CMU M.Des. Interaction Studio 2, 12 weeks
Devika Khowala, Hajira Qazi, Shengzhi Wu
Sketch, Principle, After Effects
Each year, there 1.18 million international students in the United States. Many of them go through a process of acclimation that can be, at times, stressful and overwhelming.
During our M.Des. Studio 2, which attempted to explore the connection between artificial intelligence and learning, we attempted to design a solution that would create a more inclusive environment for international students on campus. We framed out design challenge as follows:
We followed a process with 3 phases of research: exploratory, generative, and evaluative. As a result, we were able to experiment with a variety of research methods, which led to some valuable insights and concept directions.
We began by conducting exploratory research with international students on campus to better understand what pain points they encountered and how they overcame them when first arriving to the US. We used a variety of research methods to get at these questions. Methods like interviews, surveys, journey mapping, storyboarding, and letter writing were leveraged.
Through this research we discovered some initial insights that guided us moving forward:
1. People largely rely on social interaction as a way of adapting to a new culture. Community and a social network are key to this process.
2. People can’t prepare for every situation. Sometimes they need help in the moment of an interaction they could not have prepared for.
3. Because the topics of learning are so varied, resources for immigrants are fragmented and hard to find.
After our exploratory research, we began generative research with the goal of sparking ideas and concepts around how international students can overcome the various hurdles we heard about earlier.
We held a two part participatory design sessions in which we identified the most common problematic scenarios international students come up against and then generated solutions to those scenarios. With these solutions we were not looking for 1-to-1 solutions, but rather looking for themes that emerged which would inform our final design.
We generated the following insights through participatory design workshop:
1. A bi-directional cultural learning process makes the acclimation process for immigrants easier and more effective than unidirectional approach.
2. International students try to avoid unfamiliar situations they anticipate to be difficult, and will go out of their way to do so.
3. Having a supportive community is important to the mental and emotional wellbeing of international students.
We then developed 3 concept directions to speed date with international students. We received positive feedback about the social network with facilitated interaction and decided to move forward with this concept. There were a few reasons for this. First, and most importantly, a network would allow for us to organically create bi-directional learning between international and American students. Second, this platform created an incentive for both international and American students to join. And finally, by creating an intervention before students arrive on campus, we are able to create a more welcoming environment before students even arrive in the US.
With our concept direction set, we began formalizing the user journey and creating wireframes. We developed various iterations of the key features and began gathering feedback from users.
We focused much of our testing on the chat intervention and matching experiences, as those were integral to our concept and where artificial intelligence is leveraged most.
We received vital feedback from our testing that we then integrated into our final designs.
1. People didn't like when the bot made assumptions about them or put words into their mouth.
2. People liked having multiple options provided to them, as they were unsure about the accuracy of the bot intervention.
3. People preferred having more information about their matches, but were actually okay with having anonymized matches. Some saw the value in not the anonymity of matching.
To better understand how the facilitation bot would function during a conversation, we also conducted conversation analysis on conversations that we setup between incoming CMU Design students. We printed out these conversations and noted points of breakdown or missed opportunity.
We discovered that breakdowns didn’t happen as often as expected, but there were lots of opportunities cultural learning that were not capitalized on. That shifted our thinking about the bot from being about fixing breakdowns to proactively creating opportunities for cultural learning as a way of increasing engagement between students.
The result of all this research and iteration is the Naya platform for incoming students. Naya is a social networking platform for incoming students that leverages AI to facilitate bidirectional cultural learning through person to person conversation.
When students enroll at a university, the school will invite each incoming class to join this platform prior to arriving on campus. By creating an intervention that allows students to begin cultural learning before stepping foot on campus, we hope to lessen the effects of cultural shock by providing international students with access to key knowledge and creating a support network prior to arrival.