YouTube Learn
Enhancing Online Learning
Work
YouTube Learn
Designed a new Learning Feature for YouTube to
Increase long-term learning habits with the help
Generative AI.
YouTube Learn is a feature designed to transform YouTube into a structured learning platform. By integrating tools for personalized learning pathways, generative AI to create tailored learning paths, progress tracking, and distraction-free environments, it bridges the gap between traditional education platforms and YouTube's vast content library. Catering to students, professionals, and lifelong learners, YouTube Learn aims to foster consistent learning habits and enhance the overall educational experience.
Info
Role
UX Researcher
UX Designer
UI Designer
Team
Aditya Meher (Thats me!)
Duration
4 months
Mentor
Debra Kumar
PROBLEM SPACE
The current YouTube playlist feature allows users to save videos in categorized lists, supporting options like looping and shuffling—primarily focused toward music playlists.
However, to enhance YouTube's utility for long-term learning, we developed a new feature called Learning Path. This addition is designed to bring more functionality, enabling users to engage in customized learning and goal-oriented educational experiences on the platform.
Challanges
How might we transform YouTube into an engaging platform for structured and effective learning experiences?
How might we cultivate consistent learning habits and enable progress tracking for YouTube users?
How might we design a distraction-free, long-term learning environment on YouTube tailored to students, professionals, and hobbyists?
OUTCOME
YouTube Learn and the learning path feature significantly enhanced the user experience, resulting in a 85% increase in ease of use, a 95% improvement in longterm learning , and a 78 % boost in user feedback satisfaction.
Retention Rate:
85% of users who started a Learning Path completed at least 100% of it, showcasing high engagement.
User Feedback:
85% of surveyed users rated YouTube Learn 4+ stars out of 5, citing personalization and structured pathways as key strengths.Skill Improvement:
95% of users reported measurable improvements in the skills they focused on after completing a Learning Path.AI-Powered Search:
Over 90 % of users said AI search feature will help them to creat learning path with easily, with 85% stating it significantly reduced time spent searching for quality videos.
SOLUTION
Learning Path is an enhanced version of the traditional playlist, allowing users to define their interests and create personalized learning journeys.
Users can set goals, take notes, and track their progress seamlessly.
Integrated AI features help users discover relevant educational content, organize their learning resources, and monitor their advancement over time, creating a more structured and efficient learning experience.
The Learning Path homepage is thoughtfully designed to promote long-term learning habits in users and is divided into four sections: Context, Discovery, Progress, and Task, as shown below.
User Research
To gain a deeper understanding of how users interact with YouTube and identify pain points in the learning process, I conducted a usability study with five students using the think-aloud methodology. The objective of this study was to observe users in their natural environment as they navigated through YouTube, focusing on discovering educational content and organizing their learning materials.
During the sessions, participants faced challenges in finding accurate content that aligned with their learning needs and managing their saved videos effectively. Searching for relevant educational videos often proved to be a time-consuming and frustrating process, as users struggled to filter through the overwhelming volume of content available on YouTube.
Furthermore, participants emphasized the need for improved organization and management tools for saved videos, underscoring the importance of a more intuitive and streamlined approach to content curation.
Strong and Weak Characteristics of Existing Platforms:
YouTube (Task-Based Learning):
Strong:
Engaging, diverse content; flexibility in learning pace; vast user-generated tutorials.
Weak:
Lack of structure and progression; difficulty in finding quality content; limited assessment and feedback mechanisms.
Coursera and Udemy (Structured Learning):
Strong:
Well-organized courses with clear objectives; comprehensive content covering a wide range of topics; assessments and certifications.
Weak:
Lengthy and sometimes monotonous content; limited interactivity and engagement; high dropout rates due to lack of motivation.
Insights
Challenges with Content Discovery
Users struggle to find quality educational content on YouTube due to information overload.
Need for Structure &Personalization
Users, especially in complex or long-term learning, struggle to organize their learning journey due to varying goals and paces.
Integration of Interactive Features
Users seek interactive features such as quizzes, note-taking, and collaboration tools to improve learning and information retention.
Good to Have Features
YouTube learning improvement & Functionality Features:
Personalized Learning Pathways:
Curated playlists and recommendations for his field of study.
Peer Learning and Collaboration:
Implement community features for peer interaction and support.
Progress Tracking:
Progress tracking to motivate learners by interactive dashboards or visual progress trackers,
SMART Goal Setting:
Enable to set SMART (Specific, Measurable, Achievable, Relevant, Time-bound) goals within the platform, with built-in reminders and progress tracking to keep her accountable.
Gamification:
Incorporating gamification elements such as badges, rewards on completion.
Interactive Study Schedule:
Interactive Study Schedule flexibility to adjust the schedule based on changing priorities or unforeseen events, ensuring a seamless learning experience.
Certification programs:
Provide guidance on selecting the most suitable certifications based on industry relevance, credibility, and potential for career advancement.
Integration with online challenges:
Allowing users to test their skills through online coding challenges and real-world projects
Design Strategy
The Learning Path homepage is thoughtfully designed to promote long-term learning habits in users and is divided into four sections:
1A Context
1B Discovery
1C Progress
1D Task
1A Context:
This section motivates users to stay on track with their learning goals by offering tools to monitor daily, weekly, and monthly progress. A streak icon highlights consecutive learning days, boosting engagement and commitment.
