Artificial intelligence and language studying blend seamlessly when it comes to online education. Already a key component of sectors such as eCommerce, FinTech, and marketing, AI is quickly becoming standard practice in education.
Online education has become a revolution en masse. With the accelerated introduction of AI to foreign language learning, we are now experiencing a similar paradigm shift. AI-powered language studying combined with the use of neural network capabilities is resulting in a new era of education for students and teachers alike.
But how exactly can you use AI to improve learning outcomes for your students?
Navigate through the realms of AI and language learning, exploring real-world applications and drawing from our expertise at Intellias. Major eLearning services providers win reputable customers like Visa, PepsiCo, and Deloitte with platforms implemented by Intellias. Our AI algorithms have helped educational startups get recognized by publishers at Oxford, Cambridge, and Macmillan.
Learn from our experience, cases, and success stories:
- AI applications and algorithms in language learning
- Practical usage of AI in language learning apps
- Chatbots for studying
- Tips for using AI based on the Intellias solutions
Challenges of language learning
Mastering a new language can be difficult. Especially when traditional methods of teaching have limitations that make it harder for students to succeed. Textbooks, videos, and audio recordings include useful content but lack personalization. Occasionally, this may result in students progressing to the next level before they thoroughly understand the material.
Working with tutors also has disadvantages. Although a teacher or other professional may tailor the curriculum to each student, language learners (both adults and children) often experience anxiety when speaking a new language. In schools, speaking in front of classmates increases this anxiety and can hinder the process for students who may otherwise be successful.
AI technology can solve these issues. Language learning apps and online programs can be used in privacy and at a pace that suits each student. However, many apps and programs apply a one-size-fits-all approach that doesn’t customize the content, goals, or schedule to each learner.
How is AI applied to language learning?
AI-powered language apps are more convenient, personalized, and effective. Often integrated into eLearning courses, apps give learners remote access to content and can play an active role in the process.
Just as the rise of online education revolutionized the language learning process, developments in AI technology promise a new turning point. Studying a language with AI is becoming increasingly common, as AI enables various useful features in apps and programs.
Language bots
Many believe that to fully understand the peculiarities of a language, you must engage with native speakers. However, AI models replicate real speech and conversations with rapidly increasing accuracy. A language learning chatbot can respond to messages with personalized, relevant information. Language learners can use a chatbot to practice conversations without the anxiety they may feel when talking to a person.
Machine translation
AI technologies such as neural machine translation improve the quality of translations and help with foreign languages. One method known as machine translation as a bad model helps students find and fix mistakes in the machine-translated text. Ultimately, this allows students to learn more about the language and improve comprehension, writing, and vocabulary.
Personalized textbooks
People learn in different ways and at different speeds, so it’s unreasonable to expect everyone to follow the same textbook and be equally successful. Personalized textbooks adapt to learners’ needs based on individual progress. Textbook customization is of great value to teachers. Teachers can upload content into an AI system, which can then generate textbooks tailored to a specific school, course, or group of students.
Pay attention to these AI language models
The wide range of AI language models can be confusing, and we’re here to discuss the most impactful ones in the learning landscape.
GPT-3
Claimed to be the largest AI language model ever trained by 2020, GPT-3 by OpenAI is backed by nearly 175 billion parameters. The application is a rockstar in helping students as it creates a human-like quality of text and engages with users like a native language speaker.
By integrating GPT-3 into applications and chatbots, one can create interactive and personalized learning experiences. Adaptive exercises, quizzes, and conversational simulations — all wrapped in a language learning process with the help of GPT-3.
The tool can simulate conversation, allowing language learners to practice dialogues and responses. Such a practice helps improve oral communication skills and enhances the ability to understand and respond in real-life scenarios.
BLOOM
BLOOM (BigScience Large Open-science Open-access Multilingual Language Model) is the largest open-source AI model and one of the newest on our list. With GPT-3 pioneering the industry and establishing a new path for AI developers, BLOOM was designed to pick up the slack. The tool is multilingual, operating with 46 natural languages and 13 programming languages.
The BLOOM model is designed by over 1000 researchers from more than 70 countries. It has 176 billion parameters and is both downloadable and accessible on the Hugging Face website. Learners can perform different tasks with the tool, picking from its selection of languages.
The learning possibilities are pretty similar to those offered by GPT-3. By interacting with BLOOM, language learners can also improve their language structure. Users can input sentences or phrases and get corrected versions back together with feedback on grammar and syntax.
The tool can provide information about cultural nuances, idioms, and expressions in the target language. Understanding these aspects is crucial for effective communication and integration into a language community.
LaMDA
LaMDA, which stands for Language Model for Dialogue Applications, was introduced by Google. LaMDA is designed to engage in free-flowing, open-ended conversations on a wide range of topics. It is intended to make conversations with AI models more natural and dynamic. Google claims LaMDA stands out from other AI models as it was trained on dialogue.
