Natural Language Processing in ESL Vocabulary Acquisition: A Review of Conversational Agents and Intelligent Feedback Systems

Vocabulary is essential for learning a second language; yet, students often struggle with remembering words, getting sufficient exposure, or receiving instant feedback. Natural Language Processing (NLP) has made significant advances, providing practical responses through interactive and adaptable tools that enable individuals to learn English as a second language (ESL). This article examines how NLP allows individuals to learn new words in two primary areas: conversational agents and intelligent feedback systems. Conversational agents, such as chatbots and virtual tutors, offer interaction and contextualized practice, which boosts motivation and decreases anxiety. Intelligent feedback systems deliver immediate, personalized, and data-driven corrections, enabling learners to improve their accuracy and become more autonomous. While both approaches demonstrate clear benefits—ranging from improved retention to increased engagement—each also faces limitations. These include restricted contextual comprehension, ethical and privacy concerns, and risks of overreliance on technology. A key finding from the existing literature highlights the potential for collaboration between conversational agents and intelligent feedback systems. When these elements are integrated, they more effectively imitate the dynamics of human tutoring by blending interaction with corrective support. improving classroom instruction, promoting independent learning, and expanding the roles of educators. The review highlights strengths and weaknesses in current research, emphasizes the need for integration, and suggests directions for future work. Recommendations include conducting long-term studies, adapting research to cross-cultural contexts, and implementing ethical safeguards. Collectively, the findings demonstrate NLP as a transformative tool for equal and effective ESL vocabulary acquisition.

کلیدواژه ها:

ESL vocabulary ، Natural Language Processing (NLP) ، Conversational agents ، Intelligent feedback ، Adaptive learning