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TPR (Total Physical Response) is a methodology for teaching foreign languages. In traditional TPR, teachers need to spend a considerable amount of time confirming the accuracy of students’ movements, which results in a low-efficiency teaching process and affects the fairness of student learning. A motion sensing system can assess the accuracy of body movements and guide students’ movements immediately after detecting them. Hence, in this study, an artificial intelligence (AI) motion sensing teaching system that combines gesture detection and French learning was written in Python. The system was then used to understand the effectiveness of different teaching methods among kinesthetic or non-kinesthetic students in French learning. Further, a delay test was conducted to assess learning retention. There were significant differences in the effects of the interaction between instructional methodologies and learning style tendency on learning retention. By connecting gestures, words, and sounds, students in the group that used the French TPRAI motion sensing teaching system were able to recall what they had learned through body movements on the delay test 14 days after the post-test to retain learning.

Artificial intelligence learning approach through total physical response embodiment teaching on French vocabulary learning retention