While LaMDA’s primary focus is on improving conversational abilities, its applications in language learning could involve creating interactive and engaging dialogue scenarios for learners. It might help users practice conversational skills, understand contextual nuances, and receive feedback on language usage.
MT-NLG
MT-NLG (Machine Translation Natural Language Generation) is associated with machine translation and natural language generation tasks. In language learning, machine translation models like MT-NLG can help learners understand and translate text between different languages. Such integration of AI in language teaching can be beneficial for learners who want to study materials in a language they are not fully proficient in.
What are the benefits of AI in language learning?
Increasingly, the benefits of machine learning in education are becoming clearer, and AI in language learning is no exception. AI algorithms have the potential to advance eLearning in every field. Companies can use such solutions to train employees. Individual learners can use AI in language learning to study anytime, anywhere. Schools and colleges can employ it to increase students’ opportunities. More importantly, AI has already proven its significance in linguistics. Here are just some of the benefits:
Adapting to student needs
A key benefit of AI is the personalization of the learning experience. When teaching a class full of students, it’s almost impossible for teachers to find an approach that suits all. When using AI for learning a new language, the needs of each individual student can be fulfilled. Educators can collect useful data about learners, their abilities, and learning styles. When analyzed correctly, this data can predict future performance and pave the way for personalized education.
AI-powered language learning platforms allow users to work at their own pace. AI can repeat topics, engage learners with tasks they’re best at, and consider factors like cultural background.
Providing instant feedback
With traditional teaching methods, feedback is often slow to arrive. Teachers read and grade many students’ work and can take a while to deliver results. With AI for languages, feedback is almost instantaneous. AI-based platforms grade tests and evaluate essays automatically after submission, pointing out errors and how to fix them. As a result, students can instantly take action to correct their mistakes and avoid them in the future.
AI language learning solutions also help teachers pinpoint weaknesses in curriculum. They can identify misleading questions, show how they can be improved, and identify who needs additional guidance
No fear of failing
Making mistakes is a natural part of education. Unfortunately, the fear of making mistakes can negatively affect the very process. Students who feel ashamed of mistakes, knowledge gaps, or low grades can disengage with studying. AI in language learning doesn’t reprimand learners, embarrass them in front of classmates, or threaten them with punishment. AI simply evaluates learners without judging their linguistic talent.
A redefined role for teachers
Not even the most sophisticated language learning bot can entirely replace human teachers. However, AI can redefine teachers’ roles. AI algorithms can carry out grading, paperwork, and other mundane administrative tasks quickly and efficiently, allowing teachers more time to coordinate the processes and mentor students. Tech-savvy teachers may also analyze data collected by algorithms.
Deeper involvement in the learning process
Thanks to AI for learning languages, students can study anywhere at their own pace, set their own goals, and follow a customized, personalized syllabus. AI also helps develop engaging games, quizzes, and other activities that tailor lessons to students’ interests.
Machine learning (ML) is a branch of AI that allows systems to become more effective at performing tasks and making decisions over time. Deep learning is a type of machine learning that uses algorithms designed to replicate the human brain. Each algorithm learns from a vast dataset. Dimensionality reduction algorithms make these datasets more manageable.
Hundreds of dimensionality reduction algorithms exist for mastering foreign languages. For example, the Decision Tree algorithm helps AI systems make smart, data-driven decisions. The K-Means and Naïve Bayes algorithms help AI classify data.
Natural language processing (NLP), Collocation Extraction, and Point Mutual Information (PMI) are three of the main algorithms used for language learning. NLP allows machines to read and understand human language. Collocation extraction is used to retrieve information, classify documents, and solve language generation problems, while PMI measures the probability of two words occurring together.
Intellias experience with AI for language learning
In collaboration with Alphary, Intellias engineered an AI language learning solution. Years of experience in the eLearning field allowed our team to develop an ingenious backend solution for the Alphary language learning application. This solution is based on the globally recognized Leitner flashcard methodology and intelligent NLP algorithms. It incorporates data mining, machine learning, corpus statistics, and semantic analysis. By parsing and redesigning a multilingual dictionary, we created different types of language acquisition practices for better user engagement while adding rewards and achievements to motivate users.
Resulting in a smart NLP learning app for Android and iOS that uses AI in English teaching to help students learn more effectively. Each version of the Alphary app uses the Oxford suite of Learners’ Dictionaries and an integrated AI named FeeBu (Feedback Butterfly) that mimics the behavior of an English tutor, giving automated, intelligent feedback.
Accessing a huge collection of English texts, the FeeBu app provides contextualized vocabulary practice methods. FeeBu uses four basic criteria — grammar, spelling, meaning, and word choice — to evaluate success in language mastery.
