2013/05/24 by Sandra Y. Okita, Daniel L. Schwartz
Computer Science · Psychology · #Innovative Teaching and Learning Methods #Intelligent Tutoring Systems and Adaptive Learning #Online Learning and Analytics
paper · doi:10.1080/10508406.2013.807263
openalex publication_date 2013/05/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
Feedback is important for learning. However, there are different types of feedback, and not all feedback is effective. Here we introduce recursive feedback (RF), which occurs when tutors observe their pupils use what they have been taught. Two experiments examined the value of RF during learning by teaching. In the first study adults taught another adult face to face about human biology. Those participants who observed their pupil interact with an examiner exhibited superior learning relative to individuals in several control conditions that included elements of learning by teaching but not RF. The second study examined whether RF benefits extend to teaching computerized teachable agents in regular classrooms. High school students played games in which they induced logical rules. Students taught their agent the governing rules. They received RF when they observed their teachable agent play a prediction game against a second competitor agent. On a posttest, these students exhibited greater abilities to use logic to solve novel problems compared to students in control conditions who received direct feedback by playing against the competitor agent themselves. RF may further generalize to nonteaching situations that also involve a production–appropriation cycle, such as do-it-yourself projects in which people have a chance to learn from how other people take up their handiwork.