Re-blogged from “The Rise of the Machines: Big data, learning analytics, and adaptive learning.”

There is a long history of teaching machines—mechanical, multimedia, and computers—extending back to an 1809 patent for an educational appliance for the teaching of reading. By 1936, there were nearly seven hundred patents for teaching devices. The history of these devices can be traced from the original patented machines of the nineteenth century through the teaching/testing devices of Sidney Pressey in the 1920s to the more sophisticated teaching machines of Harvard psychologist B.F. Skinner in the 1950s.

Where initial devices were more about testing, late-twentieth-century efforts focused on teaching that enables students to adapt to machine-provided feedback. B.F. Skinner created a mechanical “teaching machine” in the mid-1950s that broke learning into sequenced steps and allowed students to pace themselves as they worked through a series of questions. The steps resembled processes that tutors use to engage students and guide them, via feedback, toward increasingly accurate responses and new knowledge. The machine posed questions and offered new questions only when the student answered correctly; an incorrect answer caused the machine to repeat the question. Skinner’s efforts eventually fell out of favor in part because few companies were willing to invest in designing and developing materials for a product with an indeterminate future, but interest in adaptive learning persisted through the latter half of the century with the emergence of affordable personal computers.

Contemporary instructional designers adhere to Skinner’s basic tenets, offering adaptive learning tools that present course materials to students who do not move on to subsequent questions until their performance, based on data generated in the adaptive learning process, indicates competency and knowledge. Adaptive learning combines individualized instruction (or rather, something that feels like it to the student), peer interaction, effective and engaging simulations, and applications that dynamically adapt to the learner’s abilities.

Re-blogged from “The Rise of the Machines: Big data, learning analytics, and adaptive learning.”


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