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George Bradford

50 most stunning examples of data visualization and infographics | Richworks - 0 views

  • The terms Data visualization and Infographics are used interchangeably, the former means the study of visual representation of data and the latter is its representation per se.
  • 42) Geological Time Spiral
  • 40) Map of online communities
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  • 44) Global distribution of water?
  • 43) 1 hour in front of the TV
  • 36) Evolution of Storage
  • 33) The Life of a web article
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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.
George Bradford

Measuring Teacher Effectiveness - DataQualityCampaign.Org - 0 views

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    Measuring Teacher Effectiveness Significant State Data Capacity is Required to Measure and Improve Teacher Effectiveness  States Increasingly Focus on Improving Teacher Effectiveness: There is significant activity at the local, state, and federal levels to  measure and improve teacher effectiveness, with an unprecedented focus on the use of student achievement as a primary indicator of  effectiveness. > 23 states require that teacher evaluations include evidence of student learning in the form of student growth and/or value-added data (NCTQ, 2011). > 17 states and DC have adopted legislation or regulations that specifically require student achievement and/or student growth to "significantly" inform or be the primary criterion in teacher evaluations(NCTQ, 2011).  States Need Significant Data Capacity to Do This Work: These policy changes have significant data implications. > The linchpin of all these efforts is that states must reliably link students and teachers in ways that capture the complex connections that  exist in schools. > If such data is to be used for high stakes decisions-such as hiring, firing, and tenure-it must be accepted as valid, reliable, and fair. > Teacher effectiveness data can be leveraged to target professional development, inform staffing assignments, tailor classroom instruction,  reflect on practice, support research, and otherwise support teachers.  Federal Policies Are Accelerating State and Local Efforts: Federal policies increasingly support states' efforts to use student  achievement data to measure teacher effectiveness. > Various competitive grant funds, including the Race to the Top grants and the Teacher Incentive Fund, require states to implement teacher  and principal evaluation systems that take student data into account.  > States applying for NCLB waivers, including the 11 that submitted requests in November 2011, must commit to implementing teacher and  principal evaluation and support systems. > P
George Bradford

Data Visualization: Modern Approaches - Smashing Magazine | Smashing Magazine - 0 views

  • 2. Displaying News
  • Digg Stack 15: Digg stories arrange themselves as stack as users digg them. The more diggs a story gets, the larger is the stack.
  • Let’s take a look at the most interesting modern approaches to data visualization as well as related articles, resources and tools.
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  • an application that visually reflects the constantly changing landscape of the Google News news aggregator. The size of data blocks is defined by their popularity at the moment.
  • Digg stories arrange themselves as stack as users digg them. The more diggs a story gets, the larger is the stack.
  • a typographic book search, collects the information from Amazon and presents it in the form of keyword you’ve provided.
  • uses visual hills (spikes) to emphasize the density of American population in its map.
  • lets you explore the behavior of your visitors with a heat map. More popular sections, which are clicked more often, are highlighted as “warm” – in red color.
  • Eric Blue provides some references to unusual Data Visualization methods.
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    Data presentation can be beautiful, elegant and descriptive. There is a variety of conventional ways to visualize data - tables, histograms, pie charts and bar graphs are being used every day, in every project and on every possible occasion. However, to convey a message to your readers effectively, sometimes you need more than just a simple pie chart of your results. In fact, there are much better, profound, creative and absolutely fascinating ways to visualize data. Many of them might become ubiquitous in the next few years.
George Bradford

Using Big Data to Predict Online Student Success | Inside Higher Ed - 0 views

  • Researchers have created a database that measures 33 variables for the online coursework of 640,000 students – a whopping 3 million course-level records.
  • Project Participants American Public University System Community College System of Colorado Rio Salado College University of Hawaii System University of Illinois-Springfield University of Phoenix
  • “What the data seem to suggest, however, is that for students who seem to have a high propensity of dropping out of an online course-based program, the fewer courses they take initially, the better-off they are.”
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  • Phil Ice, vice president of research and development for the American Public University System and the project’s lead investigator.
  • Predictive Analytics Reporting Framework
  • Rio Salado, for example, has used the database to create a student performance tracking system.
  • The two-year college, which is based in Arizona, has a particularly strong online presence for a community college – 43,000 of its students are enrolled in online programs. The new tracking system allows instructors to see a red, yellow or green light for each student’s performance. And students can see their own tracking lights.
  • It measures student engagement through their Web interactions, how often they look at textbooks and whether they respond to feedback from instructors, all in addition to their performance on coursework.
  • The data set has the potential to give institutions sophisticated information about small subsets of students – such as which academic programs are best suited for a 25-year-old male Latino with strength in mathematics
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    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.
George Bradford

Assessment and Analytics in Institutional Transformation (EDUCAUSE Review) | EDUCAUSE - 0 views

