Iron Education, Teaching Aid and Training Content Design · 2026
Negotiabbles Tablet App
by Negotiabbles
- A' Design Award 2026 Iron Winner in Education, Teaching Aid and Training Content Design
- Awarded April 15, 2026
- CLIENT: Negotiabbles
- Estimated Number of Design Views: 4,487
- Verification code 8C176BE631 · Verify this award
About Negotiabbles Tablet App
Negotiabbles is an educational tablet application that helps children in grades K-8 practice negotiation skills. The app presents common peer situations, such as sharing a resource or resolving a disagreement, as illustrated story chapters. Children speak with artificial intelligence characters and are guided through stating needs, giving reasons, listening, and reaching agreement. Emotion bubbles above each character change in color, size, and shape to show emotional states in real time. A summary screen records the strategies used and progress across sessions.
Xuefei Wang's Negotiabbles Tablet App operates within the expanding domain of digital social-emotional learning platforms, representing a thoughtful synthesis of contemporary educational technology design principles and character-driven pedagogical frameworks that seek to render complex interpersonal skill development accessible and engaging for diverse learners. The interface architecture demonstrates sophisticated understanding of cognitive load theory through its strategic simplification of visual elements, deploying geometric character forms constructed from elementary shapes that function simultaneously as engaging avatars and cognitively efficient visual anchors, reducing processing demands while maintaining aesthetic appeal and emotional resonance. The chromatic strategy employs a carefully calibrated pastel palette punctuated by vibrant multicolored typography, creating an environment that signals psychological safety and playful exploration while maintaining sufficient contrast for legibility and accessibility compliance, the warm-to-cool color progression across the letterforms suggesting inclusivity and chromatic diversity without hierarchical privileging of particular hues. Compositionally, the dual-screen presentation reveals pedagogical intentionality, the upper welcome screen establishing the application's friendly character-populated universe and clearly articulated entry points through contrasting button treatments, while the lower active learning screen demonstrates the focused dyadic interaction model through which skill development occurs, the generous negative space surrounding the two primary character forms directing attention toward the conversational exchange and reducing visual competition during critical learning moments. The dialogue text "Oh no, that stinks. I'll be really careful, I promise!" exemplifies the application's approach to modeling empathetic communication and constructive response to setbacks, embedding social script examples within naturalistic conversational contexts that learners may encounter across various negotiation scenarios. Technical execution demonstrates fluency with vector-based digital illustration optimized for high-resolution tablet displays, the crisp edge definition and flat color application ensuring visual clarity across varied screen sizes and lighting conditions, while the minimal geometric aesthetic aligns with contemporary design trends emphasizing clarity and directness. The character design vocabulary draws subtle inspiration from mid-century Scandinavian children's illustration traditions and contemporary kawaii aesthetic movements, creating forms that feel simultaneously retro-familiar and freshly contemporary, their simplified facial features allowing learners to project emotional states and intentions onto relatively neutral forms, facilitating identification and role-play engagement. The small avatar toolbar suggests systematic progression through multiple characters or scenarios, implying curriculum structure and achievement tracking embedded within the playful visual system, while the lightbulb icon signals scaffolded support available when learners encounter difficulty, demonstrating attention to differentiated instruction principles. This application invites consideration of how digital learning environments can harness visual design as pedagogical infrastructure, wherein aesthetic choices become active contributors to learning outcomes rather than mere decorative surface, the approachable character forms lowering affective barriers to engagement with potentially anxiety-inducing interpersonal skill practice, the clear interface architecture supporting autonomous navigation and reducing cognitive friction, and the conversational modeling providing concrete examples of constructive communication strategies. How might character-mediated learning environments uniquely position learners to explore interpersonal scenarios with reduced social risk while maintaining sufficient authenticity to support transfer of learned skills into real-world contexts?
Press Kit
- Unique Properties
- 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.
- Dimensions & Packaging
- 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).
- Tags
- 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
- Production Technology
- 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.
- Design Challenge
- 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.
- Project Duration
- The project started in December 2024 and finished in June 2025 in the United States.
- Operation Flow
- 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.
- Research
- 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.
- Inspiration
- 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.
