Week 10 – Ting and Jason

Smart app for meetings.

We are designing an app to record, analyze, and provide related references for group meetings. 

Inspiration:
Every time during the studio critique, guest crits always give us so many references and suggestions which are so hard to catch up in such short time. We usually take notes on the notebook but still miss out a lot. Also, we all have the experience that the crit gave an unsure name or terms which needed to be looked up afterward. Record the whole conversation could be a way to solve this problem, but how can we use Machine Learning to improve this experience?

Questions:
We followed this guideline from Human-Centered Machine Learning by Josh Lovejoy and Jess Holbrook to start off.

  • Describe the way a theoretical human “expert” might perform the task today.
    Ans:
    1.We would expect the expert to check if anyone mentioned incorrect information.
    2.to differentiate small talk/joke/sarcasm.
    3.to read the tone of the members. Who was agree or against with some certain idea?
    4.Categorize the transcription by recognizing the sound.
    5.Look up the dictionary or google.
  • If your human expert were to perform this task, how would you respond to them so they improved for the next time? Do this for all four phases of the confusion matrix.
    Ans:
    1.The user will be asked to delete unrelated reference on the report tab.
  • If a human were to perform this task, what assumptions would the user want them to make?

Week 10 – Franky Wang

App design for smart cars

+++ Group work with Yin Hu +++

We are designing a mobile app to provide automatic remote service for cars that allow users to control their smart car accessories and stay informed about the vehicle conditions when they are not in the car cabin. Also, users can make simple adjustments to car functions from the app for better convenience. 

App MapWireframe

WK10 Yin Hu & Franky Wang

Project3

app map

Wireframe

Feedback:

  1. consider if the user is a passenger.
  2.  buttons in the index page, buttons in other tabs, such as buttons in the safety tab, their positions makes users feel confused.
  3. tap the button to enter and tap it again to exit, users may don’t know how to use it.
  4. the car finding, the location detection technology?
  5. the approach to connecting cars may not be so convenient.

Week 8 Feedback and Paper Prototype_Jean

Feedback from the first prototype and user testing

  1. In the “Data Input” part, it should be input from other devices like iPhone app, because it is hard for the users to input all the data in the TV.
  2. In the Exercise part, there should be an option to add other family members, because there might be the exercise that they wanted to play together.
  3. Many of the headers look like the menu bar, try to differentiate it.

Week8_Qizhao(Eric)

Last week, I made a paper prototype and did a user test. Here is some feedback I got from user testing:

  1. Since that AppleTV doesn’t have the API to connect to Facebook and Twitter, the login part of the app may be tricky;
  2. The position of the image of the restaurant gives users the illusion that it is clickable. Why not make it clickable and try to add more detail to it.
  3. The function of sending invitation is hard to realize in AppleTV.

So I change my concept a little bit. In this version, the main value of the app will be searching interesting restaurants and enable users to see the 360-degree images of the restaurants so that they can know if the environment of the restaurants is good or not. What’s more, users can also check the menu and see the food intuitively.

Here are the wireframe and the visual interface.

 

WEEK 9:

User test feedback

  1.  The users tried to select the profile picture in the upper right corner but the profile picture was not selectable. so I decide to delete it.
  2. The users want to see more contents on the homepage.
  3. The users were confused about the categories.

Final prototype: https://marvelapp.com/62851b1/screen/40297763

 

Apple TV Final

 

In this Baby Balanced Apple TV version, the emphasis is on the viewing part which will help parents prepare the food for the baby easier when viewed from the TV.

From the first prototype, I changed the Baby Data content for Apple TV because if there is too much unnecessary information. My assumptions are parents will only want to see the progress of the baby in the Apple TV and not the details of what the baby has eaten since they will not be able to plan meals from the Apple TV anyways.

Final Prototype