DavAI: Designing a Custom ChatGPT bot for Russian Language Learners

The article explores the development and application of DavAI, a ChatGPT-based bot designed for beginner and intermediate Russian language learners. It highlights the bot’s capacity to act as a powerful supplementary tool within Russian language education. DavAI features six virtual personalities that represent diverse geographical regions, cultures, dialects, and social backgrounds. The technical customization process of DavAI is detailed, emphasizing content integration and pedagogical strategies that enhance language acquisition. Practical steps for language instructors on developing custom AI chatbots are outlined, including defining the model’s scope and purpose, gathering and segmenting training data, and employing fine-tuning techniques such as Reinforcement Learning from Human Feedback (RLHF). This process emphasizes iterative improvements based on feedback from both students and instructors. The article also addresses ethical considerations, particularly in preventing the reinforcement of stereotypes and generating culturally inaccurate content.

Authors

Publication Details

Journal
Russian Language Journal
Published
2024-12-30
DOI
https://doi.org/10.70163/0036-0252.1400
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.35
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article

DavAI: Designing a Custom ChatGPT bot for Russian Language Learners

Irina Meier
1 citations
Russian Language Journal
AI in Service Interactions
0.35
article

DavAI: Designing a Custom ChatGPT bot for Russian Language Learners

Irina Meier
article en
1 citations

Abstract

The article explores the development and application of DavAI, a ChatGPT-based bot designed for beginner and intermediate Russian language learners. It highlights the bot’s capacity to act as a powerful supplementary tool within Russian language education. DavAI features six virtual personalities that represent diverse geographical regions, cultures, dialects, and social backgrounds. The technical customization process of DavAI is detailed, emphasizing content integration and pedagogical strategies that enhance language acquisition. Practical steps for language instructors on developing custom AI chatbots are outlined, including defining the model’s scope and purpose, gathering and segmenting training data, and employing fine-tuning techniques such as Reinforcement Learning from Human Feedback (RLHF). This process emphasizes iterative improvements based on feedback from both students and instructors. The article also addresses ethical considerations, particularly in preventing the reinforcement of stereotypes and generating culturally inaccurate content.

Russian Language JournalVol. 74(1)
Quality Education
Openalex Percentile: Top 29%
AI in Service Interactions
0.35
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