设计师 Negotiabbles 的作品 Negotiabbles 平板电脑应用程序荣获了极具声望的 2026 A' Design Award 铁奖，竞赛类别为教育、教学辅助与培训内容设计。

铁教育· 2026

Negotiabbles 平板电脑应用程序

设计师： Negotiabbles

客户: Negotiabbles

教育类别A' Design Award 铁奖获奖者

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关于 Negotiabbles 平板电脑应用程序

Negotiabbles 是一款教育类平板电脑应用程序,旨在帮助幼儿园至八年级的儿童练习协商沟通技巧。该应用将常见的同伴情境——例如共享资源或化解分歧——以图文故事章节的形式呈现。儿童与人工智能角色对话,并在引导下学习表达需求、陈述理由、倾听他人并达成共识。每个角色头顶的情绪气泡会通过颜色、大小和形状的变化,实时展现其情绪状态。总结页面则记录所使用的沟通策略以及各次练习中的进步情况。

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关于A' Design Award 铁奖

Negotiabbles 平板电脑应用程序是 A' Design Award 铁奖得主，这是授予满足人们对设计精良的创作所期待的专业与工业要求的优良设计的声望认可。铁奖得主展现出其创作者的高超技艺、高度专业化、专家级的理解力和创造能力。预计Negotiabbles 平板电脑应用程序将成为一件备受推崇、令人钦佩且被珍爱的创作，既实用又创新。这件赢得 A' Design Award 铁奖的设计整合了行业最佳实践，并拥有与专业知识和才华相结合的称职技术特性。Negotiabbles 平板电脑应用程序因其严谨而受到尊重，旨在提供有助于让世界变得更美好的生活品质改善。

