In a 5-person team, we conducted user research exploring how generative AI could be integrated into FanDuel's infrastructure to enhance user performance in fantasy sports.
In a 5-person interdisciplinary team, we worked with FanDuel to conduct user research and determine how to integrate generative AI into their infrastructure and improve the fantasy sports user experience.
Role
UX Designer
Timeline
Fall 2023
Timeline
Fall 2023
Timeline
Fall 2023
Team
3 UX Researchers
2 UX Designers
Team
3 UX Researchers
2 UX Designers
Tools
Figma
Qualtrics
Dedoose
Miro
Tools
Figma
Qualtrics
Dedoose
Miro
Tools
Figma
Qualtrics
Dedoose
Miro
OVERVIEW
FanDuel, a leader in the mobile sports betting industry with two main products—FanDuel Sportsbook and the Fantasy app—was looking to enhance its user experience by exploring the potential of generative AI. Our team, RGB-GT, was tasked with conducting in-depth user research to understand how fantasy players currently use AI to improve their experience and identify the best way to integrate this technology into FanDuel’s infrastructure. The ultimate goal was to strategically utilize AI to not only provide a more personalized experience but also to give players a unique competitive advantage, setting FanDuel apart from its competitors.
OVERVIEW
FanDuel, a leader in the mobile sports betting industry with two main products—FanDuel Sportsbook and the Fantasy app—was looking to enhance its user experience by exploring the potential of generative AI. Our team, RGB-GT, was tasked with conducting in-depth user research to understand how fantasy players currently use AI to improve their experience and identify the best way to integrate this technology into FanDuel’s infrastructure. The ultimate goal was to strategically utilize AI to not only provide a more personalized experience but also to give players a unique competitive advantage, setting FanDuel apart from its competitors.
OVERVIEW
FanDuel, a leader in the mobile sports betting industry with two main products—FanDuel Sportsbook and the Fantasy app—was looking to enhance its user experience by exploring the potential of generative AI. Our team, RGB-GT, was tasked with conducting in-depth user research to understand how fantasy players currently use AI to improve their experience and identify the best way to integrate this technology into FanDuel’s infrastructure. The ultimate goal was to strategically utilize AI to not only provide a more personalized experience but also to give players a unique competitive advantage, setting FanDuel apart from its competitors.
TL;DR
Too long to read? No problem, here is the gist.
What is the project?
An evidence-based design study on how generative AI can be leveraged to improve the experience for new players on the FanDuel Fantasy football app.
Why is a solution needed?
Based on our user research we found that novice users would usually have to do their own research on the players they choose for their roster and rely on others to create and learn how to make decisions while playing Fantasy sports. This would mean users would have to rely on other sources of information outside the application and evaluate on how these info would effect their decisions.
What is the value of this solution?
The feature we are adding was designed to aid users in the initial steps of their experience by providing verified in-app information. It also delivers quick, digestible highlights of game performance, offering actionable insights on how to improve. Finally, users have the option to share their personalized highlights on social media, allowing them to celebrate achievements and engage with friends.
My role and responsibilities
I was actively involved in user research, conducting and coding interviews to analyze insights from our target audience. Additionally, I was responsible for many aspects of the product design process, from ideating and creating concept sketches to collaborating on the design system. I also created wireframes and final prototypes to showcase the product's functionalities.
What is the project?
An evidence-based design study on how generative AI can be leveraged to improve the experience for new players on the FanDuel Fantasy football app.
Why is a solution needed?
Based on our user research we found that novice users would usually have to do their own research on the players they choose for their roster and rely on others to create and learn how to make decisions while playing Fantasy sports. This would mean users would have to rely on other sources of information outside the application and evaluate on how these info would effect their decisions.
What is the value of this solution?
The feature we are adding was designed to aid users in the initial steps of their experience by providing verified in-app information. It also delivers quick, digestible highlights of game performance, offering actionable insights on how to improve. Finally, users have the option to share their personalized highlights on social media, allowing them to celebrate achievements and engage with friends.
My role and responsibilities
I was actively involved in user research, conducting and coding interviews to analyze insights from our target audience. Additionally, I was responsible for many aspects of the product design process, from ideating and creating concept sketches to collaborating on the design system. I also created wireframes and final prototypes to showcase the product's functionalities.
What is the project?
