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With the growing trend in adopting intelligent chatbots across various sectors, ranging from customer service to personal assistants, it is essential to understand how User Experience (UX) methodologies are being employed to improve user-system interaction and overall user satisfaction in the artificial intelligence era. This work aims: (i) to investigate the main current UX methodologies used in the development of intelligent chatbots and conversational interfaces, and (ii) to identify how effectively measure and evaluate the quality of conversations between humans and chatbots beyond traditional usability metrics. For this purpose, we conducted a systematic literature review (SLR) following a rigorous and systematic procedure to search, select, and analyze primary studies in the literature. Our corpus is made up of ten studies, each presenting solutions on UX methodologies and evaluation metrics and strategies for analysing quality of conversation in intelligent chatbots. This paper also raises relevant challenges and potential directions for future research based on the main findings of the SLR.

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User Experience in Intelligent Chatbots: A Systematic Mapping

  • 会议论文

  • 发表日期：

    2026年

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  • Thais Batista,
  • Iris Gurgel,
  • Daniela Maia,
  • Cybelle Lemos,
  • Débora Chacon,
  • Elias Jacob de Menezes Neto,
  • Hugo Melo,
  • Igor Correia,
  • Isaac Lourenço,
  • Lorena Macêdo,
  • Matheus Vidal,
  • Maycon Santos,
  • Paulo Araújo

摘要

With the growing trend in adopting intelligent chatbots across various sectors, ranging from customer service to personal assistants, it is essential to understand how User Experience (UX) methodologies are being employed to improve user-system interaction and overall user satisfaction in the artificial intelligence era. This work aims: (i) to investigate the main current UX methodologies used in the development of intelligent chatbots and conversational interfaces, and (ii) to identify how effectively measure and evaluate the quality of conversations between humans and chatbots beyond traditional usability metrics. For this purpose, we conducted a systematic literature review (SLR) following a rigorous and systematic procedure to search, select, and analyze primary studies in the literature. Our corpus is made up of ten studies, each presenting solutions on UX methodologies and evaluation metrics and strategies for analysing quality of conversation in intelligent chatbots. This paper also raises relevant challenges and potential directions for future research based on the main findings of the SLR.