  • At the University of Maryland, Baltimore County (UMBC), we believe that process is an important factor in creating cultural change. We thus approach transformational initiatives by using the same scholarly rigor that we expect of any researcher. This involves (1) reviewing the literature and prior work in the area, (2) identifying critical factors and variables, (3) collecting data associated with these critical factors, (4) using rigorous statistical analysis and modeling of the question and factors, (5) developing hypotheses to influence the critical factors, and (6) collecting data based on the changes and assessing the results.
  • among predominantly white higher education institutions in the United States, UMBC has become the leading producer of African-American bachelor’s degree recipients who go on to earn Ph.D.’s in STEM fields. The program has been recognized by the National Science Foundation and the National Academies as a national model.
  • UMBC has recently begun a major effort focused on the success of transfer students in STEM majors. This effort, with pilot funding from the Bill and Melinda Gates Foundation, will look at how universities can partner with community colleges to prepare their graduates to successfully complete a bachelor’s degree in a STEM field.
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  • Too often, IT organizations try to help by providing an analytics “dashboard” designed by a vendor that doesn’t know the institution. As a result, the dashboard indicators don’t focus on those key factors most needed at the institution and quickly become window-dressing.
  • IT organizations can support assessment by showing how data in separate systems can become very useful when captured and correlated. For example, UMBC has spent considerable effort to develop a reporting system based on our learning management system (LMS) data. This effort, led from within the IT organization, has helped the institution find new insights into the way faculty and students are using the LMS and has helped us improve the services we offer. We are now working to integrate this data into our institutional data warehouse and are leveraging access to important demographic data to better assess student risk factors and develop interventions.
  • the purpose of learning analytics is “to observe and understand learning behaviors in order to enable appropriate interventions.
  • the 1st International Conference on Learning Analytics and Knowledge (LAK) was held in Banff, Alberta, Canada, in early 2011 (https://tekri.athabascau.ca/analytics/)
  • At UMBC, we are using analytics and assessment to shine a light on students’ performance and behavior and to support teaching effectiveness. What has made the use of analytics and assessment particularly effective on our campus has been the insistence that all groups—faculty, staff, and students—take ownership of the challenge involving student performance and persistence.
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    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.
George Bradford

[!!!] Penetrating the Fog: Analytics in Learning and Education (EDUCAUSE Review) | EDUC... - 0 views

  • Continued growth in the amount of data creates an environment in which new or novel approaches are required to understand the patterns of value that exist within the data.
  • learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs.
  • Academic analytics, in contrast, is the application of business intelligence in education and emphasizes analytics at institutional, regional, and international levels.
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  • Course-level:
  • Educational data-mining
  • Intelligent curriculum
  • Adaptive content
  • the University of Maryland, Baltimore County (UMBC) Check My Activity tool, allows learners to “compare their own activity . . . against an anonymous summary of their course peers.
  • Mobile devices
  • social media monitoring tools (e.g., Radian6)
  • Analytics in education must be transformative, altering existing teaching, learning, and assessment processes, academic work, and administration.
    • George Bradford
       
      See Bradford - Brief vision of the semantic web as being used to support future learning: http://heybradfords.com/moonlight/research-resources/SemWeb_EducatorsVision 
    • George Bradford
       
      See Peter Goodyear's work on the Ecology of Sustainable e-Learning in Education.
  • How “real time” should analytics be in classroom settings?
  • Adaptive learning
  • EDUCAUSE Review, vol. 46, no. 5 (September/October 2011)
  • Penetrating the Fog: Analytics in Learning and Education
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    Attempts to imagine the future of education often emphasize new technologies-ubiquitous computing devices, flexible classroom designs, and innovative visual displays. But the most dramatic factor shaping the future of higher education is something that we can't actually touch or see: big data and analytics. Basing decisions on data and evidence seems stunningly obvious, and indeed, research indicates that data-driven decision-making improves organizational output and productivity.1 For many leaders in higher education, however, experience and "gut instinct" have a stronger pull.
George Bradford

Eric Blue's Blog » Dataesthetics: The Power and Beauty of Data Visualization - 0 views

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    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!
George Bradford

About | SNAPP - Social Networks Adapting Pedagogical Practice - 3 views

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    "The Social Networks Adapting Pedagogical Practice (SNAPP) tool performs real-time social network analysis and visualization of discussion forum activity within popular commercial and open source Learning Management Systems (LMS). SNAPP essentially serves as a diagnostic instrument, allowing teaching staff to evaluate student behavioral patterns against learning activity design objectives and intervene as required a timely manner. Valuable interaction data is stored within a discussion forum but from the default threaded display of messages it is difficult to determine the level and direction of activity between participants. SNAPP infers relationship ties from the post-reply data and renders a social network diagram below the forum thread. The social network visualization can be filtered based upon user activity and social network data can be exported for further analysis in NetDraw. SNAPP integrates seamlessly with a variety of Learning Management Systems (Blackboard, Moodle and Desire2Learn) and must be triggered while a forum thread is displayed in a Web browser."
George Bradford