An evidence-based design study on how generative AI can be leveraged to improve the experience for new players on the FanDuel Fantasy football app.
Why is a solution needed?
Based on our user research we found that novice users would usually have to do their own research on the players they choose for their roster and rely on others to create and learn how to make decisions while playing Fantasy sports. This would mean users would have to rely on other sources of information outside the application and evaluate on how these info would effect their decisions.
What is the value of this solution?
The feature we are adding was designed to aid users in the initial steps of their experience by providing verified in-app information. It also delivers quick, digestible highlights of game performance, offering actionable insights on how to improve. Finally, users have the option to share their personalized highlights on social media, allowing them to celebrate achievements and engage with friends.
My role and responsibilities
I was actively involved in user research, conducting and coding interviews to analyze insights from our target audience. Additionally, I was responsible for many aspects of the product design process, from ideating and creating concept sketches to collaborating on the design system. I also created wireframes and final prototypes to showcase the product's functionalities.
Problem Statement
How might we utilize generative AI to improve the user experience and performance on the FanDuel Fantasy Sports app?
Main Features
Main Features
Main Features
01
Game Highlights
The Highlight page provides a summary of a user’s most recent game. It also offers personalized, AI-driven suggestions to help users refine their strategy for future matchups and gain a competitive edge.
01
Game Highlights
The Highlight page provides a summary of a user’s most recent game. It also offers personalized, AI-driven suggestions to help users refine their strategy for future matchups and gain a competitive edge.
02
Highlights Reel
Based on the user's preference, the highlights can be shared as a video reel. Users can then share these videos on any social media platform or save them directly to their device.
02
Highlights Reel
Based on the user's preference, the highlights can be shared as a video reel. Users can then share these videos on any social media platform or save them directly to their device.
03
Highlights Report
The highlights can also be shared as a detailed report, which users can save to their device or share on any social platform.
03
Highlights Report
The highlights can also be shared as a detailed report, which users can save to their device or share on any social platform.
04
Highlights From History
This feature allows users to get a summary of highlights from their past games. Users can select any game from their history to create a custom highlight reel.
04
Highlights From History
This feature allows users to get a summary of highlights from their past games. Users can select any game from their history to create a custom highlight reel.
05
Edit Highlights
Users can edit the visual style and content of their highlight videos. They have the option to choose a style from seasonal themes or use an AI prompt to generate a custom look and feel for their video.
05
Edit Highlights
Users can edit the visual style and content of their highlight videos. They have the option to choose a style from seasonal themes or use an AI prompt to generate a custom look and feel for their video.
Process
Process
Define
Context
FanDuel, a prominent player in the fantasy sports arena, has a substantial user base of 12 million registered users. The growing adoption of AI in fantasy sports, leveraging techniques like pattern recognition and data analytics, has significantly enhanced the overall user experience. However, there are many existing issues. Users will often go to third-party sources to research, increasing their workload. There is also an absence of generative AI for drafting within existing apps and a lack of transparency on how Fantasy sports apps operate.
Integrating generative AI into FanDuel's services would streamline the user experience, setting them apart from competitors. This AI implementation can enhance operational efficiency and user engagement, acting as virtual assistants or chatbots to assist users in team lineup creation, making FanDuel more user-friendly and technologically advanced.
Define
Context
FanDuel, a prominent player in the fantasy sports arena, has a substantial user base of 12 million registered users. The growing adoption of AI in fantasy sports, leveraging techniques like pattern recognition and data analytics, has significantly enhanced the overall user experience. However, there are many existing issues. Users will often go to third-party sources to research, increasing their workload. There is also an absence of generative AI for drafting within existing apps and a lack of transparency on how Fantasy sports apps operate.
Integrating generative AI into FanDuel's services would streamline the user experience, setting them apart from competitors. This AI implementation can enhance operational efficiency and user engagement, acting as virtual assistants or chatbots to assist users in team lineup creation, making FanDuel more user-friendly and technologically advanced.
Process
Market
Define
Context
FanDuel, a prominent player in the fantasy sports arena, has a substantial user base of 12 million registered users. The growing adoption of AI in fantasy sports, leveraging techniques like pattern recognition and data analytics, has significantly enhanced the overall user experience. However, there are many existing issues. Users will often go to third-party sources to research, increasing their workload. There is also an absence of generative AI for drafting within existing apps and a lack of transparency on how Fantasy sports apps operate.
