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Effective visual representations can help higher education bridge silos and unleash the power of data. 
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If you think data—in education, or any field—is cut and dry, think again. Working with data in the classroom, especially, can be either exhausting o
Peter Mellow's insight:
A nice collection of articles about the different ways you can use data in education.
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Four years after the launch of edX, the data generated by massive open online courses still mystifies many institutions. Could inter-university collaboration unlock the secrets to better course delivery?
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"Learning Analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs." Via Beth Dichter, Pauline Farrell
Beth Dichter's curator insight,
July 18, 2014 11:05 PM
This detailed infographic provides an in-depth look at learning analytics. It begins by describing traditional education as a school bus, with the expectation that all students will get to "the finish line together." The infographic then turns to personalized learning, where students would work at their pace and in their way to master material. Analytics play a key role in personalized education. Why? If you use a tool that provides you with the ability to measure, collect, analyze and report data about your students you have the opportunity to adapt curriculum. The infographic shares seven areas that may be considered. From here the infographic moves to the learning analytics cycle which moves to four areas: * Descriptive - What has happened? * Diagnostic - Why has it happened? * Predictive - What will happen? * Prescriptive - What should I do? What comes next? The role of the teacher, which is followed by a What's Next section. There is much to learn about learning analytics in this infographic. You may download the complete infographic from the site. 
miguel a. rodriguez's curator insight,
July 19, 2014 5:24 AM
Interesante infografia de google analytics 
John Lemos Forman's curator insight,
July 20, 2014 10:55 PM
Muita expectativa mas ainda poucos resultados concretos ... De qualquer modo, esta se formando uma percepção de que o modelo educacional vai ser fortemente impactado nos próximos anos
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Schools and universities pump lots of time and money into collecting data on learning analytics, but there is no research to show that such data actually helps to improve learning outcomes.
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Data visualization expert Stephen Few said, “Numbers have an important story to tell. They rely on you to give them a clear and convincing voice.” With the influx of data and introduction of self-service analytics tools, we're going to need more people capable of communicating insights effectively. The next generation of data storytellers will not be limited to just analysts and data scientists. Everyone will need to know how to tell a story with numbers.
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The American Council on Education’s (ACE) Center for Policy Research and Strategy (CPRS) released a new report with support from TIAA Institute, “Evolving Higher Education Business Models: Leading with Data to Deliver Results.”
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Three higher ed chief data officers discuss the state of analytics at their institutions.
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Content mining of archival materials can make for amazing discoveries. Here's how to prepare for the coming influx of researchers who will want access to digital archives as a data source.
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Designing a textbook or lecture with the average student in mind may sound logical. But L. Todd Rose, who teaches educational neuroscience at Harvard University’s Graduate School of Education, argues that doing so means that the lesson is designed for nobody.
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Raquel Oliveira's curator insight,
January 27, 2014 10:22 AM
a humanidade clama por ser envolvida nas decisoes, projetos e aprendizagem. Sim, eu sinto esse movimento em diversos setores. Em relação a aprendizagem de adultos, é irreversível !
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Although states are doing a masterful job of accumulating data and integrating data sources to support education improvement, according to a new report, the next part of the job may be their toughest yet: teaching people how to use the data.
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Netflix meets Google meets academia. Data mining is reshaping the college experience.
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The higher education community must set the table and invite others to help us define ethical practice and responsible use of student data in the rapi
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If you think data—in education, or any field—is cut and dry, think again. Working with data in the classroom, especially, can be either exhausting or exhilarating—depending on your fitness level. Data can be big, but also quite small. It’s often quantitative, but is increasingly qualitative. It’s pr
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In short, we want educational predictions to be wrong. If our predictive model can tell that a student is going to fail, we want that to be true only in the absence of intervention. If the student does in fact fail, that should be seen as a failure of the system. A predictive model should be part of a prediction-and-response system that (1) makes predictions that would be accurate in the absence of a response and (2) enables a response that renders the prediction incorrect (e.g., to accurately predict that, given a specific intervention, the student will succeed). In a good prediction-and-response system, all predictions would ultimately be negatively biased. The best way to empirically demonstrate this is to exploit random variation in the assignment of the system—for example, random assignment of the prediction-and-response system to some students but not all. This approach is rarely used in residential higher education but is newly enabled by digital data.The grand challenge in data-intensive research and analysis in higher education is to find the means to extract knowledge from the extremely rich data sets being generated today and to distill this into usable information for students, instructors, and the public.
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Jenny Rankin in her TEDxTUM Talk on Education Data puts forward various examples on how heroes effectively used data to communicate various messages..
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U of California at San Diego's new early warning system aims to condense millions of data points into a simple metric showing whether students will graduate on time.
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Researchers can now access de-identified learning data from more than 230 massive open online courses (MOOCs) hosted on Instructure's Canvas Network.
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We spoke with dozens of educators across a range of schools—from mainstream to technology-forward—and we conducted an online survey with a nationally representative sample of 4,600 public school teachers.
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This fall, Oral Roberts University (OK) issued Fitbits to on-campus students and Garmin vivofits to online students — part of the "whole person" philosophy at the Tulsa-based institution that urges students to be "well prepared" physically. The data generated by those activity trackers on movement, heart rate and sleep patterns drizzles automatically into the university's D2L gradebook in time for settling up midterm grades and finals. The results are displayed through D2L for faculty and students, just as if they were weekly quiz grades. The Garmin device, added CIO Mike Mathews, syncs with an online service that allows students to set goals and share progress with others.
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Massive open online course providers are collecting troves of data about their students, but what good is it if researchers can't use the information?
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Denver — Data mining is creeping into every aspect of student life—classrooms, advising, socializing. Now it’s hitting textbooks, too.
CourseSmart, which sells digital versions of textbooks by big publishers, announced on Wednesday a new tool to help professors and others measure students’ engagement with electronic course materials.
When students use print textbooks, professors can’t track their reading. But as learning shifts online, everything students do in digital spaces can be monitored, including the intimate details of their reading habits.
KF: See ryanbretag's comments on this at: http://wp.me/pXQaZ-Wt
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