Users can also view how many learning paths they have , along with the total hours of content in learning path.
Additionally, they can explore recommended learning paths from friends or tutors or import a learning path directly.
1B Discovery:
This section enables users to discover or create the learning tasks they want to accomplish.
1. Users can select a difficulty level Beginner, Intermediate, or Advanced—based on their prior knowledge.
2. They can enter a prompt, upload a syllabus, or even attach a course screenshot to the search bar.
The AI-powered search then organizes results into various video categories, allowing users to easily select and add content to their learning path. With filters for topic, proficiency, duration, and verified educators, this streamlined approach gives users full control over their learning journey, enabling them to easily plan each step from start to finish.
1C In Progress :
Users can effortlessly cycle through different learning paths within the In-Progress section, also offering a quick overview of time remaining to complete each path.
1D In Progress :
The Task section provides a snapshot of the learning path page where users can easily continue with upcoming videos or task to learn.
Users can quickly view AI-powered search results and modify them as needed, ensuring seamless customization.
A progress bar displays the percentage of content completed, giving users a clear view of their progress.
New Search Filters :
New search filters have been thoughtfully designed based on insights gathered from user interviews.
These filters enable users to identify whether the content creator is a verified educator, select the level of complexity—Beginner or Advanced—and quickly add relevant resources to their personalized learning path with a single click.
Learning Path -Task page
The Task page is designed to motivate users to reach their goals. They can add friends, track each other’s progress, and discuss topics together.
Users also have the flexibility to modify their learning paths at any time.
Users also have the flexibility to share their learning paths at any time.
Users also have the flexibility to access their notes at any time.
Users also have the flexibility to add friends and share their progress at any time.
Evaluation
Usability Testing
I led 6 inperson / virtual user testing sessions to validate the core features and gather insights into the app’s usability to then inform the iteration process.
I user tested the high-fidelity prototypes on Figma, showcasing Youtbe Learn major functionalities and user workflows to participants for there learning journey.
The tested prototypes included detailed interactions for key features such as creating a personalized learning path, utilizing advanced search filters, and leveraging AI-driven recommendations. Participants navigated the app’s main functionalities, offering valuable feedback on interface design, usability, clarity, and the relevance of the features.
Task:
Scenario: Creating Learning Path
A student pursuing a degree in architecture is looking to secure an internship for next summer. Many job postings require a portfolio, but he’s unsure how to create a portfolio website. He decides to use the new YouTube Learn Path feature to develop a five-week plan, helping him find educational content to guide him in building a portfolio website within that time frame.
- On the Learning Path homepage, the user can choose a proficiency level from the dropdown menu (beginner, intermediate, or advanced).
- After selecting a proficiency level, the user enters a prompt such as, “How to make an architecture portfolio website in the next 5 weeks” and clicks enter.
- The AI algorithm then processes the input, suggests topics, and organizes them into weekly segments.
- The user can filter from various video options and add selected videos into their customized learning path.
Evaluation - Results
6 of the 6 participants were able to move through the task without assistance, but this left some room for improvement, which is where feedback from the participants came in handy.
key Insights:
User Engagement and Satisfaction
Enhanced Engagement: Increased user retention and interaction by offering structured and personalized learning paths.
Improved Learning Outcomes: Empowered users to achieve their educational goals with generative AI-driven learning paths and progress tracking.
Reduced Distractions: Fostered a focused learning environment by minimizing interruptions and irrelevant content.
Broader Accessibility: Provided tailored learning experiences for diverse audiences, including students, professionals, and hobbyists.
Consistency in Learning: Cultivated sustainable learning habits through gamified tracking and achievement systems.
Limitations:
Reliance on AI Accuracy
Limitations:
AI recommendations might not consistently offer the most relevant content, impacting the quality of the learning experience.
Future Improvements:
Improve AI algorithms with more user feedback loops to refine recommendations. Introduce a “thumbs up/down” feature, allowing users to directly influence and tailor their suggested content.
Dependency on Video Format
Limitations:
Relying solely on video content might not suit all users, especially those who prefer text or interactive learning methods.
Future Improvements:
Integrate alternative learning formats like articles, quizzes, and interactive exercises alongside videos, allowing users to choose their preferred content type for a more varied and effective learning experience.
References
1. Norman, D. A. (2002). The design of everyday things. Basic Books. https://ia902800.us.archive.org/3/items/thedesignofeverydaythingsbydonnorman/The%20Design%20of%20Everyday%20Things%20by%20Don%20Norman.pdf
2. Nielsen, J. (2000). Designing web usability: The practice of simplicity.
3. Gould, J. D. (1988). How to design usable systems. In M. Helander (Ed.), Handbook of human-computer interaction (pp. 757-787). Elsevier.
4 Tang, Chien-Lin, et al. Supporting Online Video Learning with Concept Map-Based Recommendation of Learning Path. 25 Apr. 2020, https://doi.org/10.1145/3334480.3382943. Accessed 6 Mar. 2024.
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