Abstract
This research paper discusses the impact of language learning on
traditional language learning/teaching methods and the current language
learning/teaching methods. Traditional language learning methods, such as
classroom instructions have engaged with technology-based approaches and such
approaches became widely used in recent years. This paper examines the ways in
which both computer-assisted and mobile-assisted applications have changed the
way people learned. Lastly, this paper argues that while technology can have
powerful effects on learners, it should not solely be used alone for now;
rather it should be merged with other methods when used to ensure an effective
language learning experience
Introduction
In today’s globalized world language learning has become an essential
aspect for individuals that aim to be in contact with other cultures. Those
individuals have been using traditional methods such as the usage of
dictionaries and getting private classes. But nowadays learners started using
technology to aid their language learning process as the technology has
improved significantly, even some learners are only using technology-based
methods instead of traditional methods. The purpose of this research paper is
to discuss the impact of technology in language learning with an emphasis on
both usage of technology in traditional methods and completely new methods
introduced with technology such as mobile apps as well as evaluating its
benefits and drawbacks.
Review of Literature
When we say “traditional language
learning methods” we usually refer to a classroom environment in which there is
no technology use. This is how language learning mostly occurred till the
second decade of the 21st century. However, after the 2010s there
have been great changes in language studies. Most notably, Google introduced a
multilingual machine translation service named “Google Translate” in 2006 and
it started being widely used after the 2010s. This meant that language learners
did not necessarily need to search hardcopy dictionaries or ask their teachers
about a sentence they did not understand. Even though it was not usually giving
accurate translations till switching to neural machine translation from
statistical machine translation in 2016 still learners could benefit from its
translations greatly. For example, students could practice a phrase in their
target language with Google Translate by using its translation, text-to-speech,
and automatic speech recognition options without relying on the classroom
environment and classroom materials for target language input (van Lieshout,
C., & Cardoso, W., 2022)
After smartphones were
introduced, downloadable mobile applications became a thing in iOS devices at
first. First-ever applications were mostly games and mobile application
versions of frequently used websites such as social media platforms (Such as
Facebook and Twitter). Online language learning platforms such as Duolingo
introduced their mobile applications which made language learning easier and
more accessible. Learners did not need to go to classrooms or libraries for
language learning sources, they became able to practice their target language
with a device they carry in their pockets whenever they wanted. For example,
Duolingo was first introduced as a mobile application in 2011 but language
learners realized that it was not solely enough for learning a language because
such applications did not give many options for native-like language practice,
instead, the learners had to repeat the same phrases over and over again. This
also gave a new realization to problems that occur in online language learning
and as a solution other applications such as the ones that use artificial
intelligence to give a more personalized learning experience like Rosetta Stone
and the applications that match learners with native speakers of the target
language to practice (e.g: Hello Talk, Tandem) were introduced to enhance the
mobile language learning process were introduced
What can be called the parent of
all the applications mentioned above is “Computer-Assisted Language Learning”
as known as “CALL”. It is tightly related to the other areas of applied
linguistics and computer science. Not very recently but in the 1950s CALL was
used for the first time when computers were extremely large, however,
experiments with CALL remained limited due to the cost and the limited number
of those huge machines. In 1959, the University of Illinois developed some
applications that can be considered the first-ever computer-based applications
for language learning to be used on the Programmed Logic/Learning for Automated
Teaching Operations (PLATO) system. PLATO’s programming language consisted of
some of the best features of CALL. Its focus was on the translation of Russian
documents during the Cold War (Beatty, 2013).
Till the 1980s CALL system relied
on drill-and-practice systems mostly, after the 1980s experimentations with
games and simulations started to occur in the field of CALL, which were later
to be called “intelligent CALL” or “ICALL” could be seen in the Bassein and
Underwood’s work of Juegos Coomunicativos in 1985. Juegos Communicativos was a
game created for communicative practice of the Spanish language. In 1995,
another game named Spion was introduced to practice German. (Otto, 2017) In
summary, the shift in EFL teaching from structural approaches to communicative
approaches also affected how computer-assisted language learning technologies
existed.
But nowadays with the great
development in technology and artificial intelligence, more diverse ways can be
used to aid language learning. For example, learners don’t even need to use the
language exchange applications mentioned above necessarily. Because now there
are artificial intelligence models that chat with you just like a native
speaker and using them is safer than talking to a stranger on the internet.
Also, if you could not understand a phrase in a context a native speaker of the
language would not be the best person to explain it to you because often native
speakers do not study their own language and do not know its rules but an AI
chatbot can explain that phrase to you immediately and would not get bored if
you ask it over and over again when you don’t understand it. But when you chat
with a native speaker you do not know when they are going to respond or if they
are going to respond at all.
However, practicing the language
with no human interaction is not always beneficial as I stated above. Because its
outcomes would be similar to the outcomes of the grammar-translation method
since there is no oral practice of the language. You can understand the
language in deep but you cannot speak it in real-life situations. In some
cases, you would not even be able to understand the language when someone
speaks to you, because all you practiced is grammatical structures but in a way
that is similar to real-life communication. In the traditional structural
methods, this is caused by the reliance on books and other hardcopy materials whereas,
in the usage of artificial intelligence models, this is caused by reliance on
written communication only.