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由设计师提供的致谢、团队成员及技术详情。

独特属性: Negotiabbles is an educational app that helps children in grades K-8 build essential negotiation skills in a safe, playful, and story-driven environment. Many kids struggle to express needs or resolve conflicts and only 28% of children ages 6 to 8 can do so clearly. Our design transforms complex negotiation principles into age-appropriate role-play with AI characters, real-time feedback, and emotion-visualized interfaces. By turning peer conflicts into engaging learning opportunities, Negotiabbles empowers kids to grow confidence, empathy, and lifelong communication skills.
尺寸与包装: Digital application for tablets (10-inch, 2160 x 1620 px). Voice input with real-time AI response. Adaptive difficulty across K-8 stages. Cloud-based architecture supporting single-player, guided, and multiplayer modes. Emotion-visualized bubble interface rendered at 60 fps. Secure data handling for child users (COPPA-aligned).
标签: Educational App, Children, Negotiation Skills, Social-Emotional Learning, AI Role-Play, Voice Interaction, Color Psychology, Emotion Visualization, Game-Based Learning, Conflict Resolution, K–8 Education, Interactive Storytelling, Child Development, Shape Psychology, Empathy Training
生产技术: User-centered iterative design process. Voice interaction via speech processing APIs, AI-driven role-play via NLP, real-time emotion visualization through a custom animation system built on color and shape psychology frameworks. Prototyping and usability testing with target-age children refined scaffolding and interaction patterns. Digital-first, cloud-based architecture.
设计挑战: The central creative and research challenge was to make the invisible visible: negotiation is fundamentally a psychological process involving shifting emotions, competing needs, and evolving positions - none of which have an inherent visual form. The team needed to develop a visual language that could represent these dynamics in a way that is immediately intuitive to children as young as five, while remaining scientifically grounded and systematically scalable. The solution was the development of an "Emotional Periodic Table" - a structured visual vocabulary that combines two psychological frameworks into a unified motion-design system. Color psychology provides the chromatic axis: warm hues (reds, oranges) represent tension, frustration, and assertiveness; cool hues (blues, greens) represent calm, openness, and agreement; transitional tones (yellows, purples) represent uncertainty, curiosity, and shifting positions. Shape psychology provides the morphological axis: angular, spiky forms convey conflict, defensiveness, and high emotional intensity; rounded, smooth forms convey receptiveness, empathy, and resolution. These two axes combine to generate a matrix of emotion states, each represented by a distinct bubble form - a specific combination of color, shape, size, opacity, and movement behavior. For example, a large, red, angular bubble pulsing rapidly represents strong disagreement, while a small, blue, rounded bubble drifting gently represents calm agreement. The system includes transitional animations (a bubble softening its edges as tension decreases, or warming in hue as frustration builds) that create a continuous, readable motion language. The research challenge was ensuring that these mappings were not arbitrary but grounded in established color-emotion and shape-emotion associations from developmental and environmental psychology. The team cross-referenced color psychology literature (warm colors as activating, cool colors as calming) with shape psychology research (angular shapes as threatening, curved shapes as approachable) to build a mapping framework that aligns with children's intuitive perceptions. The resulting periodic table organizes all possible emotion-bubble states into a systematic grid, allowing the design team to ensure visual consistency, avoid redundancy, and create clear distinctions between emotional states. This system serves as both a design tool (guiding the creation of new scenario content) and a pedagogical tool (helping children learn to "read" emotions through visual pattern recognition). The motion language embedded in the bubbles: speed, direction, oscillation, merging and splitting behaviors, all add a temporal dimension that reflects how emotions evolve during a conversation, rather than presenting them as static labels.
研究: This project investigates how interactive, AI-mediated role-play can support the development of negotiation skills in children aged 5-13 (grades K-8). Drawing on social-emotional learning (SEL) theory and child negotiation research, the study identifies a critical gap: while negotiation is a foundational interpersonal skill, it is largely absent from early education curricula. Existing data indicates that only 28% of children aged 6-8 can clearly articulate their needs in peer disputes, and that children with underdeveloped negotiation abilities face significantly higher rates of peer rejection by adolescence. The research proposes an emotion-visualized, voice-based application as an intervention tool. The design framework translates established negotiation principles: BATNA (anchoring, justification, and emotional regulation) into scaffolded, story-driven interactions with AI characters. The emotion visualization system, grounded in color psychology and shape psychology, maps internal states to external visual cues, enabling children to observe and interpret the emotional dynamics of a conversation as it unfolds. The study details the iterative, user-centered design process, including literature review, scenario development, interface prototyping, and usability testing with target-age users. Findings suggest that combining voice interaction, real-time visual feedback, and narrative framing creates an engaging and developmentally appropriate learning environment for practicing complex social skills.
灵感: Negotiabbles came from research on social-emotional learning, revealing a gap between children's need for conflict resolution skills and available tools. Research shows that children with weak negotiation skills at age 8 are 2.5 times more likely to face peer rejection. Existing tools focus on emotions but not the full negotiation cycle. Inspired by storybook visuals and color-emotion psychology, the bubble interface makes abstract emotional dynamics visible through responsive shapes and colors.
项目周期: The project started in December 2024 and finished in June 2025 in the United States.
操作流程: The user flow begins with story selection, where the child chooses a scenario drawn from common peer situations such as sharing a resource, resolving a disagreement, or joining a group activity. Each scenario is framed as a storybook chapter with illustrated AI characters. Upon entering a scenario, the child engages in voice-based dialogue with the AI character, who presents a negotiation challenge. The interface displays dynamic emotion bubbles above each character. These bubbles shift in color, size, and shape in response to the tone and content of the conversation, providing real-time visual feedback on emotional states. As the child speaks, the system processes their input and the AI character responds contextually, guiding the child through negotiation stages: stating needs, giving reasons, listening, proposing compromises, and reaching an agreement. At each stage, the scaffolding system offers gentle prompts if the child needs support (for example, a prompt to explain their reasoning or consider the other character's perspective). After the scenario concludes, the child receives a summary screen displaying which strategies were used, how emotional states shifted during the conversation, and specific areas for continued development. Progress is recorded in a personalized negotiation profile that tracks growth across sessions and strategy types. In multiplayer mode, two children engage in a guided negotiation with each other, with the AI serving as a mediator that monitors turn-taking, emotional escalation, and strategy use, ensuring both voices are heard and the interaction remains constructive.
团队成员: Zixuan Li (Product Design Lead)
Xuefei Wang (UX Design Lead)
Lydia (Tiansui) Leiwang (UX Motion/Visual Design)
Zilu (Ruby) Wang (UX Design)
Huimeng Lu (UX Design)