In class, we were assigned to design a digital solution centered around music to create more meaningful experiences for a selected marginal demographic and enhance their well-being. We focused on international women working in IT—where men dominate the workforce.

Mumu

Team
Sharon + 4 Group Members

Role
UX Designer

Skills
Desk Research | User Interview | Affinity Diagram | Persona | Wireframe | Prototyping | Usability Testing

Timeline
April - May 2024

Design Process

Desk Research

User Interview

Define

Ideation

Desk Research

We began by identifying a marginalized demographic to focus on, pitching our ideas, and ultimately selecting international women working in IT. We then conducted research to understand their experiences and determine how we could enhance their well-being. We gained a deeper understanding of their experiences and explored ways to enhance their well-being, leading us to valuable insights worth further investigation.

Despite proficient English skills, many international individuals feel their language abilities fall short in informal settings, significantly affecting their confidence. (Westcott, & Vazquez Maggio, 2015)

Power imbalances in the workplace make it more challenging for women, causing stress and lower job performance. (Piotrkowski, 1998)

Women struggle to balance career growth with domestic responsibilities, even without children (Martin & Barnard, 2013)

User Interview

We started with a brainstorming session to generate key ideas and potential questions relevant to our demographic. Our main goal is to understand their work environments and experiences of marginalization as international women in male-dominated fields. Additionally, we included questions about music to explore their usage and the role it plays in their lives.

To recruit participants, we posted in relevant Facebook groups targeting international female office workers in the Australian IT sector. Each group member conducted one interview, resulting in a total of five participants for our study.

Interview Questions

Data from Interviews

Define

Our personas were developed based on patterns observed in the interview data, representing the diverse types of international female professionals and their unique challenges in the IT department.

During our workshop activity, we utilized card sorting and identified three main insights through the affinity diagram:

1.    Language and Communication Barriers for International Workers

Non-native speakers find it challenging to communicate and present themselves professionally, which might limit their possibilities for advancement in their careers.

2.    Gender Inequality in Male-Dominated Fields

Women encounter significant difficulties in achieving fair treatment regarding salaries and leadership opportunities.

3.    Work-Life Balance for Working Women

Working women struggle to balance career and family responsibilities which negatively affects their well-being and sense of fulfilment.

How Might We…

Empower international women to present themselves confidently, promote a more gender-equal workplace, and support a balanced work-life experience?

Ideation

The app empowers international female professionals through personalized support, confidence-building, and networking opportunities. By connecting mentors and mentees based on shared career interests, musical preferences, and similar backgrounds, the app helps create a strong bond that makes it easier for them to relate to one another. This similarity creates supportive relationships, facilitating knowledge sharing and guidance, which provide valuable resources to help international female professionals navigate the IT industry and address challenges in male-dominated environments.

Here are the User Journey and System Blueprint illustrating how users interact with our solution and how the system supports each step of their experience.

User Journey

System Blueprint

Core Features

Preference Selection

Integration with Music Apps

Music Event Discovery

In-App Messaging

Personalized Suggestions

The app uses an algorithm to generate personalized mentor or mentee suggestions by considering factors such as industry experience, career goals, shared interests, and music preferences. This helps increase the chances of building meaningful and supportive mentorship connections.

Prototype