Dual Coding and Language Learning: Drawing as Cognitive Support

Abstract

As artificial intelligence in language teaching rapidly develops, there is a definitive necessity for reconsideration of the manner in which students operate with the newly appearing vocabulary and build meaning. This paper applies the dual coding theory and wider concepts of human cognition to determine the specification of drawing as a teaching approach. Even though AI tools can help one to become more efficient and personalized, they promote superficial engagement with the language as well. In comparison, drawing asks the learner to actively interpret and give meaning to the work, making connections between the systems of the verbal and the visual in a manner that enhances the role of form and meaning. Based on studies of the development of cognitive psychology, second language acquisition, and education, this paper summarizes both theoretical and classroom-based constructs that drawing is a teaching and learning strategy based on conceptual analysis as its major approach. The paper explains that drawing is far beyond a technique of memorization. Students are recomposing linguistic information when engaged in constructing their own visual images, and they make deliberate personal decisions concerning meaning. This further involvement promotes semantic encoding and more retention in the long run. Text planning, lexical retrieval, and language production in general are also supported by drawing. Instead of considering drawing as a substitute for technological innovation, this paper proposes that it is complementary in a digitally mediated classroom. Cognitive processes of humans will stay the key in second language acquisition into the twenty-first century; thus, drawing remains an instrumental process of second language education in the world where automation effects become more prominent.