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Lossless Learning: an Interview with Jared Stein of Instructure

http://www.hybridpedagogy.com/page-two/lossless-learning-interview-jared-stein

The idea of “lossless learning” was inspired at first by a desire to think differently about some of the fundamental concepts we take for granted in education, like transmission and reception of information, in order to help teachers and technologists find new ways forward.

Like most ideas, we arrived at this metaphor from many different conversations and research threads serendipitously coming together over an extended period of time. I do remember Josh Coates and I talking about the potential of big data – truly big data from a cloud-native learning platform like Canvas. Canvas has a tremendous amount of data, more than we currently know what to do with. So how do you make that much learning data actionable in a way that is both reliable and meaningful? How do you know which data is important and which is not? Is it even the right data? I’d been reading and writing on blended learning for a while, and the lack of data in face-to-face was foremost on my mind. Josh related the challenge of lossiness in data storage, situations where the quality of information is lost — sometimes inadvertently, but sometimes to gain a benefit elsewhere, like in size or speed. This idea of educational lossiness — accidental or planned — lined up with the notion in blended education that you lose something when you move from teaching face-to-face to teaching online — and vice versa. And we were off.

The important thing about the idea of lossless learning is that it’s not just about some new tools or feature’s we’ve added to Canvas, it’s about how technology in general can help capture important information that would have been otherwise lost, and thereby lead to improvements in the quality of the learning experience. My hope is that by paying attention to education’s tendency toward lossiness, educators and technologists will find a fresh way to reflect on the information that is either captured and sacrificed in any learning experience in order to re-evaluate and iterate learning design for greater effectiveness and efficiency.