Iron Mobile Technologies, Applications and Software Design · 2023
Ling Chatbot App
by Qian Wan
- A' Design Award 2023 Iron Winner in Mobile Technologies, Applications and Software Design
- Awarded April 15, 2023
- CLIENT: Qian Wan
- Estimated Number of Design Views: 20,477
- Verification code 760570DE9C · Verify this award
About Ling Chatbot App
Ling is an educational chatbot mobile application that provides reliable learning resources about equity, diversity, and inclusion to help Chinese international students to learn and prevent discrimination and harassment. The app also connects users to their school’s trustful case report sources. Through humanized conversational interaction, the app makes people talk about difficult topics easier.
Press Kit
- Unique Properties
- Ling is a mobile based educational purposed chatbot that provides real time inquiry functionality and learning resources about equity, diversity, and inclusion to help Chinese international student to identify and prevent discrimination and harassment that happened to them. The app also connects users to their school’s trustful case report sources.
- Dimensions & Packaging
- The app is designed for iOS.
- Tags
- Social Equity, Chatbot, mobile app design, User experience, Information Architecture
- Production Technology
- I used Miro board to synthesize research findings. The interface design was done through Figma, Sketch, Figma, and Illustrator.
- Design Challenge
- It was hard to initiate such a difficult topic with people who experienced racial discrimination. Sharing my own stories that resonate with people helped me drive the conversation. I also found that much existing research has been done only on post-discrimination experience, but it doesn't cover all the needs. People often didn't realize when things happened, not to mention to look for help in time. After mapping out their journey, I realized that lack of knowledge leads to those consequences.
- Project Duration
- The project started in June 2021 in LA and finished in August 2022 in Seattle
- Operation Flow
- The first time users will be asked to connect with their student account so that the app will provide the most easy to access and trustful resource for the students. When users are not sure if they experienced racial discrimination, simply by chatting with Ling, she will use a conversation based approach to identify the racial discrimination types step by step and provide support by connecting users with their school’s EDI department.
- Research
- I interviewed 11 Chinses international students who are currently studying in the USA and who had experienced racial discrimination. I mapped their journey, mood, and reaction with the user journey to identify the design opportunity. Then I did literature research to learn how to measure racial discrimination systematically.
- Inspiration
- COVID19 has driven racism and violence against Asians. Chinese international students who are coming from a very distinct culture study abroad, and are new to a culture. They are less sensitive to racial discrimination when it is happening to them. Although those aggressions are often subtle, they can be just as harmful to health and well-being.
Colors of Ling Chatbot App
Design Interview about Ling Chatbot App
The inspiration behind the creation of Ling came from the urgent need to address the rising racism and violence against Asians, particularly Chinese international students, in the wake of the COVID-19 pandemic. These students, who come from a distinct culture and are studying abroad, often face discrimination and harassment but may be less sensitive to it due to their unfamiliarity with the local culture.
The goal was to create a mobile-based educational chatbot that could provide real-time support, learning resources, and guidance on equity, diversity, and inclusion (EDI) to help these students identify and prevent discrimination and harassment. Ling aims to bridge the gap in knowledge and provide a humanized approach to addressing these challenging experiences.
I intend to actively promote Ling to raise awareness among educational institutions, student communities, and relevant stakeholders about the importance of addressing racial discrimination and providing support.
Since the onset of the COVID-19 pandemic, I have become increasingly aware of the challenges and issues faced by Asians, particularly in relation to the rise in racism and discrimination. This heightened awareness has prompted me to engage in conversations and actively seek to understand the experiences of Asians who have encountered similar difficulties.
By designing this work, the goal was to bridge that gap and provide a solution that could empower students to recognize discrimination, express their experiences, and access trusted resources and support. It was driven by the desire to foster a safer and more inclusive environment for these students, enabling them to navigate their studies abroad with greater confidence and well-being.
What sets the design of Ling apart from other similar or resembling concepts is its focus on the specific needs of Asian international students facing racial discrimination. While there are other platforms and resources that address equity, diversity, and inclusion (EDI), Ling takes a unique approach by combining real-time inquiry functionality, personalized learning resources, and connection to trusted case report sources within the students' own schools.
I utilized a variety of design tools to aid in the development and execution of the design. Some of the key design tools that were employed included user research where I used tools such as interview guides, note-taking apps, and audio/video recording devices. These tools helped capture and document the experiences and perspectives of the users accurately. As for design, I used Figma and After Effects for prototyping.
