Why history matters: A review of Watters's <i>Teaching Machines, the History of Personalized Learning</i>

Elcoro (2024) read Watters’s book on teaching machines and wrote a short review. The goal was to remind behavior analysts where personalized learning really started.

The paper walks through the 1950s and 1960s, when B. F. Skinner, Susan Markle, and Kent Wyckoff built the first teaching machines. It shows how their work shaped today’s computer lessons.

Markle and Wyckoff get little credit today, yet they wrote the rules for good program design. Their rules still work: small steps, instant feedback, and proof that each student masters each step.

The review argues that forgetting these pioneers leads to weak online lessons. Knowing the history helps you spot and fix bad programs.

van Timmeren et al. (2016) extends the same idea. They show how Florida Tech used those old rules to grow a huge ABA training program. History guided real-world scaling.

Danforth (2011) and Danforth et al. (2010) use the same method—digging through old speeches—to show how Kirk’s labels hurt kids with intellectual disability. Both papers say: look back before you act now.

McComas et al. (2025) sounds like a contradiction. They warn that early ABA held ableist views. Elcoro’s piece is celebratory. The gap is about focus: Elcoro praises teaching tech, McComas critiques social goals. Both agree we must learn from history, not repeat it.

Next time you write a task analysis or build an online module, borrow the old checks: Does each frame teach one small thing? Does the learner get immediate feedback? Credit Markle and Wyckoff when you train staff or pitch a new app. History gives you evidence—and credibility.