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A Dialogue System for Second Language Learning with Dynamic Adaptation to In-Dialogue Difficulty Changes

Researchers from the Association for Computational Linguistics have developed a dialogue system for second language learning that dynamically adjusts utterance difficulty based on the learner's topic-specific proficiency. The system, presented at the 27th Annual Meeting of the Special Interest Group on Discourse and Dialogue in Atlanta, uses large language models with prompt engineering and Direct Preference Optimization to minimize the difficulty gap between system and user. Experiments in Japanese and English showed the method effectively tracks utterance difficulty for learners.

read1 min views1 publishedJul 21, 2026
A Dialogue System for Second Language Learning with Dynamic Adaptation to In-Dialogue Difficulty Changes
Image: Aclanthology (auto-discovered)
Abstract

We propose a dialogue system for second language learning that dynamically adjusts the difficulty of its utterances by adapting to changes in the learner’s utterance difficulty across dialogue topics. Recent studies have advanced second language learning dialogue systems based on large language models (LLMs) grounded in the Input Hypothesis. However, although learners’ language proficiency varies based on their familiarity with a given topic, conventional fixed-difficulty dialogue systems do not adequately account for this variability. In this study, we propose a dialogue system for second language learning that minimizes the difficulty gap between the system and a user model. The user model dynamically varies utterance difficulty based on the topic during dialogue. Our LLM-based dialogue system controls utterance difficulty by prompt engineering and Direct Preference Optimization (DPO). Experimental results in both Japanese and English demonstrate that the proposed method is effective in tracking utterance difficulty for second language learners.- Anthology ID:

- 2026.sigdial-1.13
- Volume:
[Proceedings of the 27th Annual Meeting of the Special Interest Group on Discourse and Dialogue](/volumes/2026.sigdial-1/)- Month:
  • August
  • Year:
  • 2026
  • Address:
  • Atlanta, Georgia, USA
- Editors:
[Jinho D. Choi](/people/jinho-d-choi/),[Yun-Nung Chen](/people/yun-nung-chen/),[Kotaro Funakoshi](/people/kotaro-funakoshi/),[Ali Emami](/people/ali-emami/)- Venue:
[SIGDIAL](/venues/sigdial/)- SIG:
[SIGDIAL](/sigs/sigdial/)- Publisher:
  • Association for Computational Linguistics
- Note:
- Pages:
  • 170–187
- Language:
- URL:
[https://aclanthology.org/2026.sigdial-1.13/](https://aclanthology.org/2026.sigdial-1.13/)- DOI:
- Cite (ACL):
[A Dialogue System for Second Language Learning with Dynamic Adaptation to In-Dialogue Difficulty Changes](https://aclanthology.org/2026.sigdial-1.13/)(Morioka et al., SIGDIAL 2026)- PDF:
[https://aclanthology.org/2026.sigdial-1.13.pdf](https://aclanthology.org/2026.sigdial-1.13.pdf)
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