The impact of AI on language learning

Charlotte Guest
People sat in a office, one with a VR headset on smiling and gesturing with the other two watching

Recently, Artificial Intelligence (AI) has shown itself to be a useful and breakthrough tool for many things, including language learning. Educators, learners and businesses are constantly seeking effective methods to impart language skills and AI-powered solutions have proved to be invaluable assets in this regard.

The impact of AI on language learning is multifaceted, presenting opportunities as well as challenges for educators, learners and corporate entities. According to a , many institutions say that AI will be instrumental to improving their competitiveness, funding, and innovation.

It is a widely discussed topic nowadays. While it has its advantages, there are also some drawbacks to consider.

The impact of AI on language learning
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Pros

Personalized learning

AI-powered language learning platforms analyze user's strengths, weaknesses, learning pace, and preferences to offer a personalized learning path. This approach enhances engagement and optimizes learning outcomes and goals.

Accessible

These types of applications and programs enable language learners to access lessons, exercises, and tutoring from anywhere, at any time, breaking down barriers and offering flexibility to learners worldwide. It can aid and support students with additional needs, making learning a lot less of an obstacle. For example, condensing/summarising content or tasks in an understandable way or suggesting word alternatives, just to name a few.

Enhanced and immediate feedback

It can provide learners with instantaneous feedback on their pronunciation, grammar, and vocabulary usage. This feedback allows learners to identify their mistakes and rectify them promptly, accelerating the learning process. AI can use advanced voice recognition technology to detect the learner's pronunciation and accent to provide accurate feedback.

With real-time analysis, algorithms can identify errors and suggest corrections right away and feedback is personalized. Based on the level of proficiency, algorithms can provide suggestions that are easy to understand and implement. This means more time to do other things, without worrying about providing or waiting for feedback.

Augmented teaching

AI tools are used to supplement traditional teaching methods. They help teachers create dynamic lesson plans, track student progress and identify areas that require additional attention, enhancing overall teaching effectiveness. This makes teaching more effective and enjoyable for both teachers and students. Plus, it takes some of the pressure off teachers by lightening their workload.

Cons

Lack of human interaction

AI has a significant limitation in language learning as it lacks the ability to provide authentic human interaction. Language acquisition is a complex process that involves cultural nuances and subtle communication cues that AI may not be able to fully comprehend. As a result, the immersive experience may be limited.

We have not yet reached a level where AI is proficient in natural spoken conversation, so its ability to assist in certain language contexts is currently limited. It will no doubt develop over time, but currently, it's not at a developed enough level. There are upcoming experimental conversational tools like , developed by Google, which are great examples of AI-powered conversation simulators.

Plagiarism and overreliance

Excessive reliance on AI-based tools might hinder the development of self-reliance and critical thinking skills in learners. Relying solely on technology and the ability to adapt to diverse real-world linguistic scenarios.Teachers are also more likely to face the challenge of students submitting AI-generated assignments.

So tools and systems will have to be implemented to check and identify any unoriginal AI-generated content. But this will be a constant process; as AI evolves and improves, so will plagiarism systems; it will likely be a constant race to keep up.Commonly used like are now incorporating checks for AI-generated content; the company reported that reviewed had been flagged as having its majority content AI-generated.

Unequal access/resources

There is a concern that not all learners may have equal access to these tools due to technological disparities, which could create a learning divide. While some schools and institutions may have the resources to invest in advanced AI systems and software, others may lack the necessary infrastructure or funding to provide their students with the same level of access.

This could mean that students in less privileged communities or schools may be at a disadvantage, missing out on the benefits of AI-powered learning tools and falling behind their peers who have access to them. Technology typically becomes cheaper over time, due to things like improved manufacturing processes, wider circulation and broader competition but this still may mean less privileged institutions could be left behind, using older or previous-generation tech which may not be as easy to use and learn from.

Privacy and ethics

AI-powered language learning platforms collect a large amount of user data. However, many users are concerned about data privacy, security breaches, and of their personal information. As AI is implemented more heavily into platforms, it will require more data to function effectively. Therefore, advanced security systems must be implemented and kept up to date to ensure that user data is securely protected from potential data breaches.