Yes, the design of Ling is influenced by data and analytical research. Extensive research was conducted to gain insights into the experiences, needs, and challenges. I conducted interviews with 11 Asian who were currently studying or working in the USA and had experienced racial discrimination. These interviews provided valuable firsthand insights into their experiences, emotions, and reactions to discrimination. The interviews focused on understanding their journey, mood, and reactions, helping identify design opportunities and areas of improvement.
Participating in an international design competition provides a platform to share the design concept and story behind Ling with a global audience. It offers the opportunity to raise people’s awareness in post-COVID era, and it inspires more people contribute to and address the issue.
During the design process of Ling, I learned and improved myself. Working on a project focused on the experiences of Asians highlighted the importance of cultural sensitivity in design. It deepened my awareness of cultural nuances, communication styles, and diverse perspectives. This experience broadened my horizons and improved my ability to design inclusively for users from different cultural backgrounds.
Grand Interview about Ling Chatbot App
The inspiration for Ling really came from observing the unique challenges that many Asian international students, particularly Chinese students, face when studying abroad. During the pandemic, I saw a troubling rise in racially motivated aggression against Asian communities. In particular, international students—already adapting to new academic and social environments—were especially vulnerable. Many students I spoke with felt isolated, unsure of how to respond to incidents of discrimination or subtle biases, and sometimes were even unaware that what they were experiencing was a form of harassment.
I did it intentional. We’re dealing with sensitive and deeply personal topics, so the interaction needed to feel as human and empathetic as possible. A chatbot format lets users feel like they’re having a private, supportive conversation rather than completing a sterile questionnaire or navigating through a typical app.
I kept the information architecture very streamlined. Instead of overwhelming users with long lists of articles or resources, we embedded bite-sized educational content directly into the chat experience. When users bring up a question or concern, Ling responds in a way that’s both informative and conversational
Through these interviews, I uncovered a consistent pattern: students often weren’t sure if what they were experiencing counted as discrimination, or they felt uncertain about how to react. This ambiguity led many of them to dismiss or internalize their experiences, often at the expense of their well-being. These findings directly influenced Ling's core features.One of the main features that emerged was Ling’s ability to help users identify different types of discrimination in real-time. By talking to Ling about their experiences, students can describe situations and receive feedback on whether what they encountered could be classified as a form of discrimination. This feature was inspired by students who expressed a need for clarity and validation.Another significant feature is the direct connection to their school’s resources, like equity, diversity, and inclusion (EDI) departments. Many students I spoke with didn’t know how to seek help within their institutions or feared that their concerns wouldn’t be taken seriously. By integrating a direct link to trusted resources, Ling helps them take immediate action, whether it’s reporting an incident or accessing support services, without having to navigate complex administrative structures on their own.
Every university has a different system for handling discrimination reports, so we had to work closely with each institution to understand their protocols and technical limitations.
Each city has its own mix of cultures and challenges when it comes to discrimination, and being exposed to different perspectives helped us better understand the range of experiences international students might have.
The solution was to design a step-by-step approach that felt more like a guided conversation than an assessment. This approach allowed us to simplify complex concepts without compromising depth or empathy.First, we broke down the identification process into digestible, relatable prompts, guiding students through their experiences gradually. Ling uses simple, non-technical language to ask questions like, “Did you feel uncomfortable with something someone said or did?” instead of directly probing for discrimination indicators. This lets users reflect without feeling pressured to label their experience immediately.Next, we used conditional branching in the dialogue, where Ling’s responses change based on the user’s input. This made interactions feel personalized, so Ling could offer tailored support, such as a follow-up question to help users articulate what they’re feeling. This dynamic helps Ling feel genuinely engaged, offering empathy while leading users gently toward recognition of what they might be experiencing.
One example is when users describe an interaction where they felt uncomfortable but aren’t sure why. Ling might respond by asking, “Did someone make a comment about where you’re from or how you speak?” and then explain how assumptions or remarks based on stereotypes can be microaggressions. For instance, if a student describes being complimented for speaking “good English,” Ling explains that while it may seem positive, it can imply an expectation of inadequacy based on their ethnicity—a common type of microaggression. This helps users pinpoint the subtle nature of such comments and understand the underlying bias.
One feature I'm exploring is a peer support network, where students can anonymously share their experiences or advice with each other through Ling, moderated to ensure safety and privacy.
I regularly collect anonymous surveys and conduct follow-up interviews with volunteer users to gauge how helpful Ling has been in real-life situations.