Colors of Negotiabbles Tablet App
Grand Interview about Negotiabbles Tablet App
The Emotional Periodic Table emerged from a key insight during our research. We found that negotiation is not only about emotions, but also about the tension created when different perspectives, needs, and communication styles interact. Across different individuals and cultures, people often negotiate in very different ways, yet many are unaware of how their words, tone, or actions are actually perceived by others.This led us to ask a fundamental question: how can we make these invisible dynamics visible? We wanted children to not only recognize their own feelings, but also understand the emotional impact of their behavior and the shifting tension within a conversation. Through multiple rounds of exploration, we discovered that color, shape, and motion could work together as a shared visual language. Colors represented emotional states and intensity, shapes reflected communication patterns, and motion visualized how interactions evolved over time.The breakthrough was realizing that negotiation could be taught through visualization rather than explanation. The Emotional Periodic Table became a system for making emotions, intentions, and interpersonal dynamics tangible. By helping children see what is normally invisible, the experience encourages greater self-awareness, empathy, and understanding of how their choices influence others during a negotiation. At the same time, transforming these abstract social dynamics into colorful, interactive visual elements makes the learning process more fun, engaging, and approachable for young learners.
Negotiabbles addresses the gap by replacing passive learning with active, voice-driven practice. Most Social and Emotional Learning (SEL) tools teach children about emotions through videos or multiple-choice scenarios. Negotiabbles puts children inside a real conversation where their words have immediate, visible consequences, combining AI role-play, real-time emotion visualization, and fairytale distancing, in a way no existing tool does. What truly differentiates us is the emotion visualization system. Rather than labeling feelings with text or static icons, we built a living visual language where warm colors and angular shapes signal tension, while cool tones and rounded forms communicate calm. Children absorb it intuitively through play, without instruction.This was confirmed powerfully during usability testing. The moment that surprised us most was watching children spontaneously narrate the emotion bubbles mid-conversation, pointing at the screen and saying "see, he's getting angry now," accurately reading emotional states through color and shape alone, before we had explained the system at all. We expected to guide children through the visual language. Instead, they taught themselves. It revealed something that has since shaped our broader thinking: Children engage far more deeply when emotions have a visible and concrete form rather than remaining abstract beyond their reach.
The voice-first decision was both pedagogical and deeply human. Negotiation is a spoken, real-time skill, and teaching it through taps or text would be like teaching someone to swim without water. When a child speaks aloud to advocate for themselves, they practice the real cognitive and emotional experience of finding words under pressure, regulating tone, and responding to another voice, which is exactly what they need in a playground dispute or classroom disagreement.One of the design challenges we faced was handling silence and hesitation. When a child freezes mid-conversation, that moment carries real emotional weight. In peer interactions, silence can feel like failure, and we couldn't let the app replicate that. Our solution was to deploy AI as a sensitive, in-the-moment guide. When hesitation is detected, the AI character offers a gentle contextual nudge like "how about asking why they feel that way?", keeping the conversation alive without breaking immersion or undermining the child's sense of agency.The feedback loop is deliberately multi-sensory: the AI responds verbally, emotion bubbles shift in real time, and on-screen captions support younger readers, delivering emotional, auditory, and visual feedback simultaneously. Across the K–8 range, the system scales with the child. Younger learners receive shorter exchanges and more frequent prompts, while older children navigate complex scenarios with greater nuance and less scaffolding.
One of our core design principles was that children should experience Negotiabbles as a story and game first, not as a lesson. While the project draws heavily from developmental psychology, negotiation theory, and AI-powered personalization, we were careful not to expose that complexity directly to young users. Instead, we translated research insights into playful interactions, memorable characters, and emotionally engaging scenarios.This was especially important because negotiation often involves disagreement, conflicting perspectives, and moments of tension. For many children—and even adults—these situations can feel intimidating. We wanted to create an environment where children could safely explore difficult conversations, make mistakes, and experiment with different approaches without fear of judgment or failure. The goal was not to teach them the “correct” answer, but to help them build confidence in navigating differences.The AI works mostly behind the scenes, adapting conversations and feedback to each child's responses, while the interface focuses on curiosity, imagination, and positive reinforcement. We often described our approach as “hiding the vegetables in the soup.” The science provides the structure, but the child experiences a safe, playful world where learning happens naturally through exploration. We believe children are more willing to engage with challenging social situations when they feel emotionally secure, and that balance between rigor and warmth became a guiding principle throughout Negotiabbles.
