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50 MOST STUNNING EXAMPLES OF DATA VISUALIZATION AND INFOGRAPHICS Posted by Richie on Thursday, April 15, 2010 "A picture is worth a thousand words", if I had a penny for every time I heard that!! There is so much data in the world today that it has become impossible for us to analyze them with patience. Data as we perceive it, need not be boring, bland and cumbersome to remember. To make complex things seem simple, is Creativity and using pictures to represent data has been an age old method to analyze data in a fun way. From navigating the web in an entirely new dimension to understanding how the human brain works; from peeking into how Google has evolved to analyzing the inner working of the geeky mind, Infographics has completely changed the way we view content and visualize data.

"Examples of Direct and Indirect Measures Examples of Direct Measures of Student Learning"

Drawing on sociocultural discourse analysis and argumentation theory, we motivate a focus on learners' discourse as a promising site for identifying patterns of activity which correspond to meaningful learning and knowledge construction. However, software platforms must gain access to qualitative information about the rhetorical dimensions to discourse contributions to enable such analytics. This is difficult to extract from naturally occurring text, but the emergence of more-structured annotation and deliberation platforms for learning makes such information available. Using the Cohere web application as a research vehicle, we present examples of analytics at the level of individual learners and groups, showing conceptual and social network patterns, which we propose as indicators of meaningful learning.

People | Member | Simon Buckingham Shum Snr Lecturer in Knowledge Media I am fundamentally interested in technologies for sensemaking, specifically, which structure discourse to assist reflection and analysis. Examples: D3E, Compendium, ClaiMaker and Cohere.

One of my areas of interest that has grown over the last couple years has been data visualization. I'm a visually-oriented learner, and I look forward to seeing any techniques, illustrations, or technologies that: 1) Allow people to assimilate information as fast as possible. 2) Deepen understanding of knowledge by visually illustrating data in new and interesting ways. There is nothing like having an intellectual epiphony after looking at a picture for a few seconds (pictures can definitely be worth a thousand words). 3) Present information in an aesthetically pleasing way. Or, in extreme examples, inspire a sense of awe!

"   Welcome to the Program Evaluation Standards, 3rd Edition   Standards Names and Statements Errata Sheet for the book   After seven years of systematic effort and much study, the 3rd edition of the Program Evaluation Standards was published this fall by Sage Publishers: http://www.sagepub.com/booksProdDesc.nav?prodId=Book230597&_requestid=255617. The development process relied on formal and informal needs assessments, reviews of existing scholarship, and the involvement of more than 400 stakeholders in national and international reviews, field trials, and national hearings. It's the first revision of the standards in 17 years. This third edition is similar to the previous two editions (1981, 1994) in many respects, for example, the book is organized into the same four dimensions of evaluation quality (utility, feasibility, propriety, and accuracy). It also still includes the popular and useful "Functional Table of Standards," a glossary, extensive documentation, information about how to apply the standards, and numerous case applications."

"Introduction In this discussion paper, we define learning process analytics as a collection of methods that allow teachers and learners to understand what is going on in a' 'learning scenario, i.e. what participants work(ed) on, how they interact(ed), what they produced(ed), what tools they use(ed), in which physical and virtual location, etc. Learning analytics is most often aimed at generating predictive models of general student behavior. So-called academic analytics even aims to improve the system. We are trying to find a solution to a somewhat different problem. In this paper we will focus on improving project-oriented learner-centered designs, i.e. a family of educational designs that include any or some of knowledge-building, writing-to-learn, project-based learning, inquiry learning, problem-based learning and so forth. We will first provide a short literature review of learning process analytics and related frameworks that can help improve the quality of educational scenarios. We will then describe a few project-oriented educational scenarios that are implemented in various programs at the University of Geneva. These examples illustrate the kind of learning scenarios we have in mind and help define the different types of analytics both learners and teachers need. Finally, we present a provisional list of analytics desiderata divided into "wanted tomorrow" and "nice to have in the future"."

Assessment and analytics, supported by information technology, can change institutional culture and drive the transformation in student retention, graduation, and success. U.S. higher education has an extraordinary record of accomplishment in preparing students for leadership, in serving as a wellspring of research and creative endeavor, and in providing public service. Despite this success, colleges and universities are facing an unprecedented set of challenges. To maintain the country's global preeminence, those of us in higher education are being called on to expand the number of students we educate, increase the proportion of students in science, technology, engineering, and mathematics (STEM), and address the pervasive and long-standing underrepresentation of minorities who earn college degrees-all at a time when budgets are being reduced and questions about institutional efficiency and effectiveness are being raised.

New students are more likely to drop out of online colleges if they take full courseloads than if they enroll part time, according to findings from a research project that is challenging conventional wisdom about student success. But perhaps more important than that potentially game-changing nugget, researchers said, is how the project has chipped away at skepticism in higher education about the power of "big data." Researchers have created a database that measures 33 variables for the online coursework of 640,000 students - a whopping 3 million course-level records. While the work is far from complete, the variables help track student performance and retention across a broad range of demographic factors. The data can show what works at a specific type of institution, and what doesn't. That sort of predictive analytics has long been embraced by corporations, but not so much by the academy. The ongoing data-mining effort, which was kicked off last year with a $1 million grant from the Bill and Melinda Gates Foundation, is being led by WCET, the WICHE Cooperative for Educational Technologies.

July 18, 2012 College Degrees, Designed by the Numbers By Marc Parry Illustration by Randy Lyhus for The Chronicle Campuses are places of intuition and serendipity: A professor senses confusion on a student's face and repeats his point; a student majors in psychology after a roommate takes a course; two freshmen meet on the quad and eventually become husband and wife. Now imagine hard data substituting for happenstance. As Katye Allisone, a freshman at Arizona State University, hunkers down in a computer lab for an 8:35 a.m. math class, the Web-based course watches her back. Answers, scores, pace, click paths-it hoovers up information, like Google. But rather than personalizing search results, data shape Ms. Allisone's class according to her understanding of the material.