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EXPLORING THE BOUNDARIES OF WHETHER AI CAN REPLACE
HUMAN TEACHERS
Saydasheva Angelina Anvarovna
Associate Professor, Inha University in Tashkent
https://doi.org/10.5281/zenodo.15726845
Abstract
As artificial intelligence (AI) advances rapidly, its integration into
education, particularly in language acquisition, has ignited a controversial
debate regarding the role of human educators. This article examines the current
capabilities of AI, its pedagogical limitations, and the essential human elements
of language instruction to assess the degree to which AI can replace language
educators. AI technologies can help you learn more about yourself and offer you
feedback right away, but they don't have the emotional intelligence, cultural
sensitivity, or flexibility needed for full language learning. This paper argues,
through a critical examination of recent research and expert opinions, that AI
should be viewed not as a replacement, but as an auxiliary tool that augments
the capacities of educators and students in increasingly digital learning contexts.
Key words:
Artificial Intelligence (AI), chatbots, ethics, language
acquisition, machine learning, Natural Language Processing (NLP), pedagogy
Introduction
In a very short length of time, AI has impacted a lot of areas, such as
healthcare, banking, and education. Chatbots, speech recognition systems,
grammar checkers, and adaptive learning platforms are all common AI tools
used in language instruction today. This progress raises a basic question: Can AI
replace human language teachers? This article contends that language
acquisition remains a fundamentally human endeavour, despite the capacity of
AI to automate certain aspects. AI should be thought of as a tool, not a substitute.
Part of AI in Learning a Language
Apps that use AI have made learning a language less complicated and more
personal. Machine learning algorithms are used by sites like Duolingo and
Rosetta Stone to alter content according on how well users do (Wang & Vasquez,
2012). Chatbots, like the ones in apps like Mondly and Elsa Speak, enable you
rehearse speaking and fix your pronunciation right away (Burstein et al., 2020).
Natural Language Processing (NLP) can check your grammar, assist you learn
new vocabulary, and provide you writing feedback that becomes better over
time.
These tools have a lot of good points:
• Scalability: AI can help a lot of pupils at once.
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• Open all the time: Students can practise anytime they like, and they don't
have to arrange an appointment with a teacher.
• Quick feedback: Automated systems make it less likely that you will
make mistakes.
AI systems can also assist with making lesson plans by gathering
information. Teachers can look at patterns in how often students make mistakes,
how long they stay interested, and how their abilities improve. This enables
them use data to make relevant classes to each student. These kinds of analytics
are helpful for major school systems to find out where the curriculum isn't
working as effectively as it might and where kids in different groups aren't as
interested as they could be.
The limits of AI when it comes to taking the place of teachers
Even though AI can perform a lot of things, it still needs a few fundamental
things to learn a language:
1. Emotional Intelligence and Motivation: Learning a language may be
hard, terrifying, and a chance to grow as a person. Human teachers assist
children learn by giving them empathy, support, and chances to interact with
other people (Krashen, 1982).
2. Cultural Nuance and Pragmatics: Algorithms alone cannot effectively
instruct on the functioning of language within social and cultural frameworks.
Teachers put language use in real-life settings (Kukulska-Hulme, 2020).
3. Being flexible in the classroom: Teachers routinely check in on how
students are feeling, what they don't understand, and how the group is
functioning together. AI can't read div language or react in a way that feels
natural (Hockly, 2018).
4. Critical Thinking and Dialogue: Teachers want students to utilise new
words in class debates, argue, and see things from other people's points of view.
AI isn't very good at this yet.
5. Ethical and Privacy Issues: AI systems need user data, which makes
people worry about privacy, permission, and bias in algorithms. Teachers are
better at handling sensitive information and making the classroom a secure
place to learn because of their professional ethics.
Also, the concept that all pupils have the same access to AI technologies
doesn't take into account the challenges that arise with the digital divide.
Students who live in locations with few resources may not have the tools,
internet access, or digital skills they need to get the most out of programs that
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use AI. Teachers usually act as middlemen who fill in these gaps by modifying
the materials and methods to fit the demands of the location.
A Model for Collaboration: Educators and AI
Instead than seeing AI as a replacement, it is better to think of it as a way
for people to work together. In this idea, teachers are facilitators who employ AI
for practice, review, and testing. AI accomplishes the same things over and over,
so teachers can focus on activities that need higher-order thinking. On top of
that, teachers use data from AI to make lessons more relevant to their pupils.
This integration aligns with the concept of TPACK (Technological
Pedagogical Content Knowledge), which posits that technology should enhance
rather than supplant pedagogical skills (Mishra & Koehler, 2006). AI can help in
flipped classrooms, where students undertake AI-driven tasks before class and
then work on them more fully with the teacher's help during class.
Digital pedagogy should be a part of teacher training programs so that
instructors can critically evaluate, choose, and apply AI tools that align with their
educational objectives. If teachers do not acquire this kind of training, AI could
be used in a way that does not suit the needs of students' emotions and
language.
Conclusion
AI has made language learning easier to get to and more efficient, but it
can not replace the human components of teaching that are important for
meaningful, contextual, and emotionally supported learning. In the future, the
greatest technique to teach language will be a mix of different methods. AI can
help, but it can't take the position of teachers, who are vital. Teachers give
students the social, emotional, and cultural support they need to learn a
language, while AI makes the process more personal and gives them more
feedback. We can develop language learning spaces that are open to everyone,
work well, and look to the future by knowing what AI and human teachers are
good at.
References:
1.
Burstein, J., Elliot, N., & Molloy, H. (2020). Natural language processing for
educational applications. Morgan & Claypool Publishers.
2.
Hockly, N. (2018). Focus on learning technologies. Oxford University Press.
3.
Krashen, S. D. (1982). Principles and practice in second language
acquisition. Pergamon Press.
4.
Kukulska-Hulme, A. (2020). Mobile-assisted language learning (MALL) and
AI. ReCALL, 32(3), 233–252. https://doi.org/10.1017/S0958344020000125
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5.
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content
knowledge: A framework for teacher knowledge. Teachers College Record,
108(6), 1017–1054.
6.
Wang, S., & Vasquez, C. (2012). Web 2.0 and second language learning:
What does the research tell us? CALICO Journal, 29(3), 412–440.