But when technology is used to
aid the language learning process rather than solely relying upon it, it
enhances the learning process. Using an artificial intelligence model would
help a learner if the learner also has the ability to use language in human
interactions. If the learner does not possess the ability to use language in
real-life human interactions still he or she can watch a video on YouTube to
get used to the sound of the language. On YouTube, or other video streaming
platforms there are many sources for listening activities for the target language,
you can even watch a random person’s daily life to get to know about his or her
culture and language at the same time, this is not something possible in
traditional language learning methods
Without technology, a learner
could practice with native speakers only if he or she visited the country where
his or her target language is spoken or if the learner encountered a native
speaker of their target language in their own country but technology makes it
easier to practice with native speakers or hear how native speakers sound at
least. This means one of the best contributions of technology to language is
making it more accessible for everyone. In the past not everyone could travel
abroad and take private classes, it is still like that but today anyone who
wants to learn a language can do it on their phones or computers easily. They
can download hundreds of book pdfs about their target language, they can find
hundreds of audial sources to get accustomed to the sound of their target
language.
One of the best examples of
audial sources to aid language learning is forvo.com. It is a Web 2.0-based
website (which means a collaborative website that is editable by users such as
Wikipedia) that provides a user-created and user-maintained database for
pronunciation in any language in the world. Any user can record and upload a
pronunciation from everyday items to celebrity names. Even if the pronunciation
of the words the user wanted to pronounce are already provided still the user
can record his or her pronunciation and upload it on Forvo, the pronunciations
are voted by other users on their accuracy. Currently, there are over 700,000
pronunciations on the site in 241 languages. Unsurprisingly since Forvo is an
English-based website it has over 70,000 recorded pronunciations making English
the most well-represented language on the site. (Grieser, 2010)
While it was not easy to check
the pronunciation of a word previously it is now one click away thanks to
Forvo. In the past, all a person could do was reading the transcription of a
word in the dictionary to get an idea about what the word sounded like, even
the teachers used to do that so it was almost impossible to know how a native
speaker would pronounce the word unless hearing it from a native speaker in
person. But today we can learn the pronunciation of a word immediately and even
we can hear it from different accents and dialects thanks to Forvo and similar
websites.
We should note that while
learning via computer enables the learners to learn in a non-classroom environment,
learning through the mobile phone enables the learner to learn even when they
are having a walk or cooking in the kitchen. Therefore, today we also have MALL
(Mobile Assisted Language Learning) besides CALL. Even though learning through
mobile devices has its own advantages it still has some disadvantages such as
reading difficulty caused by the small screen and data storage limitations. So
it is sometimes difficult for students to carry on the tasks given by the
teachers, so teachers should take to what extent students have access to
technology into account. (Miangah, 2012)
We for sure do not know what the
future will bring but we know that technology is developing quickly and we wake
up to new technologies every single day, we said “Language learning
technologies include no or less human interactions” above but one day there
might be systems that do not only make us study the language in the written
form only but study it as if we are chatting with a native speaker face to
face. This is likely to occur due to the quickly developing virtual reality
technologies.
Conclusion
In conclusion, this research paper has discussed the impact of
technology on language learning processes with a focus on its history and its
benefits in enhancing the second language learning process. This paper also
compares traditional language teaching methods with current methods that are
combined with technology such as computer-assisted language learning systems
and mobile-assisted language learning systems. Traditional methods that are
supported with technology-based applications usually enhance the learning
process with its accessibility, and more personalized learning experiences. On
the other hand this paper argues that technology should not be solely used
since it would not enhance the language learning process as effective as when
it is combined with traditional methods such as face to face communication.
Because the technology of today is not enough to take place of real human
interaction. In summary, this paper shows how technology enhances language
learning processes with its benefits and drawbacks.
References
1) van
Lieshout, C., & Cardoso, W. (2022). Google Translate as a tool for
self-directed language learning. Language Learning & Technology, 26(1),
1–19. http://hdl.handle.net/10125/73460
2)
Beatty,
K. (2013). Teaching & researching: Computer-assisted language learning
applied linguistics in action (2nd ed., reprint, revised). Routledge.
3)
Otto,
S. E. K. (2017). From Past to Present: A Hundred Years of Technology for L2
Learning. In C. A. Chapelle & S. Sauro (Eds.), The Handbook of Technology
and Second Language Teaching and Learning (pp. 15-33). John Wiley & Sons,
Inc.
4) Grieser,
Jessica (2010) "The Effect of Dialect Features on the Perception of
“Correctness” in English-Word Voting Patterns on Forvo.com," University of
Pennsylvania Working Papers in Linguistics: Vol. 16 : Iss. 2 , Aricle 10.
5)
Miangah, T. M., &
Nezarat, A. (2012). Mobile-Assisted Language Learning. International Journal of
Distributed and Parallel Systems (IJDPS), 3(1), 309. DOI:
10.5121/ijdps.2012.3126.
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