consulting firms. They are frequently embedded in intensive management systems that make use of information technology (IT) marketed by corporations such as IBM, Oracle, and SAP. They are then sold to clients such as the UK government and its bureaucracies, including the universities. This alliance between the public and private sector has become a threat to academic freedom in the UK, and a warning to the American academy about how its own freedoms can be threatened.

DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link other data sets on the Web to Wikipedia data.

For the past several years, EDUCAUSE publications have described the emergence of two complementary forces: (1) the growth of "academic analytics" in higher education and the knowledge services needed to support seamless sharing and leveraging of contextualized data/information; and (2) the escalating accountability demands that are driving performance measurement and improvement initiatives. These forces converged in the July/August 2007 issue of EDUCAUSE Review, which showcased their potentially transformative impacts on higher education

Knowledge Cartography: Software Tools and Mapping Techniques. (Eds.) Okada, A., Buckingham Shum, S. and Sherborne, T. Springer: Advanced Information and Knowledge Processing Series. ISBN: 978-1-84800-148-0"