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论文精选 65arXiv

Comparing Human Role-Players and LLM-Simulated Clients in Online Counselling Training: An Analysis of Counselling Patterns· 人类角色扮演者与LLM模拟客户在在线辅导培训中的比较

This study investigates the capabilities of Large Language Models to simulate counselling clients in educational role-plays in comparison to human role-players. Initially, we recorded role-playing sessions, where novice counsellors interacted with human peers acting as clients, followed by role-plays between humans and clients simulated by Mistrals Mixtral 8x7b using 4-bit quantization. These interactions were analysed with a counselling communication pattern system at sentence level. We investigated two key questions: (1) to what extent LLM-generated responses replicate authentic conversational dynamics and (2) whether counsellors' communication behaviour differs when interacting with human versus LLM-simulated clients. The findings highlight both similarities and differences in the appli

AI 解读论文

研究LLM在在线辅导培训中模拟客户的能力与人类角色扮演者的对比。

核心方法
记录新手辅导者与人类同伴及LLM模拟客户的互动,使用咨询沟通模式系统在句子层面分析交互内容。
适合谁读
研究者、教育技术开发者、心理咨询培训师
要解决的问题
探索大型语言模型在教育角色扮演中是否能有效模拟真实客户,以及这种模拟如何影响辅导者的行为。
关键实验
记录了新手辅导者与人类角色扮演者及与LLM模拟客户的互动会话,并进行了模式分析。
主要贡献
揭示了LLM生成的响应在多大程度上能够复制真实的对话动态,以及辅导者在与人类与LLM客户互动时沟通行为的差异。
意义与局限
该研究有助于理解LLM在教育和培训中的应用潜力及其局限性,为未来使用技术辅助心理咨询培训提供了参考。
领域:cs.AI作者:Eric Rudolph、Philipp Steigerwald、Jens Albrecht
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