Learning Analytics, Educational Data Mining, Adaptive Learning

Graph databases and graph-processing applications have been popping up all over the place lately, and now they’re starting to go commercial. On Tuesday, popular open source project GraphLab joined the ranks of graph startups.

Kate Crawford of the MIT Centre for Civic Media goes behind the numbers to debunk five myths about big data.

The use of big data and analytics to predict student success presents unique ethical questions for higher education administrators relating to the nature of knowledge; in education, "to know" entails an obligation to act on behalf of the student. The Potter Box framework can help administrators address these questions and provide a framework for action.

Big data, big money, big skill set now required. Universities are on it.

Students' online academic activities are used to predict which students are most likely to fail.

Nine universities are testing technology that allows them to track their students’ progress with digital textbooks.

Higher education is a big business, and colleges and universities need reliable data to inform decisions that impact thousands of students and faculty each day.

Nine universities are testing technology that allows them to track their students’ progress with digital textbooks.

In our digital world, social relations have become mediated by data. Without even realizing it, we’re barricading ourselves against strangeness -- people and ideas that don't fit the patterns of who we already know, what we already like and where we’ve already been. A call for technology to deliver us to what and who we need, even if it’s unfamiliar. (Filmed at TED@Intel.)

A principal engineer at Intel, Maria Bezaitis focuses on how constellations of personal data can form new business models.

The promoters of big data would like us to believe that behind the lines of code and vast databases lie objective and universal insights into patterns of human behavior, be it consumer spending, criminal or terrorist acts, healthy habits, or employee productivity. But many big-data evangelists avoid taking a hard look at the weaknesses. Numbers can't speak for themselves, and data sets -- no matter their scale -- are still objects of human design. The tools of big-data science, such as the Apache Hadoop software framework, do not immunize us from skews, gaps, and faulty assumptions. Those factors are particularly significant when big data tries to reflect the social world we live in, yet we can often be fooled into thinking that the results are somehow more objective than human opinions. Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.

Schools put CourseSmart‘s big data analytics to work monitoring student engagement of assigned course materials. Earlier, we mentioned Desire2Learn, which analyzes student performance on the course level to improve graduation rates. Here’s a look at CourseSmart that crunches ebook usage by students so teachers can parse engagement through reports like the one excerpted above (full report at The Times).

Collecting data and statistics is nothing new in education. Educators have been using Blackboard’s analytics software for years. But what is new is the sheer amount of predictive analytics that is available. President Obama recently announced that he wants America’s college graduate ranking to go from 12th place in the world last year to first by 2020. To accomplish this, our nation’s schools and educators will need to harness the power of big data – at least that’s what Toronto-based education startup Desire2Learn says.