Learning analytics can be like shining a flashlight into a deep cave.
In an instant, access to data about teaching and learning practices illuminates facts about actual behavior that would otherwise be left to speculation and anecdote. But just as we need multiple light sources to shed light into the many caverns that connect to a single cave, collecting data from multiple learning tools has traditionally involved aggregating a series of independent data extraction processes.
As learning management systems (LMS) become next generation learning environments (NGLE), they increasingly function as hubs for connecting a wide variety of other learning technologies. But, in their current state, educational tools vary widely in terms of the kinds of data they collect, and in the extent to which they make their data available to other systems.
I remember looking at LMS data in Blackboard when I was a scholar in residence at Emory University. It was both fascinating and frustrating to look at interaction data and see the moments when students would ‘disappear’ into the cavern of another educational technology, only to ‘reappear’ after much time had passed.
Because of Learning Tools Interoperability ® (LTI®), the experience of users was seamless, but interaction data was sequestered. Educational technologies were shaking hands, but they weren’t communicating.
In order to get a fuller picture of student activity, what this meant for me as a researcher was that I had to write complex queries that pulled, structured, and integrated data from multiple independent data sources. But even this was only possible in a limited number of cases. Our lecture capture technology, for example, was a very fruitful source of data, but my level of database access was a function of the fact that we were self-hosted. Had this technology been hosted in the cloud, it would have been all but impossible to see what was going on with our students, to fully support instructional design practices, and to optimize ROI on our educational technology investment.
IMS Caliper Analytics™ & Kaltura: A Proof of Concept
Just as the LTI standard from the IMS Global Learning Consortium® has meant that students can now have a seamless experience across multiple tools within a single environment, the release of the Caliper 1.0 standard means that institutions will increasingly be able to get a full picture of their students’ learning activity.
As a proof of concept, Blackboard recently worked with Kaltura to add Caliper MediaEvent support, so that teachers could see combined activity data from Blackboard Learn and Kaltura in a single dashboard within Blackboard Learn.
The full integration process was recently described in a technical white paper by Mike Sharkey (Vice President of Analytics, Blackboard) and Jeff Rubinstein (Vice President of Product, Katura). By demonstrating the tremendous potential of this kind of data-integration, they hope to encourage more wide-spread adoption of the IMS Caliper standard:
“This educational analytics strategy will provide benefit to teachers, institutional researchers, and heads of programs using richly designed online curricula and tools that provide access to more student activity information in a familiar interface, regardless of the tool that provides the learning material. As these kinds of integrations become more widespread, Caliper-based solutions like this have the potential to alleviate the existing data silo problem and give all those supporting student learning a much more complete picture of student activity, with less friction and difficulty in mining the data.”
As a result of our work with Kaltura, customers operating Blackboard Learn SaaS with the latest version of the Kaltura Building Block automatically receive this new teacher-facing Student Activity visualization without any additional cost or technical work requirements. The nature of the IMS Caliper standard is also such that data sharing between systems will become even richer as features are added and improved.
Transforming the student experience
At Blackboard, we believe that data and analytics have the potential to transform every part of the student experience, but this kind of transformation is only possible as a result of transparency and interoperability. We are committed to each of these values, and are actively looking to for partners interested in working with us to overcome data silos and serve students better. This kind of work is also important for institutions concerned about ‘lock-in.’ Colleges and universities need to choose their educational technologies according to what best meet the needs of their students, and they should not need to worry about sacrificing data-quality for user experience.
