Model partial and uncertain defending outcomes and keep the facilitator human when deploying drama-based robot interventions¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article's deployment recommendations are twofold. First, the narrative should model realistic outcome uncertainty: the story shows that "confronting the bully can unfold in more than one way", so children learn defending can matter even when bullying is not fully stopped. Second, for real-world adoption the authors argue "the role of the joker should ideally not be automated", with a drama educator taking that role, while the Wizard's narrative-control role should be fully automated, potentially via simplified teacher-facing interfaces and LLMs.

Design Implications¶

Context¶

Requirements¶

• A human or educator facilitator to guide reflection and encourage participation

Constraints¶

• The authors state future work must explore and mitigate practical barriers for long-term deployment in educational settings

Target Learners¶

• children aged 9-10 in school anti-bullying programs

Target Learning Goals¶

• calibrated outcome expectations about defending and sustained bystander intervention

Affordances¶

• Robot Mediated Applied Drama Rmad Framework

Related Strategies¶

Examples¶

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Key Sources¶

• Elaheh Sanoubari, Neil Fernandes, Keith Rebello, Alicia Pan, Andrew Houston, and Kerstin Dautenhahn. (2026). Play-Testing REMind: Evaluating an Educational Robot-Mediated Role-Play Game. https://arxiv.org/abs/2604.00300