Artificial intelligence (AI) is persistently penetrating our daily lives. AI is already an integral part of the eCommerce, marketing, FinTech, manufacturing, and automotive industries. It’s about time we started implementing AI into foreign language learning and education as well. For many years, we’ve tried to modernize the learning process with AI language learning. But since the advent of online learning, nothing groundbreaking has happened in the industry. Using neural network capabilities together with an AI-powered language learning will revolutionize education for students and teachers as well as the enterprise sector.
Artificial Intelligence for language learning
Artificial intelligence algorithms have the potential to advance eLearning in every field. Large corporations can use language learning solution to develop their employees’ knowledge. Individual learners can use AI language learning to study anytime, anywhere. Traditional schools can incorporate artificial intelligence language learning to diversify the opportunities of students. The advantages of implementing artificial intelligence in eLearning are astounding. Here are just some of the benefits of machine learning in education.
Adapting to student needs
In a classroom of 25 students, it’s virtually impossible for a teacher to find the right approach for everyone. But thanks to using an AI for learning a new language, the needs of each individual student can be taken into consideration. With AI integrated into the learning process, educators can collect tons of data about learners, their interests, their abilities, and so on. When analyzed, this data can pave the way for personalized education.
AI-powered language learning platforms allow learners to work at their own pace, repeating topics and emphasizing things they have trouble with, engaging them with the tasks they’re best at, appealing to their interests, and taking into account such factors as cultural background. Data also allows teachers to understand what’s going on in the minds of their students and predict their future performance.
Providing instant feedback
With artificial intelligence language learning, feedback comes quickly. When you’ve worked hard on an important test, waiting for the results can be intense. And when a week later you see the mistakes you made, you might not actually remember how or why you made them. AI language learning platform can grade tests and even evaluate essays automatically right after you’ve turned them in, pointing out errors and suggesting ways to avoid them in the future. This allows students to instantly take action to correct their mistakes and probably do better on future tests. As far as teachers are concerned, AI language learning solutions can pinpoint weaknesses in their curriculum and help them see what can be improved in their lectures or practical assignments, what questions are misleading, and which learners need additional guidance.
No fear of failing
It’s okay to make mistakes – that’s how people learn. Unfortunately, when students make mistakes, get low grades, or fail to answer questions, they often feel ashamed or even scared: “What will the teacher say?” AI in language learning won’t reprimand or criticize learners, tell them they’re not smart enough in front of the whole class or threaten them with reports to their parents or a visit to the principal. AI can evaluate learners without judging them.
A redefined role for teachers
No, AI will not make teachers lose their jobs, but it will redefine the role of teachers. Instead of being the sage on the stage, teachers will become the guide on the side, meaning that technology will cover teachers’ mundane tasks while they will become more like advisers to learners. With AI language learning doing the grading and the paperwork, teachers will have more time to coordinate the learning process and mentor students. Teachers who are more tech-savvy may also try on the role of data scientists, analyzing and using the data gained from the learning process.
Deeper involvement in the learning process
Thanks to AI used for learning a new language, learners will be able to study from any place in the world at their own pace, set their own goals, and follow a customized syllabus. Teachers won’t have to go over the same material each year thanks to a personalized approach to learning that varies from student to student. Plus, AI will help develop engaging games, quizzes, and other learning and exploratory activities that combine programs of study with students’ interests. AI for language learning development by Intellias Consolidate your education software with advanced technologies, lean design, and an emphasis on learners
AI for language learning development by Intellias
Consolidate your education software with advanced technologies, lean design, and an emphasis on learners
Applying AI to language learning
Learning a new language is difficult yet rewarding. New acquaintances, business opportunities, travel, and access to tons of information are just a few of the perks. But can you really understand the peculiarities of a language without talking to locals? Artificial intelligence thinks you can.
Chatbots have come a long way from often useless dummies to intelligent assistants that can trick you into thinking you’re actually communicating with a real person. With chatbots getting smarter, people have started using them in learning foreign languages. All you have to do is engage in a dialog with an AI bot and learn through the process of communication. AI-powered language learning chatbots provide customized answers in response to your messages and can even grade your performance or give tips on what you need to improve. And the best part? You don’t have to face the anxiety of failure that you might when you’re talking to a real person.
