arXiv:2409.12968cs.HCcs.AI2024-09被引 6

用虚拟现实训练教师应对冲突时的情绪管理能力,提升教学互动质量。

MITHOS: Interactive Mixed Reality Training to Support Professional Socio-Emotional Interactions at Schools

  • 通过虚拟学生代理提供真实互动反馈,支持教师情绪调节训练
  • 四阶段系统验证了场景真实度,相似外貌的虚拟形象提升自我觉察
  • 适合教育心理、人机交互研究者,推动沉浸式教学工具发展

在复杂冲突情境中,教师常因无力感产生羞耻与自责,可能外化为愤怒。若无法准确感知情绪信号,则违背情绪调节的连续性原则,导致学生情绪困惑并阻碍其情绪调节能力发展。因此,有效的情绪调节不仅改善个体体验,更促进人际间情绪协调,影响冲突处理效果。MITHOS 是一套基于混合现实的教师培训系统,通过四个阶段支持教师的社会情感自我觉察、换位思考与积极关怀:(a)安全虚拟环境实现自由社交互动并接收自然社会反馈;(b)通过化身实现空间情境视角转换;(c)通过共调节过程进行个体情绪反思引导;(d)获得专业行为策略的专家反馈。本章介绍该系统在半自动巫师之奥(WoZ)框架下的四阶段实现,并收集数据用于开发全自动混合系统(机器学习与模型驱动结合),同时验证心理与冲突解决模型的有效性。结果表明,情景具有高真实性,且外部化身相似性显著影响自我觉察前因变量中的行为相似性。研究贡献于跨学科人本化XR研究方法论,并设计出可推广的干预系统。

原文摘要 · Abstract (English)

Teachers in challenging conflict situations often experience shame and self-blame, which relate to the feeling of incompetence but may externalise as anger. Sensing mixed signals fails the contingency rule for developing affect regulation and may result in confusion for students about their own emotions and hinder their emotion regulation. Therefore, being able to constructively regulate emotions not only benefits individual experience of emotions but also fosters effective interpersonal emotion regulation and influences how a situation is managed. MITHOS is a system aimed at training teachers' conflict resolution skills through realistic situative learning opportunities during classroom conflicts. In four stages, MITHOS supports teachers' socio-emotional self-awareness, perspective-taking and positive regard. It provides: a) a safe virtual environment to train free social interaction and receive natural social feedback from reciprocal student-agent reactions, b) spatial situational perspective taking through an avatar, c) individual virtual reflection guidance on emotional experiences through co-regulation processes, and d) expert feedback on professional behavioural strategies. This chapter presents the four stages and their implementation in a semi-automatic Wizard-of-Oz (WoZ) System. The WoZ system affords collecting data that are used for developing the fully automated hybrid (machine learning and model-based) system, and to validate the underlying psychological and conflict resolution models. We present results validating the approach in terms of scenario realism, as well as a systematic testing of the effects of external avatar similarity on antecedents of self-awareness with behavior similarity. The chapter contributes to a common methodology of conducting interdisciplinary research for human-centered and generalisable XR and presents a system designed to support it.

教育技术情绪调节虚拟现实人机交互

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