Meal Management and Cooking Mobile App

01

Define

02

Research

Cultural Probe

Our target participants for the research are college students as they represent the population of novice cooks. Since college students do not have a regular cooking schedule, our team determined that it would be appropriate to use cultural probe as the research method. Cultural probe allowed us to understand the participants' context without being on the site.

To comply with safety precautions of COVID-19, our team decided to use virtual diaries that allowed users to submit their thoughts and cooking experience after each cooking session along with photos of their cooking process. After collecting data of cultural Probe from our participants, we conducted follow-up in-depth interviews with our participants.

Data collection and analysis

Affinity Diagram

After collecting the data from our participants, we conducted an affinity diagramming session to discover common patterns that our participants experienced during their cooking sessions.

Work Models

We created work models from the data, categories, and themes we gathered and analyzed from affinity diagrams.

Sequence Model

We created a sequence model to identify at which stage of the cooking process did the participants experience frustrations.

Artifact Model

We also built a artifact model to understand how the participants interact with physical artifact in the kitchen.

Key Findings

Physical cooking space: This influenced how we designed our application because users might not have adequate space to put their phone on the kitchen dashboard.

Poor ingredient management: Participants did not plan ahead what they wanted to cook and got caught up when they realized they did not have enough ingredients to cook the food intended. Sometimes, they overbought ingredients and ended up throwing the leftovers to the trashcan, leading to food waste.

Motivations or goals of user: Participants wished to cook foods easily and in big bulk, and cook foods that represented their culture or country.

03

Ideation

Story Board

We started by storyboarding a hypothetical use case of the application.

Sketches

Idea One

The application will prompt the user to select food they want to cook for the week, and the food that the user choose will be shown at the main page (Figure 3A). After the user select the foods for the week, the ingredients required will be automatically added to the cart. In the cart (Figure 3B), the user can then review the ingredients and purchase them directly through third party vendors like Walmart. The home screen will also allow the user to explore the foods ingredients (Figure 3C).

Idea Two

Users can add these recipes to a customized list to create a meal plan (Figure 3D). On the food details screen (Figure 3E), the user can add the ingredients they want to the shopping list, and the amount will be based on serving size the user selected. On the shopping list (Figure 3F), it serves as a checking list that ensures the user would remember to purchase the ingredients they need for the week, at the right amount.

Idea Three

A stepwise recipe screen (Figure 3J) to guide the users on how to cook the specific dish. We found this important because a lot of our participants from our cultural probe tended to forget certain steps or ingredients. To solve this problem, we made the steps and ingredients as checking list, so the user can check the steps off as they go. In addition to that, we also thought of incorporating a video on the top of the screen.

Lo-fi Prototype

After the preliminary sketches we built on the ideation phase, we decided to build the low fidelity prototype of the ideas that we had on Figma.

04

Design

Hi-fi Prototype

05

Testing & Final Design

Hueristic Evaluation

We decided to use hueristic evaluation to evaluate the usability our design. This is because users would be mainly on the move or will be multitasking while using the app. Hence, we find it more appropriate to not use user-based testing.

Below shows a sample evaluation file.

Cognitive Walkthrough

Since user-based testing was not performed, we used cognitive walkthrough to evaluate our design as it allows us to be in the shoes of the user. We first define a few common tasks and each action associated with the task and create success or failure story based on our understanding of the persona of our users.

Below shows a sample test file.

Final Prototype Changes