adaptive software

Nope! Why adaptive software is not the same as personalized learning

How can adaptive software encourage a sense of community, show compassion, teach critical thinking, and foster passion?

Sorry, adaptive software is not the same as personalized learning.

We all know that changes in public education move slowly, but there’s one specific educational dilemma we’ve been mired in for decades, with varying levels of rhetoric and hand-wringing: How can we maximize individual student achievement with group instruction?

This is what Education Secretary Arne Duncan was talking about in 2010 when he called for “transformational productivity reforms that can also boost student outcomes.” Over the last century, we’ve put a lot of effort into solving this problem with varying degrees of success.

Today we see it in the hyperbole around personalization, individualization, standards-based grading, differentiation, etc. It seems as if no conference schedule or edtech brochure is complete without some “New and Improved!” way to increase educational return on investment, the latest of which is “adaptive” learning.

This trend promises to deliver differentiated instruction, personalized to each student, at the optimal time, place and pace. The claims seem almost unbelievable. Not that there isn’t truth to the need for closer-to-individual instruction. On the contrary, this is, in fact, where our focus should lie.

However, the sheer volume of buzz overwhelms, so let’s remember where the personalization-revolution began.

Starting with Personalization Basics

Benjamin Bloom (of Bloom’s Taxonomy fame) had an elegant summary of the problem. He found that the most effective model of instruction is, by definition, individualized. Bloom examined conventional, mastery and 1:1 instruction and discovered that not only is 1:1 vastly superior in improving student achievement, but also that the best performance of students elicited by conventional classroom instruction is on par with the worst performance of students in the 1:1 model.

Notice where the Conventional and Tutorial curves intersect below:

Additionally, the average performance in the tutorial condition exceeds the highest performance in the conventional classroom. Bloom proposed that since most students are able to attain this high level of achievement, the mission of educators is to figure out how to provide 1:1-level results with group instruction. Hence the decades-long “how to scale” personalization dilemma.

(Next page: Where adaptive software plays into personalized learning)

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