College Degrees, Designed by the Numbers - Technology - The Chronicle of Higher Education - 0 views

  • Arizona State's retention rate rose to 84 percent from 77 percent in recent years, a change that the provost credits largely to eAdvisor.
  • Mr. Lange and his colleagues had found that by the eighth day of class, they could predict, with 70-percent accuracy, whether a student would score a C or better. Mr. Lange built a system, rolled out in 2009, that sent professors frequently updated alerts about how well each student was predicted to do, based on course performance and online behavior.
  • Rio Salado knows from its database that students who hand in late assignments and don't log in frequently often fail or withdraw from a course. So the software is more likely to throw up a red flag for current students with those characteristics.
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  • And in a cautionary tale about technical glitches, the college began sharing grade predictions with students last summer, hoping to encourage those lagging behind to step up, but had to shut the alerts down in the spring. Course revisions had skewed the calculations, and some predictions were found to be inaccurate. An internal analysis found no increase in the number of students dropping classes. An improved system is promised for the fall.
  • His software borrows a page from Netflix. It melds each student's transcript with thousands of past students' grades and standardized-test scores to make suggestions. When students log into the online portal, they see 10 "Course Suggestions for You," ranked on a five-star scale. For, say, a health-and-human-performance major, kinesiology might get five stars, as the next class needed for her major. Physics might also top the list, to satisfy a science requirement in the core curriculum.
  • Behind those recommendations is a complex algorithm, but the basics are simple enough. Degree requirements figure in the calculations. So do classes that can be used in many programs, like freshman writing. And the software bumps up courses for which a student might have a talent, by mining their records—grades, high-school grade-point average, ACT scores—and those of others who walked this path before.
  • The software sifts through a database of hundreds of thousands of grades other students have received. It analyzes the historical data to figure out how much weight to assign each piece of the health major's own academic record in forecasting how she will do in a particular course. Success in math is strongly predictive of success in physics, for example. So if her transcript and ACT score indicate a history of doing well in math, physics would probably be recommended over biology, though both satisfy the same core science requirement.
  • Every year, students in Tennessee lose their state scholarships because they fall a hair short of the GPA cutoff, Mr. Denley says, a financial swing that "massively changes their likelihood of graduating."
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    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.
George Bradford

Many Eyes - 0 views

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    Try yourself: Explore ::Visualizations :: Data sets :: Comments :: Topic centers Participate :: Create a visualization :: Upload a data set :: Create a topic center Learn more :: Quick start :: Visualization types :: About Many Eyes :: Privacy :: Blog
George Bradford

Features | Gephi, open source graph visualization software - 0 views

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    Features Gephi is a tool for people that have to explore and understand graphs. Like Photoshop but for data, the user interacts with the representation, manipulate the structures, shapes and colors to reveal hidden properties. The goal is to help data analysts to make hypothesis, intuitively discover patterns, isolate structure singularities or faults during data sourcing. It is a complementary tool to traditional statistics, as visual thinking with interactive interfaces is now recognized to facilitate reasoning. This is a software for Exploratory Data Analysis, a paradigm appeared in the Visual Analytics field of research.
George Bradford

Cohere >>> make the connection - 0 views

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    About Cohere The Web is about IDEAS+PEOPLE. Cohere is a visual tool to create, connect and share Ideas. Back them up with websites. Support or challenge them. Embed them to spread virally. Discover who - literally - connects with your thinking. Publish ideas and optionally add relevant websites Weave webs of meaningful connections between ideas: your own and the world's Discover new ideas and people We experience the information ocean as streams of media fragments, flowing past us in every modality. To make sense of these, learners, researchers and analysts must organise them into coherent patterns. Cohere is an idea management tool for you to annotate URLs with ideas, and weave meaningful connections between ideas for personal, team or social use. Key Features Annotate a URL with any number of Ideas, or vice-versa. Visualize your network as it grows Make connections between your Ideas, or Ideas that anyone else has made public or shared with you via a common Group Use Groups to organise your Ideas and Connections by project, and to manage access-rights Import your data as RSS feeds (eg. bookmarks or blog posts), to convert them to Ideas, ready for connecting Use the RESTful API services to query, edit and mashup data from other tools Learn More Subscribe to our Blog to track developments as they happen. Read this article to learn more about the design of Cohere to support dialogue and debate.
George Bradford

Open Research Online - Learning dispositions and transferable competencies: pedagogy, m... - 0 views

