Project: A caffeine intake tracking app for students
Description: We found that extensive caffeine consumption has become an increasing problem in Denmark and that university students contribute to this in particular. That led us to investigate how a large daily use of caffeine affects a university student and how could we help students to become more aware of their consumption and its effects. As a result, we designed a mobile application to supply university students with an overview of their caffeine consumption on either a daily, weekly or monthly basis.

Role: Design Research, Preparing and conducting user studies (Surveys and Interviess), Preparing paper prototypes, Sketching, Final UI design, Preparing and taking part in user testing (Interviewer), Vector Illustrations, Preparing Audio-Visual presentation of the project(Vegas Pro).
Date: 2017
Type of project: University project.
Group members: Heine Volder Hansen, Georgi Nedelev, Benjamin Singer, Kasper Hedegaard, Mathias Lynge, Thomas Pedersen and Weronika Korbutt 

What is the problem? 
Caffeine is widely used as a psychoactive substance consumed from coffee, tea, and lately energy drinks, which sales have increased over the last years. When consumed in large quantities it can affect the body negatively, e.g sleeping disorder and reduced cognitive learning ability.

Problem formulation

“How can a mobile application support university students in quantifying their coffee consumption, and further inform users of the effects of caffeine by visualizing the quantified data of their consumption?”

Target Audience- The users
Research shows that young adults in the age group 20-26 are the most prone to experience side effects of extensive caffeine consumption. One of Denmark’s biggest supply chains has doubled its energy drink sales (2010 to 2013), while Denmark is told to be a country with the seventh highest coffee intake in the world. Therefore, with this project aimed to rise the awareness of the effects of caffeine consumption through various dietary sources by students studying at danish universities.

Photo by Nathan Dumlao on Unsplash

Research and Semi-Structured Interviews
Scripting the questions for our interviews, we agreed that from the ethnographic studies we should be able to determine the following
• Describe the context in which university students consume caffeine, and the reason for doing so.
• Identify which self-tracking applications they currently know/use, and understand
their opinion about those.
• Establish what expectations and wishes university students have for a caffeine
self-tracking app.
To make sure that the participants were comfortable, we conducted the interviews in environments they are familiar with. To make sure that the results are reliable, two researchers were present during each studies, one taking a role of facilitator and the other one acting as an ovserver.
We conducted the interviews based on the script of pre-written interview questions. Video recording and notes were collected so the data could be analyzed afterwards. 

Creative brainstorming
Prior to sketching ideas for the design of our app, we tested and researched the apps that the users in our semi-structured interviews mentioned as existing ones that they are using to track their caffeine intake. 
At the end of that phase, we set up minimum implementation requirements for the app’s user interface. We decided that the application should contain an entry page, an information screen, a customization page and a statistics page. 
For the process of narrowing down our design ideas, we organised a workshop.

The workshop structure:
Three following phases:
Phase 1: Presentation
Phase 2: Future Brainstorm
Phase 3: Narrow down
Before starting the workshop, each group member was asked to think about different ideas as to what could be implemented in the prototype.

Sketching- Design funnel, Nielsen’s heuristics. Lo-Fidelity and Mid-Fidelity designs
As a result of the workshop, we established key functionality and overall concepts. Before going into design phase, we researched design methods such as Human-Centered design, Design funnel and Nielsens Heuristics for interface design. After that, the sketching phase began, with two categories in mind- ideas for data representation and user interface design.
During sketching, we followed design funnel method by having each group member sketch several ideas and present them to the group. All of the sketches were discussed and the most promising ideas were chosen to be further developed.
Data visualization, Paper prototypes and Final sketch 

To evaluate our mid-fi sketches, we got in touch with the users.
This evaluation was needed to narrow down the most understandable visualization of the data input as well as the design of the buttons. When that was established, we went on to create Lo-Fi sketches. 
Afterwards, lo-fi user tests were conducted, where printed the 8 screens that we prepared earlier in Adobe Illustrator and asked the participants to perform four tasks using this paper prototypes of the app. 
The final sketch applies the feedback which was gathered from the Lo-Fi prototype evaluation.
We implemented the app in Android studio, utilizing Java. Upon the first opening, the app goes to the new user screen, where the user is asked to input their personal information. Following that, the data is saved. A diagram for the app can be seen in top right corner.

Two days of user testing- Results of the experiment
We handed the application to the users for a period of two days in which they had to quantify their caffeine intake. Their task was to try out two different tracking methods. Firstly, for a day they should log each time they consumed coffee. Secondly, once a day, in which they input the data from the whole day. Afterwards, we conducted a semi-structured interview. As a result, we found out that the app failed to display correct data in the statistic page. Also, it lacked proper indicators for elements such as the information screen.
Conclusion of the project
Our application was successful in supplying the users with a visual overview of their caffeine consumption. We did, however, not do very well in providing the users with information about the consequences of their consumption, as the page lacked proper indicators (e.g. notification system). Some of the users did end up reflecting on their caffeine consumption, while testing our application. 

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