Machine Learning in Online Language Teaching
October 23, 2023
By Aida Mª Gómez López
Machine learning has emerged as a powerful tool that has revolutionized various fields, and language teaching is no exception. With the proliferation of online educational platforms and the exponential growth of Internet access, machine learning has found fertile ground to transform the way people learn languages. In this article, we will explore the advantages and drawbacks of integrating machine learning in this area, highlighting its ability to personalize learning, provide immediate feedback, and offer access to interactive resources. Machine learning promises to transform the language learning experience for a global audience – can it deliver?
But what is machine learning?
Machine learning was developed in the 1950s and Arthur Samuel defined it as “the field of study that gives computers the ability to learn without being explicitly programmed”. So, as we can imagine, it is closely linked to data science, which encompasses a variety of techniques and tools to collect, process, analyze, and visualize data to understand phenomena, solve problems, and generate value in various fields. Thus, machine learning, based on databases, uses various algorithms to obtain predictive analysis and relate events.
In other words, machine learning is nothing more than an artificial intelligence technique that teaches machines to learn by themselves, without the need to be explicitly programmed. This facet of artificial intelligence makes it possible, through algorithms, to establish relationships between different variables, classify vast amounts of information, and identify discrepancies and failures between data. This approach is currently implemented in a wide variety of systems and for different purposes. On this occasion, we will focus on language learning.
Advantages of machine learning in online language training
Personalization of learning
Personalization of learning requires adapting the methodology, content, and pace of teaching to the individual needs of each learner. One of the main advantages of machine learning is its ability to analyze data, learning patterns, and individual preferences, making it key to improving student experiences.
Thanks to the evaluation of the student’s progress and skills, this tool can identify the strengths and weaknesses of each individual and design a customized program to adapt the educational content to the individual’s objectives.
Immediate feedback
The ability to provide immediate feedback is a crucial advantage of machine learning in language teaching. When students perform activities or answer questions, machine learning systems can analyze their responses in real-time using advanced algorithms, allowing them to quickly identify areas of strength and weakness in student performance.
Immediate feedback is a very positive tool because it allows students to correct mistakes instantly, which helps to consolidate learning and avoid repeating mistakes in the future. In addition, it allows students to maintain a continuous flow of learning without interruptions, which contributes to a more efficient and effective learning process overall.
Interactive resources
Access to interactive resources is one of the great advantages of machine learning in online language teaching. Thanks to this technology, a wide variety of educational tools can be developed, ranging from simple vocabulary practice applications to educational games and conversation simulations.
These resources not only offer a fun and engaging way to learn a language but also provide a more immersive and effective learning experience. For example, vocabulary practice apps can present words and phrases in relevant contexts, which helps learners better understand their meaning and usage. Educational games, on the other hand, offer challenges and rewards that encourage active participation and information retention.
These types of resources are dynamic tools that also adapt to the individual needs of learners while making language learning more fun, and therefore more engaging.
Disadvantages of machine learning in online language teaching
Self-discipline and time management.
A major disadvantage of online learning is that it requires a great deal of self-discipline and effective time management skills on the part of students. Unlike face-to-face classes, where there are set schedules and a more defined structure, online learning often allows greater flexibility in terms of when and where study activities take place, and while this, at first glance, might seem like a great advantage, it requires a great deal of discipline on the part of the learner.
So, this freedom that online learning provides can be beneficial for those who know how to organize themselves effectively, but can be a challenge for others who struggle to stay motivated and focused without direct guidance. Students must be able to set and maintain regular study schedules, meet deadlines, and track course progress autonomously.
Lack of human interaction
Another negative aspect of machine learning can be the lack of human interaction which some learners find essential for language learning. Communication with native speakers and face-to-face interaction with teachers may be missing in purely machine learning-based environments.
In addition, the lack of physical structure and the absence of face-to-face interactions with teachers and classmates can make it even more difficult to maintain motivation and focus. Without the external pressure of a traditional learning environment, some students may find it more difficult to stay engaged with the material and complete assignments promptly.
Data privacy
Machine learning, to be effective, relies heavily on the collection and analysis of large amounts of data. The use of this data can pose inconveniences for both students and their families, as it can cover a wide range from personal information to online behavior and other more sensitive data. Hence, clear privacy policies must be in place to protect students.
Error correction limitations
Although machine learning systems provide positive feedback and corrections are imminent, these systems also tend to have limitations in correcting more complex or subtle errors, especially when it comes to grammar and pronunciation.
Conclusion
Machine learning is a powerful tool with the potential to transform the current educational landscape. This technology can be leveraged to personalize learning, analyze educational data, improve assessment and monitoring of academic performance, as well as implement virtual tutoring, and automate routine tasks. However, as noted, it also has challenges and limitations such as the lack of human interaction or the privacy of the data collected.
After this analysis, we can conclude that machine learning has the potential to provide education that is more tailored to the individual needs of each student, more efficient, and more effective. But to make this technology a success, it is vitally important that educators, developers, technology experts, and policymakers,
work closely together, to take full advantage of the opportunities it offers and overcome the challenges that may arise on the road to a more innovative education.
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