Final Demo Documentation
VIA is an adaptive mobile application that helps its users to better understand an unfamiliar culture without intruding upon their whole experience. The app aims to give users relevant information regarding the behaviors and norms of an unfamiliar culture, at the necessary times, in order to help him/her learn, adapt, and acclimate into said new culture.
VIA uses data various mobile phone sensors (such as the gyroscope, accelerometer, pressure sensor, light sensor, GPS, microphone, among others) to learn about the context surrounding the user. Once VIA has details about the user’s current context, it can push notifications to the user whenever it feels that the user likely needs information regarding a cultural norm. VIA’s level of proactivity, timing, and the information meter it provides to the user is based on the situation’s defined “impact level” (see Milestone 3: Finding 3).
The data that the device displays to the user is drawn from two main sources: a search of relevant norms and traditions from search engines (such as Google, Wikipedia, travel blogs, etc) as well as crowd sourced data. Crowd sourced data comes from both newcomers who supply information about cultures they visit, as well as natives supplying information about their own culture. All this data is shown in a systematic list format. The user can choose to read, delete, or even archive notifications — these user input interactions help VIA better understand the user’s personality and preferences, so it can learn and adapt to the user’s needs. Furthermore, the ambiguity level of the information displayed by VIA can be adjusted by the user via the “Information Meter.” For instance, if the user is feeling more adventurous, s/he may set the information meter to “low.” If the user is not feel adventurous at all, the information meter may be set to “high.” Based on our formative study, we found that some people are more exploratory than others, so our system does respect those personal differences and nuances.
With Via, we aim to empower travelers to comfortably adapt, learn and fit into new cultures, thereby positively promoting cross cultural exploration and relations.
Goals for the Demo
The demo showcases how VIA helps a traveler as s/he enters an unfamiliar environment for the first time. VIA alerts the user of a norm that s/he is not familiar with based on the cultural background of the user. We also showcase how the participant can use VIA to learn about the environment as well. Finally, we showcase how the system adapts its behavior based on the user’s experiences.
The demo is divided into two scenes. The first scene demonstrates how VIA proactively helps a traveler in an unfamiliar situation, and the second scene displays how VIA adapts to the traveler’s experiences. A narrator leads the audience through the scenes to give them a better understanding of what is being depicted. Also, the interactions between the traveler and VIA are projected on a bigger screen so the audience can follow along.
As a part of the first scene, a traveler (confederate 1) enters a restaurant in a far away country named Capella. He is in a hurry to meet an important client. The restaurant setup consists of two tables: one for a traveler, who has a prototype of the app on his phone, and the second for an audience member. Since the traveler is in a hurry, he opens up the app and sets the information meter level to high, so that he gets straightforward information. An audience member will be invited to be the other diner at the restaurant. The norm set for the restaurant is to tip the waitress before the meal is served. After hearing a buzzing sound, created by another confederate (confederate 2), the traveler will look at his phone and find out that he has to tip the waitress (confederate 3) before the meal. It will be noticeable that the waitress is ignoring the audience member, since the audience member is not aware of this tipping behavior. The traveler, on the other hand, abides by the Capellian social norm and the waitress is really kind to him. He then looks up the menu and does not have a clue about some of the items on it. He opens up VIA, clicks a picture of the menu item, and gets all the information that he needs as the information meter is set to high. He orders his food and leaves the restaurant satisfied, where as the audience member is still not served.
The second scene involves the same traveler from scene 1 going to a separate restaurant after a successful meeting with his client. This time, there is no buzz, as we want to showcase that VIA understands that the traveler has been to a restaurant before and now understands the tipping norm. The traveler is in no hurry this time, and is feeling a little adventurous. Hence, he adjusts the information meter in VIA to be low, and proceeds to look up food items on the menu. VIA gives him clues about the food, so he can make decisions on his own with only a little guidance. He tips the waitress upfront, eats his meal and leaves the restaurant satisfied again.
The demonstration includes props like posters, plates, table cloths, spoons, menus, etc to make the restaurant scenes as realistic as possible.
The demo does not capture certain aspects of the system. For instance, a user can get timely notifications based on a place of his choice. This feature is really useful if the traveler wants to learn about certain cultures before he arrives at a place and be prepared for the same. This is something the demo fails to display. Hence the demo fails to display the pre-departure actions that the traveler can take in order to make his/her travel more meaningful.
Furthermore, the user can not only click pictures but also ask VIA, via text or a voice note about something that s/he comes across during her/his travel. These text and voice input features are not displayed in the demo.
Also, the crowdsourcing ability of the system is left unexplored during the course of this demo.
The demo was well received by the students and the faculty. Most of the questions asked by the students were about information meter and level of proactivity of our app. We tried to demo the use cases where the user would have the option to set the information meter based on his curiosity level and other external factors. But, the students were confused about the trigger that would let the user know the appropriate amount of information that is required for any social context. We later hammered it out that the user will always determine the level of information provided by our app. If the user is feeling adventurous and curious he might want to limit the amount of information that our app provides. In other cases, when the user is in a hurry or he is feeling less inquisitive, he might turn up the information meter and receive comprehensive info about the culture, norms, place and food.
We did not demonstrate the level of proactivity of our app. Though, in the presentation we described it extensively. There were questions around intrusion by our app at inappropriate places and time. We answered this question by giving the example of a high impact social situation where our app would be highly proactive and would buzz to alert the user before he breaks any social norms. We could have demonstrated this example, but the limitation of time prevented us from doing so.
Lastly, the students had doubts regarding the collection of information from the user to our app. We agree that there should all types of reputation/recommendation rules to validate and authenticate the information provided by the users. We also agree that while crowdsourcing the information provided by similar users should be given priority, as that information will be more relevant.
In a nutshell, the feedback and the insights provided by our audience match our concern and priority list. We have given due thoughts to each of the problems above and have sought the solutions from our data of User Enactments and Interviews. So, it seems like we are headed in the right direction.