The most difficult design decision was determining how much freedom to give the AI.Negotiation is inherently unpredictable. To help children develop real-world skills, conversations needed to feel authentic, dynamic, and responsive rather than following scripted decision trees. Yet fully open-ended AI interactions risked overwhelming children, drifting away from learning goals, or creating inconsistent experiences.This challenge led us to rethink AI not as a conversational partner, but as an adaptive learning facilitator. We designed AI-powered characters that respond uniquely to each child while remaining grounded in carefully structured negotiation frameworks and age-appropriate story scenarios.Working through this tension fundamentally shaped the product. We realized that children learn negotiation best when they are given genuine agency within safe boundaries. The result is an experience where every conversation feels personal and immersive, while still guiding children toward empathy, reasoning, compromise, and self-advocacy. It also transformed our team's understanding of educational AI: effective learning does not come from giving children the right answer, but from creating the right space to discover it themselves.
One of the most challenging questions we faced was how to make emotions visible without reducing them to labels, scores, or emojis. Early explorations relied on familiar approaches: emotion icons, mood meters, and text-based feedback. While children could recognize these signals, they struggled to understand how emotions influenced the flow of a conversation. We realized that negotiation is not a static emotional state. It is a dynamic relationship between people. This insight led us to the bubble system.We wanted to create a visual language that could be understood intuitively across ages, cultures, and reading abilities. Drawing from color psychology, emotional design research, and social-emotional learning frameworks, we began mapping emotional qualities to visual properties. Saturated colors communicate stronger emotional intensity, while softer tones suggest calmness and openness. Rounded forms feel approachable and cooperative, whereas sharper contours express tension, assertiveness, or conflict. Motion became equally important: faster movements indicate emotional activation, while slower, smoother behaviors communicate stability and reflection. Transparency helps reveal confidence, uncertainty, and emotional clarity.The hardest part was balancing expressiveness with simplicity. Early versions were either too abstract for children to interpret or too literal to feel engaging. Through multiple rounds of refinement, we continuously adjusted color ranges, shape transformations, animation timing, and interaction behaviors. We also paired bubble states with character animations and narrative context to reinforce emotional meaning from multiple channels.Over time, the bubbles evolved from a visual effect into the core interaction language of Negotiabbles. Rather than telling children how they feel, the system allows them to see emotions unfold, collide, soften, and grow throughout a conversation. The result is a living emotional mirror that transforms invisible social dynamics into something tangible, playful, and learnable.
Negotiabbles has a multiplayer gameplay mode that simulates low-stakes practice with real people, where two or three children can practice negotiation with each other in realistic scenarios and see their conversations visualized on screen. The AI serves as a mediator that prompts questions toward a resolution. This gameplay mode makes Negotiabbles playable across a wider range of environments — at home with siblings, in the classroom with classmates, and even during real-life conflicts, with AI helping to guide resolution in the moment.We plan to expand Negotiabbles’ educational scaffolding by personalizing the multiplayer learning progression according to each player’s age, personality, learning goals, and the specific scenarios they encounter day to day. A more granular progression could sequence concepts with both players’ specific needs in mind, scaling complexity accordingly and keeping the focus on each player’s individual needs and personality.In the future, we also envision Negotiabbles deepening its AI mediation layer as the platform matures. The AI mediator would no longer be a passive participant, but an active pedagogical presence — explaining its reasoning and narrating its own interventions, teaching children to recognize negotiation patterns in real time and preparing them to navigate real-world conflicts.In classrooms, Negotiabbles could provide a teacher-facing dashboard that highlights children’s learning progress and surfaces anonymized, class-level insights about which negotiation strategies children struggle with most and which conflicts arise most frequently. School counselors could use longitudinal negotiation profiles to identify students needing deeper social-emotional support, embedding the platform within a school’s broader wellbeing infrastructure.
