Enhancing Terminology Proficiency of EFL’s Higher Vocational Institution Students through AI-Assisted Learning

DOI

10.2991/978-94-6463-938-4_35How to use a DOI?

Keywords

AI-Driven Chatbot; Deepseek; EFL; Higher Vocational Institution; Terminology Proficiency

Abstract

The phenomenon of Artificial Intelligence (AI) driven chatbots as a language learning tool has been a topical issue these days. Due to its high-tech feature, it is considered one of the effective ways to encourage students to enhance their language ability independently. There were many studies about this top-ic in Indonesia, but this research focuses on investigating how effective chatbots are in building the terminology proficiency of English as a Foreign Language (EFL) students in vocational institutions. The study involved 50 third-year students at the English Department, Politeknik Negeri Padang (PNP), West Sumatra, Indonesia. It is designed as a mixed-method study and implements a concurrent triangulation strategy. There are three instruments used for data collection: pre-test and post-test, five Likert scale question-naire, and open-ended interview. After pre-test, the participants are taught to use DeepSeek, one of the latest chatbots, as personal assistant in helping them comprehend specialized terminology while completing their project in the Workshop on Interpreting class. It has DeepThink feature which presents its point of view before responding to the prompt given. By utilizing a paired sample t-test, a significant improvement in the students’ terminology profi-ciency is proven by a value of p < .001. Based on the questionnaire and in-terview, it can be concluded that the students agreed DeepSeek help them to solve difficulties which they usually face regarding specialized terminology during language study. They also agree that the chatbot feature is interesting and improves their critical thinking in enchancing terminology proficiency while using AI-driven chatbot.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Mutia El Khairat
AU  - Sariani Sariani
AU  - Fithratul Miladiyenti
AU  - Muthia Damaiyanti
AU  - Desi Yulastri
AU  - Martini Martini
AU  - Astuti Pratiwi
AU  - Silvia Djonnaidi
PY  - 2025
DA  - 2025/12/31
TI  - Enhancing Terminology Proficiency of EFL’s Higher Vocational Institution Students through AI-Assisted Learning
BT  - Proceedings of the International Conference on Applied Science and Technology on Social Science 2025 (iCAST-SS 2025
PB  - Atlantis Press
SP  - 296
EP  - 304
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-938-4_35
DO  - 10.2991/978-94-6463-938-4_35
ID  - Khairat2025
ER  -