Lingumate

Background

The Language Learning Market is experiencing significant growth, expected to reach USD 191.06 Billion by 191.06 with a CAGR of 18.3% over the forecast period, from its valuation of USD 59.60 Billion in 2021.

With an abundance of language learning apps saturating the market, it begs the question :

Do these applications genuinely empower users to embark on a journey of learning and unleash their maximum potential?

Research

The language learning app market experienced a significant surge in revenue, reaching a staggering $2.92 billion in 2021, reflecting a remarkable year-on-year growth of 65%.

The report highlights Ai and ML as key technologies fueling innovation in language learning apps, enabling personalized learning experiences, speech recognition, and language translation.

User Survey

Q : How important do you think personalization is for language learning apps? (From scale 1 - 5)

22/27 people consider it highly significant. 81.48%

Q : How do you measure your progress in learning a new language?

60% Measuring fluency (e.g. ability to have conversations)

40% Achieving specific learning goals (e.g.passing a language proficiency test)

User Interview

Q : How important do you think personalization is for language learning apps?

3/3 people consider it highly significant.

💜 Should prioritize personalization based on individual learning styles, pace, and objectives.

💜 Maintain user motivation and engagement.

Q : What are your overall thoughts on the potential of AI-powered language learning apps to revolutionize language education?

💜 Delivering effective, personalized, and engaging learning experiences.

💜 AI algorithms analyze learners, adapt content, provide tailored recommendations.

Q : How important is instant feedback and correction in language learning apps?

2/3 people consider it highly significant.

💜 “Instant feedback and correction are essential in language learning apps to help users identify and correct mistakes promptly.”

💜 “Enable users to correct mistakes promptly and progress faster.”

Learning from Insights

Limited time :

Many language learners face the obstacle of having limited time available to study and practice, which can slow down progress and make it harder to achieve their goals.

Goal to communicate :

For many language learners, the main goal is to be able to communicate effectively in the new language, whether it's for personal or professional reasons.

Desire to track progress :

Learners often want to be able to track their progress over time, whether through formal assessments or informal measures such as conversations with native speakers or keeping a language learning journal.

Ideate

Target Audience

Student : study foreign languages.

Travelers : wanting to communicate effectively in different countries.

Professionals : seeking to improve language skills for career advancement.

Affinity Map

How Might We

How might we help users track their progress and set achievable goals for language learning?

How might we provide personalized recommendations for language learning resources based on the user's skill level?

How might we integrate language learning into users' daily routines and make it more convenient for them to practice regularly?

Solution

Imagine an impact of personalized insights that drive language learners to unlocking their full potential and accelerating their language learning journey.

Idea Brainstorming

Personalized learning paths : Offer customized learning paths based on each user's learning style, skill level, and interests.

Voice recognition technology : Incorporating voice recognition technology could allow users to practice speaking and pronunciation skills in a more interactive way.

Real-time feedback : The app offers users a unique advantage by providing them with instantaneous and invaluable insights, delivered right at the moment of their actions or inputs.

Progress tracking : Providing users with detailed progress tracking could help them identify areas for improvement and stay motivated to continue learning.

Concept Refinement

User Testing

Based on the feedback obtained from the user testing phase, adjustments were implemented to the wireframe design.

To make it easier for users to track their progress, I made several modifications to the wireframe based on user testing. Specifically, I moved the topic to the top of the screen and added a progress bar to the top to indicate the completion status of each task.

I made adjustments to the plan settings to enhance its clarity and user-friendliness. Additionally, I replaced the 'DONE' button with 'NEXT' to indicate to users that it's not the end of the process.

I reorganized the layout of the languages to a horizontal format. I added a feature for daily goals to keep users motivated and on track with their language learning progress. This feature encourages users to set specific goals for themselves each day and provides them with a sense of accomplishment as they reach those goals.

Design

Color Palette & Typography

Logo Design

Final Deliverables

Key Factors to Consider

MVP 01
Personalized Study Plan
💜 The AI system creates a personalized study plan for the user based on their proficiency level, learning style, and goals.
💜 The study plan includes specific exercises and activities for the user to complete each day or week, as well as recommendations for additional resources (such as articles, videos, podcasts, etc.) to supplement their learning.
💜 The AI system adjusts the study plan as the user progresses, taking into account their performance on previous exercises and activities.

MVP 02
Progress Tracking
💜 User can see more detailed progress information on specific lesson or skill.
💜 User sees their current proficiency level for that skill or lesson (e.g. beginner, intermediate, advanced.
💜 User can navigate back to the progress tracking section to see updated progress information for all skills and lessons.

MVP 03
Real-time Feedback
💜 As the user completes each task or exercise, the AI system analyzes their responses and provides immediate feedback.
💜 Feedback may include corrections, explanations, and suggestions for improvement.videos, podcasts, etc.) to supplement their learning.
💜 Based on the user's performance, the AI system adapts the difficulty level of subsequent tasks or exercises to provide a personalized learning experience.

Evaluation

User Testing

I conducted user testing on key features, focusing on gathering feedback and insights from users. The testing process involved observing how users interacted with these features and gathering their overall feedback on usability and satisfaction.

User Feedback

“I would love more challenging features to keep me motivated.“

“I think if the study plan provides more detailed information, it would be better for users to know what they should work on.”

Final Deliverables 2

Additional Factors to Consider (Post MVP)

Post MVP 01
Scores & Leaderboards
Integrating gamification elements into language learning can transform the educational process into an interactive and enjoyable journey. By incorporating game-like features such as rewards, achievements, and leaderboards, learners are motivated to actively participate and progress in their language studies.

Post MVP 02
Enhance Study Plan by Machine Learning
Machine learning can greatly enhance personalized study plans by analyzing learner data and adapting content to individual needs. By leveraging machine learning algorithms, the app can track a learner's progress and generate customized study plans based on their specific learning goals. Machine learning can also optimize the sequencing of lessons, recommend relevant exercises and materials, and adapt the difficulty level to provide an optimal learning experience.

Post MVP 03
Insights for tracking progress in-depth
With in-depth progress tracking, users gain insights into their strengths and weaknesses, enabling tailored challenges and opportunities for growth. This approach keeps users engaged and stimulated. Additionally, in-depth progress tracking helps identify areas that require extra support. It allows users to detect patterns of struggle.

What I've learned from this project

💛 The value of conducting user research and usability testing to gather feedback and improve the app's design and functionality.

💛 The significance of understanding user needs and preferences in designing language learning apps.

💛 The need to strike a balance between aesthetics and functionality to create an engaging and visually appealing app

Limitations & Concerns

Technical Feasibility : Developing an AI-powered language learning app comes with certain technical challenges. The implementation and integration of AI algorithms and models require substantial computational resources and expertise. Ensuring seamless performance and responsiveness of the app, especially during real-time interactions and feedback, may require efficient server infrastructure and optimized algorithms.

Personalization and Data Privacy : Personalization in an AI-powered language learning app relies on collecting and analyzing user data, raising concerns about data privacy and security. App developers must prioritize privacy measures, transparent data handling practices, and obtain user consent for data usage.

Continuous Improvement : AI should be continuously updated and improved based on user feedback and evolving language trends. Regular updates, bug fixes, and adding new features and content ensure that the app remains relevant and effective for learners.