Game based
training

Client

Waymo is an autonomous driving technology company with a mission to make it safe and easy for people and things to get where they're going.

Target audience

Autonomous vehicle specialists who ride in vehicles to ensure that the autonomous system is correctly perceiving and interpreting its surroundings.

The problem: 

Autonomous vehicle specialists are required to identify and understand how the vehicle perceives hundreds of objects and symbols in its environment. Accurate detection and identification are critical to ensure safe and reliable operation. However, memorizing this large set of symbols and applying the knowledge effectively is a significant challenge for learners.

I designed and developed a self-paced instructional memory game that provides learners with ample practice in identifying and understanding perception objects. The game uses repetition, feedback, and engaging design elements to help specialists build and retain their knowledge efficiently.

My Responsibilities:

Game Design: Designed the structure, rules, and interaction flow of the game to align with the learning objectives and ensure effective knowledge retention.

Game Development: Built the game using Articulate Storyline, incorporating interactive elements and gamified features to enhance engagement.

Instructional Design: Created a cohesive instructional strategy, ensuring the game aligned with adult learning principles and provided clear, actionable feedback.

Tools

• Storyline: For game creation and interactive functionality.

• Google Suite: For collaboration, content planning, and documentation.

• SnagIt: For screen captures and editing visuals used in the game.

Key Features of the Game:

• Symbol Recognition Practice: Progressive levels of difficulty to reinforce memorization of perception objects.

• Realistic Scenarios: Simulated scenarios based on real-world use cases to contextualize learning.

• Instant Feedback: Detailed feedback for incorrect answers to promote learning through error correction.

• Progress Tracking: Learners could track their improvement over time, motivating continued practice.

Outcome:

The game successfully helped autonomous vehicle specialists improve their ability to identify and interpret perception objects. This contributed to reduced errors during vehicle monitoring, enhancing both individual performance and overall vehicle safety.

Client

Waymo is an autonomous driving technology company with a mission to make it safe and easy for people and things to get where they're going.

Target audience

Autonomous vehicle specialists tasked with quickly commenting on perception issues in operational data.

The problem: 

Inconsistent commenting practices across regions created challenges in analyzing data. While specialists were provided with a list of abbreviations to streamline note-taking, they lacked:

• Practice Opportunities: No structured exercises to reinforce the use of abbreviations.

• Feedback Mechanisms: No feedback loops to refine and standardize their commenting style.

These gaps led to sporadic and inconsistent usage of abbreviations, reducing the efficiency and reliability of data analysis.

A self-paced instructional game designed to:

• Provide learners with extensive practice in shortening comments by identifying key terms and recalling the appropriate abbreviations.

• Create an engaging and interactive way to standardize and reinforce commenting practices across regions.

My responsibilities:

• Game Design: Developed the concept and mechanics for the instructional game.

• Game Development: Built the interactive experience, ensuring usability and alignment with learning objectives.

• Instructional Design: Crafted the content and flow to maximize engagement and learning outcomes.

Tools Used:

• Storyline: For game development and interactive content creation.

• Google Suite: For collaboration and content drafting.

• SnagIt: For capturing and editing visuals to enhance the learner experience.

Key Features:

• Interactive Gameplay: Learners raced virtual cars, gaining speed by accurately abbreviating comments.

• Real-Time Feedback: Instant notifications for correct or incorrect inputs, promoting continuous improvement.

• Targeted Practice: Scenarios drawn from real-world scenarios ensured relevance to learners' daily tasks.

Outcome:

• Improved Consistency: Standardized abbreviation usage across regions, enhancing data reliability.

• Increased Engagement: Learners reported higher satisfaction with the training format compared to traditional methods.