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  • Teaching Machines: Learning from the Intersection of Education and Technology by Bill Ferster
  • Claire Laville (bio)
Bill Ferster, Teaching Machines: Learning from the Intersection of Education and Technology. Baltimore: Johns Hopkins University Press, 2014, 216pp. $34.95 cloth.

Every week, someone announces that Massive Open Online Courses (MOOCs), video games, body-monitoring devices, or some other innovation is about to transform schooling as we know it. Two memorable promises can often be detected under the bombast: that we might finally tear down the economic and geographic barriers to a quality education; and that education has finally caught up with science. Those two aspirations are older than computing. Bill Ferster’s Teaching Machines: Learning from the Intersection of Education and Technology takes a refreshingly inclusive look at scientifically driven educational reform in the United States since the nineteenth century. Ferster is a professor of education and a programmer whose projects include interactive visualization tools for historians and K-12 teachers. One of his strengths is to bring a technologist’s perspectives to initiatives that were not initially conceived as technological. This provides Teaching Machines with an eclectic, yet focused archive. According to Ferster, a teaching machine is any object or method that delivers both curricular content and pedagogy and requires no direction from a “live” teacher. Most books are not teaching machines, but a textbook with quiz and activity sections is. In this way Ferster draws out the continuities between improvised, low-tech solutions operations and today’s networked learning environments.

What Ferster calls his “odd kind of pessimism” toward his topic is not at all polemical (p. ix). He takes up the ideas of sociologist Everett Rogers to show why so many experiments failed, and why even the successful ones never had the transformative effect they promised. Rogers’s “diffusion of innovations” theory states that a successful technology must be relatively easy to use (low complexity), and that individuals should be able to actually see the thing and try it out (observability, trialability). So far, so good, but compatibility with the existing system turns out to be something of a constraint. As Ferster notes, we will surely miss the full potential of the internet as an educational tool if we constantly try to recreate the classroom. The most obvious factor behind a technology’s success, a high relative advantage, is harder to gauge here than in the marketplace. Is the new tool significantly better than what came before—in this case, being in the same room as a teacher? The guiding principles of U.S. education have shifted, along with trends in developmental psychology. For that reason the story of teaching machines is also a selective history of the sciences of mind in the twentieth century.

From their beginnings teaching machines stood in an ambivalent relation toward standardization. American schools did not begin to divide students by age until the mid-nineteenth century; by 1920 age-grading had become the norm. Sidney Pressey, [End Page 109] one of the psychologists caught up in the post–World War I vogue for intelligence testing, rejected the practice of age-grading almost immediately. In his view, age stratification would leave the weaker students lagging behind and the more adept ones perpetually bored. His Automatic Teacher was a self-scoring, multiple-choice test originally made from of old typewriter parts. It encapsulates the contradictions involved in trying to meld early behaviorism and Dewey-style experientialism. The machine was supposed to “drill material more efficiently . . . than the ‘human machine,’” as he wrote, yet he hoped it would actually mitigate the assembly-line feel of modern schools. It would “leave the teacher more free for her [sic] most important work” of nurturing the student’s character (pp. 55–56). But this progressive moment in educational technology was short-lived, largely because of the high costs of building and promoting the new gadgets. The teaching-machine idea lay dormant until the next generation of behaviorists, led by B. F. Skinner, revived it.

Skinner looms large in the history of modern education, and Ferster’s understated sense of humor is a good fit for the “small, hubris-filled world” of Harvard behaviorism (his father, Charles Ferster...


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pp. 109-111
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