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莉洛博特:一个认知对话代理来培训儿童热线辅导员:设计和初步评估
Sharon Grundmann1, Mohammed Al Owayyed2,3, Merijn Bruijnes4
1Intelligent Systems, Delft University of Technology, Delft, The Netherlands.
Journal of medical systems
|January 13, 2025
概括
开发了一种新的对话代理,Lilobot,用于培训儿童热线辅导员. 虽然初步结果显示自我效率下降,但辅导员发现Lilobot是改善辅导技能的有希望的工具.
科学领域:
- 人与计算机的交互
- 教育中的人工智能
- 心理培训 心理培训
背景情况:
- 儿童热线需要为新辅导员提供有效的培训.
- 传统的角色扮演是耗时且在后勤上具有挑战性的.
- 交谈代理提供了可扩展培训的潜在解决方案.
研究的目的:
- 提出和评估Lilobot的初始设计,这是一个用于辅导员培训的对话代理.
- 评估Lilobot在实践以儿童为中心的对话中的五阶段模型中的有效性.
- 将基于Lilobot的培训与传统的基于文本的培训进行比较.
主要方法:
- 开发了Lilobot,使用一种信念-欲望-意图 (BDI) 模型来模拟受欺凌的孩子.
- 经验丰富的辅导员参加了与Lilobot和基于文本的场景的角色扮演培训课程.
- 进行了咨询自我有效性的测量前后比较.
主要成果:
- 辅导自我效率在训练后下降,特别是在Lilobot条件下.
- 质量反表明,Lilobot作为进一步开发的补充培训工具的潜力.
- 确定了未来研究的领域,包括情感整合和LLM合并.
结论:
- 利洛博特显示出作为培训儿童帮助线辅导员的补充工具的承诺.
- 需要进一步的研究来提高代理人的能力和培训效率.
- 这项研究强调了人工智能在模拟复杂的人类互动以培养技能方面的潜力.
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