In an age where translation and conversation are automated, we're re-examining the reasons for learning Korean.
Based on the unique characteristics of the Korean language, we design AI as a collaborative partner and present prompting, writing, and speaking instructional models, as well as assessment, feedback, and ethics and policy guides.
It increases practical applicability by including a continuous strategy to reduce beginner dropouts and connect to intermediate and advanced levels.
Artificial Intelligence Encyclopedia.
You can find the artificial intelligence knowledge you need at aiseries.oopy.io.

Unlike computers, mobile devices have the advantage of being highly portable, allowing learning anytime, anywhere.
In line with this, various language learning apps have emerged.
Apps like Duolingo incorporate game elements to keep learners engaged, and machine translation services like Google Translate have become established as everyday learning tools.
At the same time, the proliferation of social media and YouTube has led learners to embrace a participatory culture, where they learn by directly communicating with speakers of the target language or by accessing cultural content like dramas, songs, and memes in real time.
--- From “01_“AI and the Change in the Language Education Paradigm””

Machine translation is basically translating sentences written in one language into another language.
When machine translation was first introduced, it was based on rules and statistics, translating each word individually, so it could not properly handle context or idiomatic expressions.
But things are a little different these days.
With the introduction of artificial neural network-based machine translation (NMT) technology, it has advanced beyond words and phrases to the level of understanding the entire context and translating it into natural sentences, and as a result, accuracy has also improved significantly.
These changes raise new questions about how and to what extent translators can be used as learning aids.
--- From 「03_“Machine Translation and AI”」

Is AI really good at providing feedback? How different would the results be if both a teacher and AI provided feedback on the same piece of writing? This question arises because studies consistently cite AI's immediate feedback as a strength.
Ahn Jae-rin and Park Jeong-ah's research began with this curiosity.
The research team gave six Korean learners' writings to six teachers and ChatGPT with the same instructions, and compared the resulting feedback side by side.
The result wasn't simply a question of who did better.
The two feedbacks revealed different strengths and limitations.
--- From “06_“AI Feedback””

As AI increasingly impacts classroom instruction and assessment, simply following the guidelines outlined above is no longer enough.
Teachers are the ones who know best when to allow and where to restrict the use of AI in the classroom.
Policies that do not properly reflect the voices of those on the ground are difficult to implement in reality.
Therefore, it is necessary for teachers to reflect on and share their own experiences to determine in which situations AI use is problematic and in which activities it is acceptable.

--- From “09_“AI Policy We Create Together””