Learning Analytics, Educational Data Mining, Adaptive Learning

There’s a counter-intuitive downside to collecting vast amounts of information about economics and human behaviour: it can mean we ignore the lessons of history.

The college classroom has been impenetrable for those seeking to understand how students learn. This was more a function of the traditional methods of teaching and learning than a result of any intentional barriers. Student behaviors were fairly opaque—some note taking, possibly classroom discuss

A university that has been testing out the use of an analytics infrastructure to improve student outcomes and retention has reported positive results, including improvements in attendance, course drop rates and course success.

Strayer University, a for-profit institution with about 43,000 on-campus and online students in its fall 2015 enrollment, has been working with analytics software from Civitas Learning, including Student Insights Platform and Inspire for Faculty. The first is an online program that integrates and analyzes data from multiple sources and applies predictive analytics to provide users with information about student behavior and engagement. The second helps instructors pinpoint those students who are doing well and those who are struggling in order to target outreach and interactions.

Higher education information technology must strategize to catch up with current business information technology.

Plans to reward universities for excellent teaching could see a bigger role for metrics that track how students spend their time.

Whether they like it or not, members of the educational technology community and faculty members should engage in debates about learning analytics algorithms, transparency and data access. That was the message delivered by George Siemens, executive director of the Learning Innovation and Networked Knowledge Research Lab (LINK) at the University of Texas at Arlington, during a recent Future Trends Forum discussion with futurist Bryan Alexander.

"You can hate something and still recognize that it is an important factor to think about," Siemens stressed. "You can think analytics are crap, but you can't deny they are influential. If we want a future that embodies values that are important to us, then we have to be active participants in the sociotechnical and economic spaces driving that change."

So why should you consider moving to the xAPI?
In addition to the items I've already mentioned, there are a number of advantages to using the xAPI. I've listed a few below:

You can provide detailed test results and the report results for multiple test scores
It will work outside of a browser or an LMS
You have more control over your content
You can easily transition from computers to mobile devices and you can use mobile apps for learning detailed results can be tracked from more in-depth games and simulations
You can track real-world performance. Say that you're running separate security tests that relate to training you are providing to your employees. You can have the results of those tests linked to their course; then adapt course content for those specific learners.
You can track the results form interactive learning objects and adaptive learning modules that are delivered based on a learners specific learning path.
The xAPI also makes it possible to learn over long periods of time as well as support team-based learning activities 

Higher education needs to actively participate in discussions around learning analytics algorithms, transparency and data access, says UT Arlington's George Siemens.

Learning analytics is an emerging, highly interdisciplinary field where many disciplines--such as education, computer science, and engineering--intersect. Since its first significant scholarly gathering in 2011, learning analytics has been increasingly mentioned in news, technical reports, academic publications, and grant solicitations. The surge of this nascent field rests on a promise--and also a premise--that digital traces of learning could be turned into actionable knowledge to promote learning and teaching.

Strayer University has recently gone public with a partnership designed to help identify factors that contribute to success for students in online courses.

"Developed in collaboration with student-success analytics innovator Civitas Learning, the findings often buck conventional wisdom, suggesting that data captured through a student's digital footprints can provide better predictors of success than the typical demographic data points," according to a news release.

Over several years, the university partnered with Civitas to aggregate relevant data from disparate sources in the company's Student Insights Platform. The data was then used to identify initiatives that seemed most promising in engaging students and faculty, improving behavioral mindsets and closing the gap between in-person and online learning.

Most of the more than 40,000 students enrolled at Strayer University in any given semester take classes online. They’re typically working adults who learn asynchronously, participating in lectures and assignments at different times that fit their busy schedules. Strayer is betting big on data ana

When we published “Disrupting Class” in 2008, we didn’t use the phrase “adaptive learning” once in the book. Just eight years later, it’s nearly impossible to imagine writing a book about educational technology and neglecting the term.

With the rapid growth of blended learning and technology more generally in schools, asking if educational software is capable of adapting to students’ needs is commonplace.

Teachers are increasingly attempting to reach each of their students who have distinct learning needs, at different times, with the right learning experience at the right time. Having effective adaptive software turbocharges those efforts and can provide a realistic pathway to accomplish that goal.

The basic idea of my bachelor thesis was to track the ping pong ball in realtime to create data visualisations for trainers and players. After a few weeks of working I started developing a projected mapped interface for the ping pong table to show the collected data. By projecting game obstacles on the surface I figured out that I can change the game play totally.