Integrating generative AI into FanDuel's services would streamline the user experience, setting them apart from competitors. This AI implementation can enhance operational efficiency and user engagement, acting as virtual assistants or chatbots to assist users in team lineup creation, making FanDuel more user-friendly and technologically advanced.
The global fantasy sports market size was estimated at USD 20.30 billion in 2022 and is expected to grow at a CAGR of 14.1% from 2023 to 2030.
The global fantasy sports market size was estimated at USD 20.30 billion in 2022 and is expected to grow at a CAGR of 14.1% from 2023 to 2030.
Despite the 2023 generative AI boom, development has been in progress for decades prior. Generative AI has been used for menial tasks such as spam detection and auto-complete for decades, but has now found itself being able to generate full text, code, art, logos, and even 3D models.
Despite the 2023 generative AI boom, development has been in progress for decades prior. Generative AI has been used for menial tasks such as spam detection and auto-complete for decades, but has now found itself being able to generate full text, code, art, logos, and even 3D models.
Who were our target users?
Fantasy Sports players
Novice Users
Professional Users
Market
Who were our target users?
Fantasy Sports players
Novice Users
Professional Users
Market
Diverge
Research Methods
01
Semi-structured Interview
We interviewed 5 current fantasy sports players.
Goals
Understand how current users use DFS applications, identify which features they value, and uncover motivations, attitudes, and behaviors.
Overview
We covered 4 main sections, each focused on different aspects of the user experience in fantasy sports, especially for app use:
Basic information on engagement with DFS
Recommendation System
Drafting methods
Perception and trust on generative AI
Key Findings
We used Dedoose to open code the transcripts. We also created a heat map to visually organize clustered parent codes using a color-coding system for enhanced accessibility. Here are a few key findings:
“Drafting a League” (103), an outlier among parent code and “Using a Recommendation system” (26)
A few strategies, such as “relying on others' suggestions”, “basing decisions on expected points and price”, are most commonly used
The “Choosing Players” step is most common (45) "Gathering Information" (38)
Diverge
Research Methods
01
Semi-structured Interview
We interviewed 5 current fantasy sports players.
Goals
Understand how current users use DFS applications, identify which features they value, and uncover motivations, attitudes, and behaviors.
Overview
We covered 4 main sections, each focused on different aspects of the user experience in fantasy sports, especially for app use:
Basic information on engagement with DFS
Recommendation System
Drafting methods
Perception and trust on generative AI
Key Findings
We used Dedoose to open code the transcripts. We also created a heat map to visually organize clustered parent codes using a color-coding system for enhanced accessibility. Here are a few key findings:
“Drafting a League” (103), an outlier among parent code and “Using a Recommendation system” (26)
A few strategies, such as “relying on others' suggestions”, “basing decisions on expected points and price”, are most commonly used
The “Choosing Players” step is most common (45) "Gathering Information" (38)
02
Survey
We conducted 2 Qualtrics surveys sent out to students across campus and through different group chats.
Fantasy Sports Survey
Goals
Understand interactions of fantasy sports users and identify valued features
Understand how Generative AI could play a role in customization of the app and the drafting process.
Overview
The survey was distributed among people who have experience playing fantasy sports. The structure of the questions were as follows:
General Information
Type of fantasy sports user play
Platform and contest preferences
Generative AI for Customization
Current customization features
Opinion on using AI for recommendations
Generative AI for Drafting
Current ways for conducting drafting research
Opinion on using AI to assist drafting
Trust of AI and factors that influence trust
Key Findings
We received 31 responses and for analysis we used Qualtric’s built-in analysis system for quantitative data and coding for open-ended questions. Here are some key findings:
Generative AI to Assist Drafting (two clusters)
Small group of individuals have no trust in AI
Majority of individuals who find AI valuable and have decent amount of trust
Generative AI for Customization
Most people are okay with sharing historical fantasy sports data with AI
People express more concerns such as “privacy”, “want to keep fantasy & life separated”, and “don’t see any benefit from sharing”
02
Survey
We conducted 2 Qualtrics surveys sent out to students across campus and through different group chats.
Fantasy Sports Survey
Goals
Understand interactions of fantasy sports users and identify valued features
Understand how Generative AI could play a role in customization of the app and the drafting process.
