The Impact of GPT-based Dialogue Systems vs. Traditional Word-list Memorization on Second Language Vocabulary Acquisition
Research Article
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The Impact of GPT-based Dialogue Systems vs. Traditional Word-list Memorization on Second Language Vocabulary Acquisition

Yueru Zhao 1*
1 Nanjing University
*Corresponding author: 221108122@smail.nju.edu.cn
Published on 11 July 2025
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LNEP Vol.106
ISSN (Print): 2753-7056
ISSN (Online): 2753-7048
ISBN (Print): 978-1-80590-253-9
ISBN (Online): 978-1-80590-254-6
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Abstract

In an age where technology is rapidly changing how individuals interact with core issues, such as education, respective institutions need to embrace these trends. Today, learning a second language is characterized by shifts in artificial intelligence, contesting with the existing traditional systems. This study compares GPT-based dialogue systems with traditional word-list practice for second language (L2) English vocabulary acquisition. Based on a 2 × 3 mixed ANOVA and independent-samples t-tests, the study analyzed pre-test, post-test, and delayed post-test data gained from 60 participants (n = 30 each for GPT group and traditional groups). Findings indicate that the GPT group significantly outperform the word-list group with a greater immediate learning gains and retention and robust effect sizes. Analysis was grounded in theories of comprehensible input, declarative/procedural knowledge, and scaffolding, positioning the study as an effective advocate for AI-driven tools in language education. These tools can be integrated in modern L2 approaches, but effective adoption needs to consider their current limitations. The potential of GPT-based techniques reveal that stakeholders need to embrace these systems even as they maintain traditional approaches.

Keywords:

GPT-based dialogue systems, L2 vocabulary acquisition, language learning technology, educational technology

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Zhao,Y. (2025). The Impact of GPT-based Dialogue Systems vs. Traditional Word-list Memorization on Second Language Vocabulary Acquisition. Lecture Notes in Education Psychology and Public Media,106,41-50.

References

[1]. Eurostat. (2024, September). Foreign language learning statistics. https: //ec.europa.eu/eurostat/statistics-explained/index.php?title=Foreign_language_learning_statistics

[2]. Ender, A. (2016). Implicit and Explicit Cognitive Processes in Incidental Vocabulary Acquisition. Applied Linguistics, 37(4), 536–560.

[3]. Kashani, S., & Shafiee, S. (2016). A comparison of vocabulary learning strategies among elementary Iranian EFL learners. Journal of Language Teaching and Research, 7(3), 511–518.

[4]. Chang, M.-M., & Hung, H.-T. (2019). Effects of technology-enhanced language learning on second language acquisition: A meta-analysis. Educational Technology and Society, 22(4), 1–17.

[5]. Yu, A., & Trainin, G. (2022). A meta-analysis examining technology-assisted L2 vocabulary learning. ReCALL, 34(2), 235–252.

[6]. Zhang, Z., & Huang, X. (2024). The impact of chatbots based on large language models on second language vocabulary acquisition. Heliyon, 10(3), e25370.

[7]. Zografos, G., & Moussiades, L. (2023). A GPT-Based Vocabulary Tutor. Augmented Intelligence and Intelligent Tutoring Systems. ITS 2023. Lecture Notes in Computer Science (Vol. 13891, pp. 270–280). Springer, Cham.

[8]. Timpe-Laughlin, V., & Dombi, J. (2020). Exploring L2 learners’ request behavior in a multi-turn conversation with a fully automated agent. Intercultural Pragmatics, 17(2), 221–257.

[9]. Hatmanto, E. D., & Sari, M. I. (2023). Aligning Theory and Practice: Leveraging Chat GPT for Effective English Language Teaching and Learning. International Conference on Environment and Smart Society (ICEnSO 2023) (Vol. 440). E3S Web of Conferences.

[10]. Hu, W.-C., & Škultéty, R. (2024). Unlocking the Learning Potential: ChatGPT as a Virtual Platform for Cross-Interaction in English Language Learning. Engineering Proceedings, 74(1), 59.

[11]. Wang, C., & Li, X. (2025). Software Review: Empowering Language Education With D-ID Creative Reality Studio’s Multimodal Capabilities. International Journal of Computer-Assisted Language Learning and Teaching, 15(1). 1-11.

[12]. Timpe-Laughlin, V., Sydorenko, T., & Daurio, P. (2022). Using spoken dialogue technology for L2 speaking practice: What do teachers think? Computer Assisted Language Learning, 35(5–6), 1194–1217.

[13]. Mai, L., & Carson-Berndsen, J. (2024). Enhancing conversation smoothness in language learning chatbots: An evaluation of GPT4 for ASR error correction. ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 11001-11005). IEEE.

[14]. Alhazmi, A. A., & Muftah, M. (2025). Evaluating ChatGPT’s Reliability in Second Language Acquisition (SLA): Insights on Language Skills and Technology’s Role. Electronic Journal of E-Learning, 23(1), 96–112.

