Negotiabbles Daim Ntawv Siv Hauv Tablet los ntawm Negotiabbles

Qhov qauv tsim Negotiabbles Daim Ntawv Siv Hauv Tablet los ntawm Negotiabbles yog tus yeej muaj nqis heev ntawm qhov khoom plig 2026 A' Design Award Hlau hauv Pawg Sib Tw Tsim Kev Kawm, Khoom Pab Qhia thiab Kev Cob Qhia.

HlauKev Kawm· 2026

Negotiabbles Daim Ntawv Siv Hauv Tablet

los ntawm Negotiabbles

Tus Neeg Siv: Negotiabbles

Tus Yeej A' Design Award Hlau hauv Pawg Kev Kawm

4,734

Tus Yeej Khoom Plig Tau Txheeb Xyuas

Txheeb Xyuas Qhov Xwm Txheej Khoom Plig rau #182529

Saib ntawm A' Design Award Tsab Xov Xwm Daim Phiaj Khoom Plig

Xim

Qhov Tsim

Txog Negotiabbles Daim Ntawv Siv Hauv Tablet

Negotiabbles yog ib daim ntawv siv hauv tablet uas qhia ntawv pab cov menyuam kawm ntawv qib K-8 xyaum txoj kev txawj sib hais haum. Daim app no muab cov xwm txheej uas cov phooj ywg ib txwm ntsib, xws li kev sib faib ib yam khoom lossis kev daws qhov tsis sib haum xeeb, los ua tej tshooj dab neeg uas muaj duab kos. Cov menyuam tham nrog cov cim tsim los ntawm kev txawj ntse cuav (artificial intelligence) thiab raug coj kom paub hais qhia lawv tej kev xav tau, muab laj thawj, mloog lus, thiab mus txog qhov kev pom zoo ua ke. Cov npuas kev xav saum txhua tus cim yuav hloov xim, qhov loj me, thiab tus duab kom qhia txog lub siab lub ntsws tam sim ntawd. Muaj ib qho screen sau qhia tseg txog cov tswv yim uas siv thiab kev vam meej thoob plaws txhua zaus kev kawm.

Qhov Lees Paub

Txog A' Design Award Hlau

Negotiabbles Daim Ntawv Siv Hauv Tablet yog tus yeej ntawm A' Design Award Hlau, ib qho kev lees paub muaj meej mom uas muab rau cov qauv tsim zoo uas ua tau raws li cov kev xav tau ntawm kev ua haujlwm thiab kev lag luam uas xav tau los ntawm cov khoom tsim zoo. Cov neeg yeej Hlau qhia txog kev txawj loj, kev paub tshwj xeeb siab, kev nkag siab ntawm cov kws tshaj lij thiab lub peev xwm tsim ntawm cov neeg tsim. Negotiabbles Daim Ntawv Siv Hauv Tablet xav tias yuav yog ib qho khoom tsim uas neeg hwm, qhuas thiab hlub uas siv tau thiab tsim tshiab. Cov qauv tsim yeej A' Design Award Hlau no sib xyaw cov kev coj ua zoo tshaj plaws ntawm kev lag luam thiab muaj cov yam ntxwv siv tshuab txawj ntse txuas nrog kev paub thiab txuj ci. Negotiabbles Daim Ntawv Siv Hauv Tablet tau txais kev hwm vim nws tag nrho thiab tsim los muab kev txhim kho rau lub neej uas pab ua rau lub ntiaj teb zoo dua.

Tom Qab Qhov Tsim

Pob Xov Xwm

Cov credit, cov neeg pab thiab cov ntsiab lus kev txawj ntse muab los ntawm tus tsim.

Yam Tshwj Xeeb: 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.
Qhov Loj & Ntim: 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).
Cov Ntsiab Lus: 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
Thev Naus Laus Zis Tsim Khoom: 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.
Kev Sib Tw Tsim Qauv: 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.
Kev Tshawb Fawb: 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.
Kev Txhawb Siab: 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.
Lub Sij Hawm Ua Hauj Lwm: The project started in December 2024 and finished in June 2025 in the United States.
Txheej Txheem Ua Hauj Lwm: 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.
Cov Tswv Cuab Pab: 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)