Overview
The survey was distributed among people who have experience playing fantasy sports. The structure of the questions were as follows:
General Information
Type of fantasy sports user play
Platform and contest preferences
Generative AI for Customization
Current customization features
Opinion on using AI for recommendations
Generative AI for Drafting
Current ways for conducting drafting research
Opinion on using AI to assist drafting
Trust of AI and factors that influence trust
Key Findings
We received 31 responses and for analysis we used Qualtric’s built-in analysis system for quantitative data and coding for open-ended questions. Here are some key findings:
Generative AI to Assist Drafting (two clusters)
Small group of individuals have no trust in AI
Majority of individuals who find AI valuable and have decent amount of trust
Generative AI for Customization
Most people are okay with sharing historical fantasy sports data with AI
People express more concerns such as “privacy”, “want to keep fantasy & life separated”, and “don’t see any benefit from sharing”
Generative AI Survey
Goals
Examine user interactions with Generative AI and their preferences
Assess reliance and trust in AI-generated information
Overview
The survey was distributed among people who have heard of or used Generative AI. The structure of the questions were as follows:
For participants who have heard of generative AI and ever used it:
Potential obstacles preventing them from using Generative AI
Potential ethical concerns they have
For Participants Who Have Used Generative AI
Purpose and frequency of use
How do they interact with Generative AI
Comfortableness, reliability and trust
Factors that influence trust
Key Findings
We received 22 responses and for analysis we used Qualtric’s built-in analysis system for quantitative data and coding for open-ended questions. Here are some key findings:
Communication Preferences
Most people prefer “command-like” and “question-like” prompts
Most people use short and concise sentences when interacting with Gen AI
Comfortableness and Trust
Most people feel comfortable interacting with Gen AI and trust the responses
But significant amount of people are neutral and negative (40%)
Participants rated “accuracy of responses” as the most important factor
Generative AI Survey
Goals
Examine user interactions with Generative AI and their preferences
Assess reliance and trust in AI-generated information
Overview
The survey was distributed among people who have heard of or used Generative AI. The structure of the questions were as follows:
For participants who have heard of generative AI and ever used it:
Potential obstacles preventing them from using Generative AI
Potential ethical concerns they have
For Participants Who Have Used Generative AI
Purpose and frequency of use
How do they interact with Generative AI
Comfortableness, reliability and trust
Factors that influence trust
Key Findings
We received 22 responses and for analysis we used Qualtric’s built-in analysis system for quantitative data and coding for open-ended questions. Here are some key findings:
Communication Preferences
Most people prefer “command-like” and “question-like” prompts
Most people use short and concise sentences when interacting with Gen AI
Comfortableness and Trust
Most people feel comfortable interacting with Gen AI and trust the responses
But significant amount of people are neutral and negative (40%)
Participants rated “accuracy of responses” as the most important factor
03
Website Breakdown
Goals
The goal is to systematically analyze and evaluate the user interface, functionality and identify areas of improvement in the process of creating and playing a Fantasy sports league. The breakdown can help to pinpoint on issues and ensure that the app aligns with the user’s expectations.
Overview
To gain firsthand experience with daily fantasy sports, our team created a contest among three members during a game night
We documented the complete user journey, from creating a contest and drafting lineups to analyzing the results in real-time
This process provided a deep understanding of the game's mechanics, allowing us to identify key pain points and inform our design strategy
Key Findings
03
Website Breakdown
Goals
The goal is to systematically analyze and evaluate the user interface, functionality and identify areas of improvement in the process of creating and playing a Fantasy sports league. The breakdown can help to pinpoint on issues and ensure that the app aligns with the user’s expectations.
Overview
To gain firsthand experience with daily fantasy sports, our team created a contest among three members during a game night
We documented the complete user journey, from creating a contest and drafting lineups to analyzing the results in real-time
This process provided a deep understanding of the game's mechanics, allowing us to identify key pain points and inform our design strategy
Key Findings
POSSIBLE DESIGN IDEAS
POSSIBLE DESIGN IDEAS
04
Task Analysis
Goals
To understand where any pain points may be withing the core process of using Fanduel.
Overview
We went step by step through the process of participating in a competition using the Fanduel app. We then wrote down each of the steps and visualized them with a flow chart diagram
There were a total of 13 steps with 5 individual total sub-steps
Within the main steps, we included the sub-process of selecting a player, which was a total of 5 steps
Key Findings
An in depth understanding of the competition participation process
Understanding where pain points may be for inexperienced players
04
Task Analysis
Goals
To understand where any pain points may be withing the core process of using Fanduel.