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    Theoretical and empirical evidence in the learning sciences substantiates the view that deep engagement in learning is a function of a complex combination of learners' identities, dispositions, values, attitudes and skills. When these are fragile, learners struggle to achieve their potential in conventional assessments, and critically, are not prepared for the novelty and complexity of the challenges they will meet in the workplace, and the many other spheres of life which require personal qualities such as resilience, critical thinking and collaboration skills. To date, the learning analytics research and development communities have not addressed how these complex concepts can be modelled and analysed, and how more traditional social science data analysis can support and be enhanced by learning analytics. We report progress in the design and implementation of learning analytics based on a research validated multidimensional construct termed "learning power". We describe, for the first time, a learning analytics infrastructure for gathering data at scale, managing stakeholder permissions, the range of analytics that it supports from real time summaries to exploratory research, and a particular visual analytic which has been shown to have demonstrable impact on learners. We conclude by summarising the ongoing research and development programme and identifying the challenges of integrating traditional social science research, with learning analytics and modelling.
George Bradford

Discussions - Learning Analytics | Google Groups - 0 views

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    Flare at Purdue in October    Hi everyone. Can someone provide more information for the upcoming SoLAR FLARE event at Purdue in October? Thanks, Kelvin Bentley By Kelvin Bentley  - May 14 - 2 new of 2 messages - Report as spam     EDUCAUSE Survey on Analytics - Looking for International Input    Colleagues, EDUCAUSE is soliciting input on analytics in higher education. They have currently sent email to their current members, but are looking for additional participation from the international community. We would greatly appreciate if you could complete the survey below. -- john... more » By John Campbell - Purdue  - May 11 - 2 new of 2 messages - Report as spam     CFP: #Influence12: Symposium & Workshop on Measuring Influence on Social Media    Hi Everyone, If you are interested in Learning Analytics and Social Media, I invite you to submit a short position paper or poster to the Symposium & Workshop on Measuring Influence on Social Media. The event is set for September 28-29, 2012 in beautiful Halifax, Nova Scotia, Canada. All submissions are due *June 15, 2012*.... more » By Anatoliy Gruzd  - May 11 - 2 new of 2 messages - Report as spam     LA beginnings    Learning Analytics isn't really new, it is just getting more publicity now as a result of the buzz word name change. Institutions have been collecting data about students for a long time, but only a few people dealt with the data. Instructors kept gradebooks and many tracked student progress locally - by hand. What's new about Learning... more »
George Bradford

Many Eyes : Browsing visualizations - 0 views

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    Listing visualizations of data. IBM Research and the IBM Cognos experiment.
George Bradford

Information graphics - Wikipedia, the free encyclopedia - 0 views

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    Information graphics or infographics are graphic visual representations of information, data or knowledge. These graphics present complex information quickly and clearly,[1] such as in signs, maps, journalism, technical writing, and education. With an information graphic, computer scientists, mathematicians, and statisticians develop and communicate concepts using a single symbol to process information.
George Bradford

Stunning Infographics and Data Visualization - Noupe - 1 views

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    Creating an effective infographic requires both artistic sense and a clear vision of what to tell the audience. The following are some cool infographics we have collected. Some are colorful, some are simple, but all are informative and visually pleasing. Not only do they provide information in a format that is easy to understand, but they are also artistic creations in their own right.
George Bradford

Browse Maps - Places & Spaces: Mapping Science - 0 views

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    Data Visualizations - Organized by KATY BÖRNER
George Bradford

American Statistical Association seeks to usher in new era of statistical significance - 0 views

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    "The American Statistical Association seeks to embrace science's inherent complexity and push for more data transparency by rejecting a common, oversimplified measure of statistical significance. March 15, 2016 By Colleen Flaherty Is the tyrannical reign of the P value finally ending (if it was ever tyrannical at all)? An unprecedented statement from the American Statistical Association seeks to usher in a "post-P
George Bradford

Open Research Online - Learning analytics to identify exploratory dialogue within synch... - 0 views

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    While generic web analytics tend to focus on easily harvested quantitative data, Learning Analytics will often seek qualitative understanding of the context and meaning of this information. This is critical in the case of dialogue, which may be employed to share knowledge and jointly construct understandings, but which also involves many superficial exchanges. Previous studies have validated a particular pattern of "exploratory dialogue" in learning environments to signify sharing, challenge, evaluation and careful consideration by participants. This study investigates the use of sociocultural discourse analysis to analyse synchronous text chat during an online conference. Key words and phrases indicative of exploratory dialogue were identified in these exchanges, and peaks of exploratory dialogue were associated with periods set aside for discussion and keynote speakers. Fewer individuals posted at these times, but meaningful discussion outweighed trivial exchanges. If further analysis confirms the validity of these markers as learning analytics, they could be used by recommendation engines to support learners and teachers in locating dialogue exchanges where deeper learning appears to be taking place.
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