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hansdezwart

elearnspace › What are Learning Analytics? - 0 views

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    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.
hansdezwart

Event - Innovation at Google: the physics of data - PARC, a Xerox company - 0 views

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    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.
hansdezwart

InfoQ: Machine Learning: A Love Story - 0 views

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    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.
hansdezwart

Deciphering the social media genome: Toward an ecology of social roles in online collab... - 2 views

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    These, and other similar projects, promise the emergence of a new social and theoretical paradigm whose goal is to decipher the web of social interactions generated by social media.
Tony Searl

Conor Williams: Educational Productivity and the Reform Wars - 0 views

  • data difficulties in "some" cases hardly eviscerate a study of "more than 9,000 districts that enroll more than 85 percent of all U.S. students."
  • Poverty does not make productive, efficient education impossible.
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    data was hard to come by in some districts, it was untrustworthy in others and controlling for all relevant variables when comparing school districts is really, really difficult.
hansdezwart

Introduction to Linked Open Data for Visualization Creators on Datavisualization.ch - 0 views

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    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.
hansdezwart

SEO, the Semantic Web and Information Discovery - 0 views

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    The father of the World Wide Web, Tim Berners-Lee defines the Semantic Web as "a web of data that can be processed directly and indirectly by machines."
hansdezwart

http://www.ifets.info/journals/11_3/16.pdf - 0 views

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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. 
hansdezwart

Gapminder Desktop - Gapminder.org - 0 views

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    With Gapminder Desktop you can show animated statistics from your own laptop
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