[15]. Nouzri, S., EL Fatimi, M., Guerin, T., Othmane, M., & Najjar, A. (2025). Beyond Chatbots: Enhancing Luxembourgish Language Learning Through Multi-Agent Systems and Large Language Model. PRIMA 2024: Principles and Practice of Multi-Agent Systems. PRIMA 2024. Lecture Notes in Computer Science (Vol. 15395, pp. 385–401). Springer, Cham.

[16]. Krashen, S. (1985). The input hypothesis: Issues and implications. Longman.

[17]. Anderson, J. (1993). Rules of the Mind. Lawrence Erlbaum.

[18]. Vygotsky, L. S. (1978). Mind in society. Harvard University Press.

References

[1]. Eurostat. (2024, September). Foreign language learning statistics. https: //ec.europa.eu/eurostat/statistics-explained/index.php?title=Foreign_language_learning_statistics

[2]. Ender, A. (2016). Implicit and Explicit Cognitive Processes in Incidental Vocabulary Acquisition. Applied Linguistics, 37(4), 536–560.

[3]. Kashani, S., & Shafiee, S. (2016). A comparison of vocabulary learning strategies among elementary Iranian EFL learners. Journal of Language Teaching and Research, 7(3), 511–518.

[4]. Chang, M.-M., & Hung, H.-T. (2019). Effects of technology-enhanced language learning on second language acquisition: A meta-analysis. Educational Technology and Society, 22(4), 1–17.

[5]. Yu, A., & Trainin, G. (2022). A meta-analysis examining technology-assisted L2 vocabulary learning. ReCALL, 34(2), 235–252.

[6]. Zhang, Z., & Huang, X. (2024). The impact of chatbots based on large language models on second language vocabulary acquisition. Heliyon, 10(3), e25370.

[7]. Zografos, G., & Moussiades, L. (2023). A GPT-Based Vocabulary Tutor. Augmented Intelligence and Intelligent Tutoring Systems. ITS 2023. Lecture Notes in Computer Science (Vol. 13891, pp. 270–280). Springer, Cham.

[8]. Timpe-Laughlin, V., & Dombi, J. (2020). Exploring L2 learners’ request behavior in a multi-turn conversation with a fully automated agent. Intercultural Pragmatics, 17(2), 221–257.

[9]. Hatmanto, E. D., & Sari, M. I. (2023). Aligning Theory and Practice: Leveraging Chat GPT for Effective English Language Teaching and Learning. International Conference on Environment and Smart Society (ICEnSO 2023) (Vol. 440). E3S Web of Conferences.

[10]. Hu, W.-C., & Škultéty, R. (2024). Unlocking the Learning Potential: ChatGPT as a Virtual Platform for Cross-Interaction in English Language Learning. Engineering Proceedings, 74(1), 59.

[11]. Wang, C., & Li, X. (2025). Software Review: Empowering Language Education With D-ID Creative Reality Studio’s Multimodal Capabilities. International Journal of Computer-Assisted Language Learning and Teaching, 15(1). 1-11.

[12]. Timpe-Laughlin, V., Sydorenko, T., & Daurio, P. (2022). Using spoken dialogue technology for L2 speaking practice: What do teachers think? Computer Assisted Language Learning, 35(5–6), 1194–1217.

[13]. Mai, L., & Carson-Berndsen, J. (2024). Enhancing conversation smoothness in language learning chatbots: An evaluation of GPT4 for ASR error correction. ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 11001-11005). IEEE.

[14]. Alhazmi, A. A., & Muftah, M. (2025). Evaluating ChatGPT’s Reliability in Second Language Acquisition (SLA): Insights on Language Skills and Technology’s Role. Electronic Journal of E-Learning, 23(1), 96–112.

[15]. Nouzri, S., EL Fatimi, M., Guerin, T., Othmane, M., & Najjar, A. (2025). Beyond Chatbots: Enhancing Luxembourgish Language Learning Through Multi-Agent Systems and Large Language Model. PRIMA 2024: Principles and Practice of Multi-Agent Systems. PRIMA 2024. Lecture Notes in Computer Science (Vol. 15395, pp. 385–401). Springer, Cham.

[16]. Krashen, S. (1985). The input hypothesis: Issues and implications. Longman.

[17]. Anderson, J. (1993). Rules of the Mind. Lawrence Erlbaum.

[18]. Vygotsky, L. S. (1978). Mind in society. Harvard University Press.

Cite this article

Zhao,Y. (2025). The Impact of GPT-based Dialogue Systems vs. Traditional Word-list Memorization on Second Language Vocabulary Acquisition. Lecture Notes in Education Psychology and Public Media,106,41-50.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICEIPI 2025 Symposium: AI Am Ready: Artificial Intelligence as Pedagogical Scaffold

ISBN: 978-1-80590-253-9(Print) / 978-1-80590-254-6(Online)
Editor: Kurt Buhring, Gregg S. Lloren
Conference website: https://2025.iceipi.org/Cebu.html
Conference date: 23 July 2025
Series: Lecture Notes in Education Psychology and Public Media
Volume number: Vol.106
ISSN: 2753-7048(Print) / 2753-7056(Online)

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