Ruby Wu

Data Quest

Data Quest

Data Quest

Playful and interactive data science learning experience for Honda

Playful and interactive data science learning experience for Honda

Playful and interactive data science learning experience for Honda

Data Quest is a game that empowers Honda employees to learn data science knowledge from scratch with fun. I led the collaboration with game designers, data scientists, and engineers, grounding our design in solid research and a well-established design system.

Year

2024

Team

Abhishek Bora / Project Manager

Ruby Wu / UI Prototyper

Fern Zhang / Learning Experience Designer

Jackson Chen / Data Scientist

Steve Wang / Game Designer

CONTEXT

CONTEXT

CONTEXT

We recognized the need to modernize Honda's data science training approach due to its lack of engagement and effectiveness.

We recognized the need to modernize Honda's data science training approach due to its lack of engagement and effectiveness.

We recognized the need to modernize Honda's data science training approach due to its lack of engagement and effectiveness.

We recognized the need to modernize Honda's data science training approach due to its lack of engagement and effectiveness.

Faced with the challenge of underwhelming traditional training methods, I collaborated with Honda to develop a game-based learning platform. This project was initiated to address the critical need for more engaging and practical data science education, aiming to transform theoretical knowledge into interactive, practical learning experiences.

Faced with the challenge of underwhelming traditional training methods, I collaborated with Honda to develop a game-based learning platform. This project was initiated to address the critical need for more engaging and practical data science education, aiming to transform theoretical knowledge into interactive, practical learning experiences.

Faced with the challenge of underwhelming traditional training methods, I collaborated with Honda to develop a game-based learning platform. This project was initiated to address the critical need for more engaging and practical data science education, aiming to transform theoretical knowledge into interactive, practical learning experiences.

Faced with the challenge of underwhelming traditional training methods, I collaborated with Honda to develop a game-based learning platform. This project was initiated to address the critical need for more engaging and practical data science education, aiming to transform theoretical knowledge into interactive, practical learning experiences.

PROJECT GOAL

PROJECT GOAL

PROJECT GOAL

We want to enhance Honda employees' data literacy through an engaging, gamified learning environment.

We want to enhance Honda employees' data literacy through an engaging, gamified learning environment.

We want to enhance Honda employees' data literacy through an engaging, gamified learning environment.

We want to enhance Honda employees' data literacy through an engaging, gamified learning environment.

We aimed to redefine how data science was taught at Honda by creating a game that not only educated but also deeply engaged the employees. The project sought to increase both the effectiveness of training and the enthusiasm for data science across the company, leveraging gamification to make learning both fun and impactful.

We aimed to redefine how data science was taught at Honda by creating a game that not only educated but also deeply engaged the employees. The project sought to increase both the effectiveness of training and the enthusiasm for data science across the company, leveraging gamification to make learning both fun and impactful.

We aimed to redefine how data science was taught at Honda by creating a game that not only educated but also deeply engaged the employees. The project sought to increase both the effectiveness of training and the enthusiasm for data science across the company, leveraging gamification to make learning both fun and impactful.

We aimed to redefine how data science was taught at Honda by creating a game that not only educated but also deeply engaged the employees. The project sought to increase both the effectiveness of training and the enthusiasm for data science across the company, leveraging gamification to make learning both fun and impactful.

DESIGN CHALLENGE ONE

DESIGN CHALLENGE ONE

DESIGN CHALLENGE ONE

Employees found it overwhelming to navigate and select relevant datasets for analysis.

Employees found it overwhelming to navigate and select relevant datasets for analysis.

Employees found it overwhelming to navigate and select relevant datasets for analysis.

Employees found it overwhelming to navigate and select relevant datasets for analysis.

I designed an interface with instant data previews and real-time validation, reducing complexity and enabling users to confidently select and evaluate data without hesitation.

DESIGN CHALLENGE TWO

DESIGN CHALLENGE TWO

DESIGN CHALLENGE TWO

A one-size-fits-all approach failed to meet diverse learning needs and preferences.

A one-size-fits-all approach failed to meet diverse learning needs and preferences.

A one-size-fits-all approach failed to meet diverse learning needs and preferences.

A one-size-fits-all approach failed to meet diverse learning needs and preferences.

I introduced user-controlled customization features, allowing employees to set learning objectives, adjust parameters in real-time, and see the immediate impact of their choices, fostering a sense of ownership and engagement.

DESIGN CHALLENGE THREE

DESIGN CHALLENGE THREE

DESIGN CHALLENGE THREE

Without timely feedback, users struggled to connect their actions to learning outcomes.

Without timely feedback, users struggled to connect their actions to learning outcomes.

Without timely feedback, users struggled to connect their actions to learning outcomes.

Without timely feedback, users struggled to connect their actions to learning outcomes.

I incorporated instant, actionable feedback mechanisms to guide users through each step, promote continuous learning, and motivate adaptive adjustments based on their progress.