EDEN: Empathetic Dialogues for English learning
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Abstract (arXiv)
Dialogue systems have been used as conversation partners in English learning, but few have studied whether these systems improve learning outcomes. Student passion and perseverance, or grit, has been associated with language learning success. Recent work establishes that as students perceive their English teachers to be more supportive, their grit improves. Hypothesizing that the same pattern applies to English-teaching chatbots, we create EDEN, a robust open-domain chatbot for spoken conversation practice that provides empathetic feedback. To construct EDEN, we first train a specialized spoken utterance grammar correction model and a high-quality social chit-chat conversation model. We then conduct a preliminary user study with a variety of strategies for empathetic feedback. Our experiment suggests that using adaptive empathetic feedback leads to higher perceived affective support. Furthermore, elements of perceived affective support positively correlate with student grit.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 8 of its 75 references that are in the map. First posted on arXiv 25 Jun 2024.
Builds on
8 of 75 references.
References · 8
- 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
- 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
- 2023DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelinescited by 803
- 2021LM-Critic: Language Models for Unsupervised Grammatical Error Correctioncited by 33
- 2023Curriculum-Driven Edubot: A Framework for Developing Language Learning Chatbots Through Synthesizing Conversational Datacited by 9
- 2021SERRANT: a syntactic classifier for English Grammatical Error Typescited by 6
- 2024Using Adaptive Empathetic Responses for Teaching Englishcited by 5
- 2021FreeTalky: Don't Be Afraid! Conversations Made Easier by a Humanoid Robot using Persona-based Dialoguecited by 2
Built on by
Citing papers per year: 2025: 4; 2026: 1.
5 papers.
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- 2025Position: LLMs Can be Good Tutors in English Educationcited by 6
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- 2026A Concise Agent is Less Expert: Revealing Side Effects of Using Style Features on Conversational Agentscited by 1
- 2025Re:Member: Emotional Question Generation from Personal Memoriescited by 0
- 2026A Concise Agent is Less Expert: Revealing Side Effects of Using Style Features on Conversational Agents15 Jan 2026
- 2025Re:Member: Emotional Question Generation from Personal Memories21 Oct 2025
- 2025Animating Language Practice: Engagement with Stylized Conversational Agents in Japanese Learning9 Jul 2025
- 2025Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above19 Feb 2025
- 2025Position: LLMs Can be Good Tutors in English Education8 Feb 2025