Overview
We went step by step through the process of participating in a competition using the Fanduel app. We then wrote down each of the steps and visualized them with a flow chart diagram
There were a total of 13 steps with 5 individual total sub-steps
Within the main steps, we included the sub-process of selecting a player, which was a total of 5 steps
Key Findings
An in depth understanding of the competition participation process
Understanding where pain points may be for inexperienced players
Design Implications
User Persona
Design
Design
Ideation
Our design implications helped guide our ideation, concept sketches, and eventually our final design prototype.
Ideation
Our design implications helped guide our ideation, concept sketches, and eventually our final design prototype.
Initial Sketches
After synthesizing our research, we brainstormed various concepts based on our initial design implications. Our goal was to ideate different ways generative AI could assist users in making decisions and improving their experience within the FanDuel DFS app.
Initial Sketches
After synthesizing our research, we brainstormed various concepts based on our initial design implications. Our goal was to ideate different ways generative AI could assist users in making decisions and improving their experience within the FanDuel DFS app.
Sketches Feedback Session
We conducted 2 feedback sessions, each with 2 users who were fantasy sports players. We walked users through each of our concept sketches and asked specific questions:
How well do these concepts align with your user needs?
What modifications or improvements would you suggest?
Are there any accessibility issues you foresee?
Which features do you find most useful or relevant?
Key Findings
Users highly value customizable options and flexibility in a given system
Users prefer when information is shown in different ways
Users prefer features that do not interfere during game time
Users enjoy when a feature contains something fun and engaging, outside of just statistics
Users preferred when UI was kept simple and intuitive
Users expressed wanting accessible visual scaling to ensure an inclusive design
We extracted specific design requirements from their suggestions to identify what to prioritize in our next iteration of creating wireframes. From their feedback, we selected our final concept.
Sketches Feedback Session
We conducted 2 feedback sessions, each with 2 users who were fantasy sports players. We walked users through each of our concept sketches and asked specific questions:
How well do these concepts align with your user needs?
What modifications or improvements would you suggest?
Are there any accessibility issues you foresee?
Which features do you find most useful or relevant?
Key Findings
Users highly value customizable options and flexibility in a given system
Users prefer when information is shown in different ways
Users prefer features that do not interfere during game time
Users enjoy when a feature contains something fun and engaging, outside of just statistics
Users preferred when UI was kept simple and intuitive
Users expressed wanting accessible visual scaling to ensure an inclusive design
We extracted specific design requirements from their suggestions to identify what to prioritize in our next iteration of creating wireframes. From their feedback, we selected our final concept.
"Highlights Reel" Design
INFORMATION ARCHITECTURE
WIREFRAMES
Main Features
Pop-up after contest for user to share
Editing a highlight
Creating a highlight reel from their competition history
WIREFRAMES
Main Features
Pop-up after contest for user to share
Editing a highlight
Creating a highlight reel from their competition history
Wireframes Feedback Session
Goals
To refine and delve into the intricacies of the final concept wireframe.
Three sessions were performed: 2 focus group sessions of 4 participants each, 1 individual interview.
Sequence
Briefing the participants about the activity and the problem statement of the project
Briefing the context of the selected concept
Walking through the wireframe and showcasing different use-case scenarios
Feedback questions and discussion
Rating of design using Likert scale
Questions
Questions were framed to understand the overall usability and functions of specific elements of our design:
What feedback can you provide on the "Highlight Reel" design?
What type of content or AI observations would you prefer in the "Highlights Reel?”
Are there any accessibility issues within this design?
Based on the current design, how likely would you use this feature?
Key Findings
Based on notes from our feedback sessions, we synthesized user feedback to identify key findings and extract actionable design implications.
Wireframes Feedback Session
Goals
To refine and delve into the intricacies of the final concept wireframe.
Three sessions were performed: 2 focus group sessions of 4 participants each, 1 individual interview.
Sequence
Briefing the participants about the activity and the problem statement of the project
Briefing the context of the selected concept
Walking through the wireframe and showcasing different use-case scenarios
Feedback questions and discussion
Rating of design using Likert scale
Questions
Questions were framed to understand the overall usability and functions of specific elements of our design:
What feedback can you provide on the "Highlight Reel" design?
