How Learning Organizations Turn LMS Data Into Intelligence

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How Learning Organizations Turn LMS Data Into Intelligence
“Swarm Intelligence” by Steve Jurvetson is licensed under CC BY 2.0

A brief survey on what you can call the “next gen” in learning technology suggests that everything is moving in one direction: Analytics. LMS Data is the current term among solution providers who promise the ability to draw from many sources to generate insights and “learn about learning.”

WIRIS

Some learning organizations have actually shown progress and, over the course of several years, have successfully implemented an analytics practice that has gone beyond displaying student outcomes. Today, it is a standard step in many current operations and is key in the design of future innovations. But is there a standardized practice in analytics? How can anyone go from LMS Data to Intelligence?

What to distinguish first

One of the first pieces of insight a learning organization gains from LMS data is clarity about the differences in learning patterns among students. This can cover their preferred mediums and schedules, but can also expand to the kinds of interactions that challenge them best. Having a sense of these profiles should entice the organization into asking bolder questions, even at the risk of highlighting the “overwhelming” breadth of possibilities that intelligence systems seem to offer.

This can lead to a “second-stage” realization: The need for tools that help refine and discard interventions and practices that give LMS Data a clear role in the operation and development of learning interventions. Another word for it is “risk management.” Once a system can serve the unique needs of each student, it becomes easier to identify and use to address the smaller pool that is still likely to under-perform. While some cases could be remedied through direct intervention (i.e. one-on-one sessions), data can also help design future courses to prevent “last resort” measures and benefit all students.

It doesn’t matter where, just knowing is the right direction

As the evidence-based methods become more prominent (and, consequently, more effective), the focus of a “Data to Intelligence” path might face new priorities. This is not only fine, but expected. If the starting team has the process fine-tuned (including quality assurance and similar third-party verifications), it is time to “sell” the proposition of LMS data to the community at large and ensure as many individuals as possible come on board. Persuasion techniques should not be out of the question: promotion, and even gamification, activities targeted to teachers and staff can make sure new behaviors are adopted quickly, and over time people acquire a general attitude of openness towards LMS data and the value of its insights, even in moments of setback.

Learning organizations that kick start narrative paths like this one will be ready to embrace more ambitious, sophisticated, even real-time operations that take LMS data as the core of a “learning as a mission” mantra. Of course, a fully-featured LMS that supports analytics and deeper learning system integration, like Moodle, is always welcome.

 


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