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Language acquisition through tandem learning, where learners practice with native speakers, is widely recognized for its effectiveness in enhancing communication skills and cultural understanding. However, this method faces persistent challenges, including difficulty finding committed partners, scheduling conflicts, inconsistent feedback, and anxiety about making mistakes. While common language exchange apps provide online solutions, these limitations often constrain them. This study explores the potential of a GPT-4o-based conversational agent (CA) as an alternative language exchange partner. CAs offer constant availability, immediate responses, and non-judgmental corrective feedback, presenting a promising solution to the barriers faced in traditional tandem learning. We employ a design science research approach to design, implement, and evaluate a CA specifically for English language learners. The CA’s features, including adaptive language levels and contextual conversational abilities, are guided by principles of second language acquisition. Results from user tests and semi-structured interviews reveal its strengths in facilitating consistent practice and reducing learner anxiety while highlighting limitations in emotional connection and cultural depth. This study contributes to understanding how advanced conversational AI can complement traditional language learning methods and offers valuable insights for future educational technology development.

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Designing a Large Language Model Based Conversational Agent for Language Acquisition

  • 会议论文

  • 发表日期：

    2025年

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  • Nicolas Neis,
  • Philipp Spleth,
  • Cecilie Kudlek,
  • Rüdiger Zarnekow,
  • Axel Winkelmann

摘要

Language acquisition through tandem learning, where learners practice with native speakers, is widely recognized for its effectiveness in enhancing communication skills and cultural understanding. However, this method faces persistent challenges, including difficulty finding committed partners, scheduling conflicts, inconsistent feedback, and anxiety about making mistakes. While common language exchange apps provide online solutions, these limitations often constrain them. This study explores the potential of a GPT-4o-based conversational agent (CA) as an alternative language exchange partner. CAs offer constant availability, immediate responses, and non-judgmental corrective feedback, presenting a promising solution to the barriers faced in traditional tandem learning. We employ a design science research approach to design, implement, and evaluate a CA specifically for English language learners. The CA’s features, including adaptive language levels and contextual conversational abilities, are guided by principles of second language acquisition. Results from user tests and semi-structured interviews reveal its strengths in facilitating consistent practice and reducing learner anxiety while highlighting limitations in emotional connection and cultural depth. This study contributes to understanding how advanced conversational AI can complement traditional language learning methods and offers valuable insights for future educational technology development.