Our team implemented a component that automatically generates gap exercises and answer options when given a headword and semantic context. We also created a system that evaluates and analyzes writing for grammatical mistakes.
In addition, we implemented a server-side component that performs NLP analysis of students’ answers. Data analysis with an n-gram model, collocation extraction, and PMI enabled us to extract collocations from a huge collection of English text to provide reliable feedback on fluency. Intellias worked on semantic word comparison based on the word space model (or distributional semantics) and semantic fingerprints.
The resulting app proved so successful that Oxford University Press, the largest publisher of English educational materials in the world, purchased it and licensed the technology for worldwide distribution. Intellias also created another version of the app with a unique branded interface for Oxford University Press.
How do different language learning apps use AI?
Each language learning app has its own model, and many incorporate AI into their processes.
Phase6
German company Phase6 offers a leading language learning app used by schools, universities, and enterprises. While Phase6 was initially only available as a desktop solution, the company had to adapt to the growing demand for mobile language learning experiences. Intellias helped Phase6 develop a scalable backend and a new cloud-based platform with mobile access. Using AI algorithms, the app provides a smart vocabulary trainer and personalized progress reports.
Duolingo
Duolingo is the world’s most popular language learning app, but how does Duolingo use AI? Duolingo has chatbots fluent in 38 languages, and each user’s AI chatbot employs machine learning to recognize the user’s voice and speech/text patterns. This enables the application to automatically create reading, writing, and speaking tests for users and allows Duolingo to grade and categorize them based on proficiency.
Chatbots and language learning
Employing chatbots in education is particularly beneficial to students, as chatbots provide personalized content on various topics. For example, Intellias developed a conversational virtual teaching assistant to improve sales representatives’ product knowledge. A smart chatbot can be just as effective as an AI language tutor.
For learning a language with AI, chatbots are indispensable. Prime examples of deep learning, they become increasingly familiar with users’ speech and text patterns over time. By replicating aspects of a human tutor’s role, such as by holding interactive conversations, a chatbot offers a level of personalization that other teaching methods lack.
Tips for using AI in language learning solutions
Artificial intelligence and language learning form a powerful duo. Using AI in language learning solutions can be highly effective if approached strategically.
Personalization
Leverage AI to provide personalized learning experiences based on individual strengths, weaknesses, and learning styles. Use adaptive learning algorithms to tailor content, exercises, and challenges to each learner’s proficiency level. Implement AI systems that offer instant feedback on pronunciation, grammar, and vocabulary. Enable learners to learn from their mistakes and make corrections in real-time.
Intellias experience: We’ve developed an app for language learning that offers personalized vocabularies for schools, universities, and the enterprise sector
Interactive conversations
Integrate AI-powered chatbots or virtual language tutors to simulate real-life conversations. Provide opportunities for learners to practice speaking and listening in a conversational context.
Intellias experience: We’ve built a conversational virtual teaching chatbot that helps sales reps strengthen their proficiency with advanced product knowledge
Natural Language Processing (NLP)
Utilize NLP algorithms to analyze and understand the context of sentences. Enable learners to engage in contextualized language exercises and simulations.
Intellias experience: We’ve developed an NLP solution for Alphary to accelerate the language acquisition process by applying AI for semantic analysis and automated feedback.
Gamification
Incorporate gamification elements using AI to make language learning more engaging and enjoyable. Use language and artificial intelligence to adapt game difficulty based on the learner’s progress, maintaining a balance between challenge and skill.
Intellias experience: We’ve built an intelligent eLearning software platform that delivers comprehensive career training to millions of employees worldwide with gamification badges and ratings.
Data privacy
Using data-driven insights to continually improve and tailor the language learning experience, make sure that user data is securely protected. Comply with data privacy requirements and standards.
Intellias experience: We’ve developed eLearning GDPR security protocols for an education platform to comply with the privacy policy of users’ personal data.
Continuous learning paths
Develop adaptive learning paths that evolve based on learners’ achievements and challenges. Use AI to suggest next steps, ensuring a continuous and progressive learning journey. Implement AI algorithms to recommend relevant learning materials based on the learner’s progress, interests, and goals. Curate content that aligns with individual learning objectives.
Intellias experience: We’ve helped our client customize their employee training management systems for enterprises and deliver immersive corporate learning experiences.
To sum up
Implementing AI in education enhances the learning experience for all. By transforming the way users learn and teachers educate, AI plays a significant role in accelerating language learning. Students will flourish with personalized content, instant feedback, and adaptation to individual needs. Meanwhile, the teacher’s role is made easier with the help of language bots, machine translation, and customized textbooks.
However, using AI tools successfully involves more than simply asking students to download and use an app. Human input from experts is essential to develop and implement the most effective solutions. An AI software development company can work with you to design a smart educational app tailored to your organization’s specific needs. Consult with an experienced company and develop educational tools that drive your business, school, or online learning programs into the future.