While conversational agents’ (CAs) semantic and syntactic capabilities have advanced, their pragmatic skills, using language appropriately in context, have emerged as a critical focus in practical applications. Hence, scholars integrate conversational skills derived from human-human interaction into CA designs. However, existing research mainly adopts an empirical approach and focuses on specific CA deployment, making it challenging to identify overarching patterns or develop a comprehensive methodology for transferring human pragmatic skills to CA design. Thus, we conducted a systematic review of 85 studies from primary databases (e.g., ACM, IEEE, etc.), focusing on designing CAs with human-derived conversational skills. We identified skill categories (verbal, paralinguistic, nonverbal), transfer strategies (from dialog data, theories, and via co-design), implementations, and evaluation metrics. We consolidated these insights into a four-stage design process: human skill exploration, definition, transfer, and iterative evaluation. Future research can leverage this to design CAs that achieve conversational goals through contextually appropriate language use.

Regular screening is critical for individuals at risk of neurocognitive disorders (NCDs) to receive early intervention. Conversational agents (CAs) have been adopted to administer dialog-based NCD screening tests for their scalability compared to human-administered tests. However, unique communication skills are required for CAs during NCD screening, e.g., clinicians often apply scaffolding to ensure subjects’ understanding of and engagement in screening tests. Based on scaffolding theories and analysis of clinicians’ practices from human-administered test recordings, we designed a scaffolding framework for the CA. In an exploratory wizard-of-Oz study, the CA empowered by ChatGPT administered tasks in the Grocery Shopping Dialog Task with 15 participants (10 diagnosed with NCDs). Clinical experts verified the quality of the CA’s scaffolding and we explored its effects on task understanding of the participants. Moreover, we proposed implications for the future design of CAs that enable scaffolding for scalable NCD screening.