Using an AI-Based Object Detection Translation Application for English Vocabulary Learning

Abstract

This study aimed to examine the effects of an AI-based object detection translation (AI-based ODT) application (app) on EFL students’ vocabulary learning. We developed a system that utilized strategies to facilitate learners’ vocabulary learning. The app applied dual code theory to present the objects in picture, word, and pronunciation formats. Seventy-two elementary school students were divided into lower-ability and higher-ability groups according to their English proficiency, and were then randomly assigned to the control and experimental conditions based on their ability. The learners’ learning performance in the control and experimental conditions was compared using a pre-test–post-test design. Through two-way ANOVA analysis, we observed that in the experimental group the higher-ability students benefited more from the AI-based ODT app technology than did the lower-ability students. This significant difference could be taken as evidence of the positive effect of the AI-based ODT app technology, particularly for higher-ability students.

Keywords

• artificial intelligence
• dual code theory
• english as a foreign language (efl)
• object detection translation
• vocabulary learning