As it's integrated more into people's lives and work, countries have begun Implementing AI-related laws to ensure the safe and ethical use of AI in daily life. Similarly, as AI develops, laws will need to constantly develop to keep up to date with technological advancements.

What about the future?

The field of language learning has a promising future with the advancement of AI. Below are some potential predictions for the not-so-far-away future:

Advancements in natural language processing (NLP)

will likely continue to advance, allowing AI systems to better understand, interpret, and generate human language. Helping it to understand the subtleties of human emotion. This will result in more advanced language learning applications with contextual understanding and nuanced feedback.

Enhanced multilingual capabilities

As technology advances, AI-driven language learning platforms are becoming increasingly popular. These platforms are now being designed to offer greater support for a wide range of languages, catering to the diverse linguistic needs of individuals worldwide. This will enable more people to access quality language education, regardless of their location or background.

With the help of these platforms, language learners could benefit from personalized and immersive learning experiences that are tailored to their unique needs and preferences.

Greater integration of Virtual Reality (VR) and Augmented Reality (AR)

VR and AR with AI will revolutionize the way we learn languages. This cutting-edge technology will create highly immersive environments that simulate real-life scenarios, allowing learners to practice their language skills in a safe and controlled environment. Mondly by ɫèAV is a great example of using this kind of technology in language learning with their and apps.

One example is that students could use virtual reality to travel to a foreign country and communicate with native speakers in real time. Easily ordering food from local restaurants or navigating through the city, all within the virtual reality platform. This type of experiential learning could significantly enhance cultural understanding, improve communication skills, and boost language proficiency, all in the comfort of home, school, or even the workplace.

With the increasing affordability and accessibility of such technologies, it is expected that such learning experiences will become more common. There are already VR with AI-controlled characters to produce more realistic and expanded responses to conversations, rather than responses being limited by a select few pre-programmed choices and getting the same few responses. This could also expand to language learning games/simulations.

The impact of AI on language learning is unquestionably transformative. It offers personalized, accessible, and efficient learning experiences. However, there are challenges such as the lack of human interaction and data privacy concerns. Therefore, we need to maintain a balanced approach while leveraging AI for language education.

As technology evolves, it's crucial to harness its potential while preserving the essence of authentic language acquisition and cultural understanding. The future promises exciting advancements that will further revolutionize language learning through AI integration.

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    Myth #1: You will learn more quickly

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    Myth #2: It replaces learning in the classroom

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    Myth #3: It can’t be incorporated into classroom learning

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    Myth #4:You can't learn in the workplace

    Online language learning is ideally suited to the workplace and we must create the need to use the language and opportunities to practise it. A job offers one of the most effective learning environments: where communication is key and you’re frequently exposed to specialized vocabulary. Online language learning tools can flexibly support your busy schedule.

    Myth #5: Online language learning is impersonal and isolating

    A common misconception is that online language learning is a solitary journey, lacking the personal connection and support found in traditional classrooms. In reality, today’s digital platforms are designed to foster community and real interaction. With features like live virtual classrooms, discussion forums and instant feedback, learners can connect with peers and educators around the world, building skills together.

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    Is game-based learning technology a waste of time?

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    We feel that game-based learning (GBL) is a waste of time… if not properly understood. Even then, one could argue that "wasting time" is a vital part of learning and perhaps we need to stop insisting that every second counts.

    Game-based learning vs. Gamification: Understanding the difference

    Let’s begin by first addressing the term "game-based learning" and how it compares to its doppelgänger, gamification. Gamification is the application of game mechanics and dynamics to non-game contexts to solve problems, engage users and promote desired behaviours. For example, rewarding acheivements with points, awards or badges for achievement, levelling up, using avatars, quests and collaboration are all gamification features, which elevate games above the mundane activities of normal life.

    The principles of gamification have been applied to the retail and services sectors for years: think of airlines' frequent flyers programs, pubs and bars running "happy hours" promotions, WeightWatchers' points-counting, Foursquare's badges for visiting new places. There are hundreds of examples of where game dynamics have been introduced into non-game contexts to influence behaviour and bring about a desired result.

