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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. 

NodeXL is a template for Excel 2007 and 2010 that lets you enter a network edge list, click a button, and see the network graph, all in the Excel window. You can easily customize the graph's appearance; zoom, scale and pan the graph; dynamically filter vertices and edges; alter the graph's layout; find clusters of related vertices; and calculate a set of graph metrics. Networks can be imported from and exported to a variety of data formats, and built-in connections for getting networks from Twitter, Flickr, YouTube, and your local email are provided.

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.

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.

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].

Papamitsiou, Z., & Economides, A. (2014). Learning Analytics and Educational Data Mining in Practice: A Systematic Literature Review of Empirical Evidence. Educational Technology & Society, 17 (4), 49-64. This paper aims to provide the reader with a comprehensive background for understanding current knowledge on Learning Analytics (LA) and Educational Data Mining (EDM) and its impact on adaptive learning. It constitutes an overview of empirical evidence behind key objectives of the potential adoption of LA/EDM in generic educational strategic planning. We examined the literature on experimental case studies conducted in the domain during the past six years (2008-2013). Search terms identified 209 mature pieces of research work, but inclusion criteria limited the key studies to 40. We analyzed the research questions, methodology and findings of these published papers and categorized them accordingly. We used non-statistical methods to evaluate and interpret findings of the collected studies. The results have highlighted four distinct major directions of the LA/EDM empirical research. We discuss on the emerged added value of LA/EDM research and highlight the significance of further implications. Finally, we set our thoughts on possible uncharted key questions to investigate both from pedagogical and technical considerations.

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.

The plan unveiled on Thursday designates money to create a "dashboard"-an interactive, online database-to give students, parents, and legislators access to detailed measures of departments' and colleges' productivity and efficiency. Data on individual professors will probably also be included, although Dr. Cigarroa stressed that each campus would be able to develop its own system of metrics and the details have not yet been worked out

Needlebase allows you to view web pages through a virtual browser, point and click to train it in understanding what fields on that page are of interest to you and how those fields relate to each other. Then the program goes and scrapes the data from all of those fields, publishes them into a table, list or map, and recommends merges of cells that appear to be mistakenly separate. It's very cool and it lets non-technical people do things with data quickly and easily that we used to require the assistance of someone more technical to do.

SDArch - Semantic Document Architecture is our atempt to bring the vision of the Semantic Web to desktop office-like documents. SDArch aims at enabling desktop document data to be efficiently discovered, linked and shared across application, enterprise and community boundaries. It introduces 'semantic documents' as completely open and queryable resources, containing data which is uniquely identified, semantically annotated and understandable by both humans and software agents.

"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."

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.

I've been following developments in intelligent tutoring systems for a while,  and find it interesting to see how researchers are combining artificial intelligence, learning theory, affective computing, and sensor networks to create applications that might prove to be useful and effective.

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

NetMiner is an innovative software tool for Exploratory Analysis and Visualization of Network Data. NetMiner allows you to explore your network data visually and interactively, and helps you to detect underlying patterns and structures of the network

BusinessWeek's 2006 Cover Story, "Math Will Rock Your World," announced a new age of numbers. With the rise of new networks, the story argued, all of us were channeling the details of our lives into vast databases. Every credit-card purchase, every cell-phone call, every click on the computer mouse fed these digital troves. Those with the tools and skills to make sense of them could begin to decipher our movements, desires, diseases, and shopping habits-and predict our behavior. This promised to transform business and society. In a book expanding upon this Cover Story, The Numerati, Senior Writer Stephen Baker introduces us to the mathematical wizards who are digging through our data to decode us as patients, shoppers, voters, potential terrorists-even lovers.

Academic analytics helps address the public's desire for institutional accountability with regard to student success, given the widespread concern over the cost of higher education and the difficult economic and budgetary conditions prevailing worldwide. Purdue University's Signals project applies the principles of analytics widely used in business intelligence circles to the problem of improving student success within a course and, hence, improving the institution's retention and graduation rates over time.

Demdex captures behavioral data on behalf of Websites and advertisers and stores it in a "behavioral data bank." The company then score each user across more than 40 behavioral and demographic variables to come up with a "traitweight," which helps websites segment their audiences better and advertisers target their messages more exactly.

Singapore's government has also provided substantial support for the Living Analytics Research Centre. The Centre, a research partnership between Carnegie Mellon and Singapore Management University, "seeks to make Singapore one of the world's premier locations for the development and applied use of real-time consumer and social analytics, as well as one of the world's leading centres for computational social science related R&D and education."

The Bill & Melinda Gates Foundation, the world's largest philanthropy, and the foundation associated with Pearson, the giant textbook and school technology company, announced a partnership on Wednesday to create online reading and math courses aligned with the new academic standards that some 40 states have adopted in recent months.