What type of content or AI observations would you prefer in the "Highlights Reel?”
Are there any accessibility issues within this design?
Based on the current design, how likely would you use this feature?
Key Findings
Based on notes from our feedback sessions, we synthesized user feedback to identify key findings and extract actionable design implications.
Accessibility, customizable options, providing encouragement and feedback, and creating an infographic-like summary report and videos are the most important to users based on our findings.
Accessibility, customizable options, providing encouragement and feedback, and creating an infographic-like summary report and videos are the most important to users based on our findings.
High-Fidelity Design
DESIGN SYSTEM
We created a design system, based on FanDuel's existing UI components, typography, icons and colors, to make our wireframe more coherent to the existing application.
DESIGN SYSTEM
We created a design system, based on FanDuel's existing UI components, typography, icons and colors, to make our wireframe more coherent to the existing application.
"HIGHLIGHTS REEL" FEATURES
The Highlights page is a summary of all the highlights of the user’s most recent game in the form of cards with the appropriate graphics, videos, and stats. It also provides AI suggestions for improvement to help users strategize better for their next fantasy game.
The highlights can be shared either as a report or a video based on user preference. The user can share these on any social platform or choose to save them on their device.
"HIGHLIGHTS REEL" FEATURES
The Highlights page is a summary of all the highlights of the user’s most recent game in the form of cards with the appropriate graphics, videos, and stats. It also provides AI suggestions for improvement to help users strategize better for their next fantasy game.
The highlights can be shared either as a report or a video based on user preference. The user can share these on any social platform or choose to save them on their device.
Users can edit the visual style and the content of the highlight video. The user has the option to decide the style from the given options, which changes seasonally, and can also use an AI prompt to describe how they want the video to be generated.
This feature provides a way for the user to get a summary of highlights from their past games. The user can select games from the history tab and create their highlights compilation.
Users can edit the visual style and the content of the highlight video. The user has the option to decide the style from the given options, which changes seasonally, and can also use an AI prompt to describe how they want the video to be generated.
This feature provides a way for the user to get a summary of highlights from their past games. The user can select games from the history tab and create their highlights compilation.
Highlights Summary Page
Design Prototype
Highlights Summary Page
Evaluation
Heuristic Evaluation
We asked UX experts to evaluate our prototype based on 8 metrics each on a 5-point scale:
Visibility of System Status
Match between the system & the real world
User control and reversibility
Consistency and navigational clarity
Error prevention
Memory Recognition Ease
Flexibility and Efficiency of Use
Simplicity and information architecture
Evaluation
Heuristic Evaluation
We asked UX experts to evaluate our prototype based on 8 metrics each on a 5-point scale:
Visibility of System Status
Match between the system & the real world
User control and reversibility
Consistency and navigational clarity
Error prevention
Memory Recognition Ease
Flexibility and Efficiency of Use
Simplicity and information architecture
SCORES
User Testing
Users were asked about immediate impressions of the prototype's functions, features, and design
Users were asked to complete 2 tasks
Create a highlight and share it with your group
Analyze your most recent game and tell us how you would change your lineup
Users were asked about features they liked and disliked
Users completed 2 questionnaires to gauge their experience
SUS Questionnaire
Word Choice Questionnaire
Findings
Provide stats and rationales that back up the insight (for more competitive users)
Make tiles clickable to view more details
Focus even more on competition and less on sharing
Provide practical suggestions for the upcoming game
Redesign information architecture and improve filtering features
Modify the report generation process to be more sequential
User Testing
Users were asked about immediate impressions of the prototype's functions, features, and design
Users were asked to complete 2 tasks
Create a highlight and share it with your group
Analyze your most recent game and tell us how you would change your lineup
Users were asked about features they liked and disliked
Users completed 2 questionnaires to gauge their experience
SUS Questionnaire
Word Choice Questionnaire
Findings
Provide stats and rationales that back up the insight (for more competitive users)
Make tiles clickable to view more details
Focus even more on competition and less on sharing
Provide practical suggestions for the upcoming game
Redesign information architecture and improve filtering features
Modify the report generation process to be more sequential
Highlights Summary Page
6023 Research Methods for HCI
Georgia Institute of Technology | Fall 2023
Dr. Carrie Bruce