    Game-based learning in action: More than just play

    Gamification does not refer to the straightforward use of games (whether digital or otherwise) as part of a teaching or learning interaction. A teacher using the board game Monopoly in the classroom to demonstrate the idea of rent is not gamifying the learning environment; they are involving learners in game-based learning. GBL refers to the use of games as tools: as devices for opening discussion, presenting concepts or promoting learner engagement within clearly defined learning objectives, in other words, learning through playing games. Gamification is the appropriation of those principles, mechanics and dynamics that make games work in order to promote engagement or engender a desired outcome.

    Teachers have long introduced games into the learning environment – such as Kim’s Game, Pelmanism and Guess Who? – and the uptake of GBL with digital games is particularly well demonstrated by the work being done by the Institute of Play, and the growing popularity of the likes of Minecraft and SimCity in schools. In terms of our immediate ELT context, pretty much any video game can be repurposed for language learning, in the same way a text, song or website can be. Take, for example, the indie game . Although there is no actual spoken language in the game, the platform puzzle format lends itself perfectly to practising language around predictions or conditionals ("If I pull that lever, the door will open"), recounting events ("I was chased by a giant spider!"), strategising and so on. In this post, we will be referring to existing digital games that have been appropriated into a learning context, as opposed to games that have been designed with a specific educational use in mind.

    Sharma and Barrett’s definition of blended learning provides a useful context for approaching the use of digital games in such modalities, notably the combination of “a face-to-face classroom component with an appropriate use of technology”. We’re making no assumptions about whether the games are being accessed in the classroom, on mobile or online at home. The blend isn’t defined by where a learner is, but by how their use of technology supports and enhances their contact with the teacher.

    The notion of appropriateness in Sharma and Barrett’s definition is critical as, in the case of a GBL project, it assumes a teacher has a familiarity with both the tech and content accessibility of a selected game. Acquiring that level of familiarity with a game requires a certain amount of time engaging with it to determine its fit for the needs of the learners, an activity which might easily be considered off task when compared to the other demands being made on an educator’s schedule.

    How GBL fuels engagement and deeper learning

    The benefits of GBL with digital games are potentially quite profound, however. First, studies indicate that playing video games in general can stimulate the generation of neurons and enhance connectivity between the regions of the brain responsible for memory formation, spatial orientation and strategic thinking. The right pairing of game and learning objectives could be argued to promote situated cognition, a theory that knowledge is constructed through – and inseparable from – social interactions and the context in which they take place. A learner immersed in SimCity stands a much greater chance of understanding the principles of taxation and the provision of public services through playing the role of a mayor, for example, than a learner being walked through the annual budget. As Lim et al. state: “games are effective because learning takes place within a meaningful context where what must be learned is directly related to the environment in which learning and demonstration take place”.

    Early-stage research on mirror neurons is adding a new aspect to the discussion around the immediacy of playing games. In short, mirror neurons suggest that when we observe someone performing an action, there is a brief moment in which our brain cells fire as if we are carrying out that action ourselves. The boundary between observer (player) and observed (in-game character) becomes blurred for a split second. A lot can happen in that split second.

    In addition to the benefits of an immersive, neuron-stroking experience, games demonstrably promote learner engagement by introducing the F-bomb into the mix (fun). They also have the capacity to provide an unrivalled social experience, as in the case of MMORPGs (massively multiplayer online role-playing games). As an example, consider how a leading MMORPG game, World of Warcraft, is applied in learning environments.

    Addressing concerns and embracing change

    However, there are often deep-seated cultural aversions to the use of games in an educational context that GBL initiatives are required to overcome. Critics have said that digital games are anti-social, that they rot your attention span, that they are not legitimate, validated learning resources. Although there is not yet a body of research that can empirically confirm or debunk the effectiveness of games used for learning, surely watching a learner plan, execute and evaluate a project in Minecraft with classmates suggests that those objections are based on dated assumptions. The language learning space in particular is still very much attached to a coursebook paradigm that is predicated on levels and a clearly defined syllabus. Perhaps GBL is too much at odds with an established business model that is the bedrock of too many large education organisations.

    So is GBL a waste of time? We’d argue that it is when its potential is not properly recognised and it is treated as light relief. Games are dynamic, engaging resources capable of delivering experiences and drawing connections that can really ignite a student’s learning experience. Furthermore, they bring a playful and unpredictable aspect to the learning process.