Matsuda, N., Sekar, V. P. C., & Wall, N. (2018 to appear). Metacognitive scaffolding amplifies the effect of learning by teaching a teachable agent. In B. McLaren & B. du Boulay (Eds.), Proceedings of the International Conference on Artificial Intelligence in Education.

Abstract: Learning by teaching has been compared with learning by being tu- tored, aka cognitive tutoring, to learn algebra linear equations for 7th to 8th grade algebra. Two randomized-controlled trials with 46 and 141 6th through 8th grade students were conducted in 3 public schools in two different years. Students in the learning by teaching (LBT) condition used an online learning environment (APLUS), where they interactively taught a teachable agent (SimStudent) how to solve equations with a goal to have the teachable agent pass the quiz. Students in the learning by being tutored condition used a version of cognitive tutor that uses the same user interface as APLUS, but no teachable agent. Instead, a teacher agent tutored students how to solve equations. The goal for students in this con- dition was to pass the quiz by themselves. Students selected and entered prob- lems to be tutored by themselves. This condition is hence called Goal-Oriented Practice (GOP). For both conditions, students received metacognitive scaffolding on how to teach the teachable agent (LBT) and how to regulate their learning (GOP). The results from the classroom studies show that (1) students in both con- ditions learned equally well, measured as pre- and post-test scores, (2) prior com- petency does not influence the effect of LBT nor GOP (i.e., no aptitude-treatment interaction observed), and (3) GOP students primarily focused on submitting the quiz rather than practicing on problems. These results suggest that with the met- acognitive scaffolding, learning by teaching is equally effective as cognitive tu- toring regardless of the prior competency.