Artificial intelligence technologies like neural machine translation have allowed machine translation to take a giant leap forward. Along with the improved quality of translations, neural machine translation can help incorporate machine translation into foreign language learning. Machine Translation as a Bad Model is a pedagogical method whereby learners identify inconsistencies and errors in machine-translated text and correct them. This helps students understand a language and its peculiarities better and improve comprehension, sentence composition, and vocabulary in the target language.
Because people learn in different ways and at different speeds, expecting everyone to follow the same textbook and be equally successful is unreasonable. That’s why personalized textbooks make so much sense. When a language learning solution knows your progress and adapts to your needs based on your personal data, it can provide you with the learning materials you need.
Textbook customization can also be of value to teachers. If teachers could upload their educational programs into an artificial intelligence system, the system could generate textbooks customized for a specific school, course or even group of students.
Learn how Intellias developed an app for language learning that offers personalized textbooks for schools, universities, and the enterprise sector
AI language learning algorithms commonly used in EdTech
There are hundreds of algorithms uniting AI and foreign language learning that help computers get smarter. Some of them, like Decision Tree, K-Means, Naive Bayes, and dimensionality reduction algorithms can be successfully applied in education. The Decision Tree is used for – you guessed it – helping AI systems make smart, data-driven decisions. And AI should be able to classify data by itself, which is what K-Means and Naive Bayes are for. Finally, AI needs to think fast, and dimensionality reduction algorithms can help out when there’s too much data.
Natural language processing (NLP), collocation extraction, and point mutual information (PMI) are also used to help AI become a valuable tool for language learning. NLP allows machines to read and understand human language; collocation extraction can be used to retrieve information, classify documents, and solve language generation problems; and PMI can measure how much one word tells about another.
Intellias experience with AI for language learning
When it comes to implementing artificial intelligence in language acquisition, Intellias knows how to do it right. Together with Alphary, we created a set of smart Android, iOS, and an NLP learning app that help students acquire English vocabulary. These applications use the Oxford suite of Learner’s Dictionaries and an integrated AI named FeeBu (Feedback Butterfly) to mimic the behavior of a human English tutor who gives automated, intelligent feedback.
The app accesses a huge corpus of authentic English texts to provide contextualized vocabulary practice. FeeBu uses four basic criteria to evaluate learner success in language acquisition: grammar, spelling, meaning, and word choice.
Our Intellias 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 automatically evaluates writing and analyzes it for grammatical mistakes.
For fluency feedback, we implemented a server-side component that performs natural language processing (NLP) analysis of students’ answers. Corpus analysis with an n-gram model, collocation extraction, and point mutual information allowed us to extract collocations from a huge English corpus 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 application that Intellias built with Alphary proved so successful that Oxford University Press, the largest publisher of English learning materials in the world, purchased it and licensed the technology for worldwide distribution. On top of that, Intellias created another app for Oxford University Press based on the approaches used in the native app but with a unique branded interface.
Learn how Intellias developed an NLP solution to accelerate the language acquisition process by applying AI for semantic analysis and automated feedback
Years of experience in the eLearning field allowed Intellias to design and develop an ingenious backend solution for the language learning application based on the world-recognized Leitner flashcard methodology and intelligent NLP algorithms, incorporating data mining, machine learning, corpus statistics, and semantic analysis. The Intellias team parsed and redesigned a multilingual dictionary, created different types of language acquisition practices for better user engagement, and added rewards and achievements to motivate users.
Once artificial intelligence and education combine, the learning experience for students as well as teachers will reach a new level. Personalization, instant feedback, and adaptation to learner needs will help students flourish. Artificial intelligence technologies will also enhance language learning with the use of language bots, machine translation, and personalized textbooks.
This is why AI software development companies are investing in smart educational applications. If you’re interested in developing EdTech solutions powered by artificial intelligence, Intellias is here to help. Contact us for advice from our artificial intelligence language learning experts and custom software developers.