The Negotiabbles team’s guiding principle around data and privacy is that data should serve the child first, transparency should be age-appropriate and contextually meaningful, and the architecture should be designed so that what is measured cannot easily be repurposed beyond its original pedagogical purposes.With the app’s pedagogical goals in mind, we aim to surface behavioral and performative data that is informative for children and their caregivers, and keep personal data and raw logs private.The team made a deliberate choice to give children direct, age-appropriate access to their own data in visual form — for example, the post-session summary and children’s negotiation personality profiles. This treats children as active participants in their own development rather than passive subjects of measurement. Parent-facing summaries could extend this transparency to caregivers without exposing raw behavioral logs, translating data into actionable developmental language instead.Personal data and raw logs — such as granular emotional data captured during peer-to-peer multiplayer sessions — should be kept private from players and caregivers alike, as they could be misused if taken out of context. A child’s pattern of emotional escalation in conflict situations is developmentally useful information for the app’s scaffolding engine, but surfacing it to parents or teachers without careful framing risks labeling or stigmatizing children based on in-app behavior that may not reflect their real-world character.
One of our earliest decisions was that the growth-tracking system should never feel like a report card. Through our research, we found that negotiation is not a skill that improves along a single linear path. Different situations require different approaches, and effective negotiators develop a range of strategies rather than a single “best” one. A child who practices compromise in one conversation and self-advocacy in another has not become more or less successful—they have expanded their toolkit.This perspective shaped how we visualized growth within Negotiabbles. Instead of focusing on scores, rankings, or performance metrics, we designed the profile to highlight exploration and diversity of strategies. Children can see which approaches they have practiced over time, such as empathy, reasoning, compromise, or self-advocacy. Growth is represented as an expanding landscape of experiences rather than a number increasing. The visual language also builds upon the Emotional Periodic Table, using colors, shapes, and motion to help children recognize patterns in their communication style without attaching value judgments to them.During testing, we found that children were naturally curious about these visual profiles. Rather than asking whether they had achieved a higher score, they were more interested in discovering new strategies and seeing how their profiles evolved over time. Caregivers responded positively as well, particularly when growth was framed as reflection rather than evaluation. Early concepts that relied on ratings and scores felt overly academic and sometimes created unnecessary pressure. Narrative summaries and visual storytelling proved far more effective, helping caregivers understand a child's development while preserving a sense of curiosity, confidence, and enjoyment.Ultimately, our goal was to encourage children to view negotiation as a lifelong practice of learning, adapting, and understanding different perspectives. By focusing on growth, exploration, and self-awareness rather than performance, we were able to create a system that motivates continued engagement without introducing anxiety or fear of failure.
One of the most interesting challenges was designing a system that could simultaneously support learning for children and content creation for the team. The Emotional Periodic Table was originally created to help visualize the emotional states, interpersonal dynamics, and negotiation tensions that sit at the heart of Negotiabbles. We wanted to make these normally invisible aspects of communication tangible so children could better understand both their own feelings and the impact of their actions on others.As the project evolved, we realized that the same framework could also serve as a shared language for designers, writers, developers, and AI engineers. When creating new scenarios, the team needed a consistent way to represent emotions, intentions, and interaction patterns. The table helped define how different emotional qualities could be expressed through color, shape, and motion, ensuring that new content remained coherent while still allowing for creativity and variation.What made this possible was that the system was built on perceptual patterns that children already intuitively understand. Warm, saturated colors often feel more intense, while cooler tones feel calmer. Rounded forms tend to feel approachable and safe, while sharper forms can suggest tension or disagreement. Rather than teaching children an abstract code, we built upon visual instincts that already exist across many everyday experiences.The balance between rigor and simplicity came from keeping the structure consistent while allowing the experience to remain playful. Children never need to study the framework directly. Instead, they encounter the same visual relationships repeatedly through stories, characters, and conversations. Over time, these patterns become familiar and meaningful without requiring formal instruction. In that sense, the Emotional Periodic Table functions much like the grammar of a language: it provides structure behind the scenes, while the learner engages naturally through use.By making emotions and negotiation dynamics visible, the framework supports both scalable content creation and meaningful learning. At the same time, transforming these abstract social concepts into colorful, interactive experiences helps make negotiation feel more approachable, engaging, and enjoyable for young learners.