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support collaborative learning. Interactive dialogue systems and conversational agents
are some of the features that can be found in some AI-based language learning systems
and that can simulate a real-life communication environment. Such systems enable
learners to rehearse conversational skills within a conducive and non-threatening space.
3. Conceptual framework
The theoretical framework of this research reveals how Artificial Intelligence (AI)
learning tools correlate with the ESL learning outcomes, i.e., the vocabulary learning and
the pronunciation development. Language learning tools that run on AI offer learners an
interactive learning session with the ability to train language skills with adaptive
exercises, speech recognition systems and personalized feedback to learners. The AI
technologies support a language learning process as they offer real time feedback,
adaptive learning, and interaction with the learner. These mediators help the learners to
acquire knowledge of vocabulary and enhance the accuracy of their pronunciations.
When they communicate with AI-based learning systems, the learners get immediate
feedback on their performance, an aspect that assists them in recognizing the linguistic
mistakes and perfecting their language output. The framework presupposes that AI
learning tools are utilized as a support system in instruction that will increase the
autonomy of learners and offer them personalized learning practice. With the help of
continuous exposure to vocabulary materials and pronunciation drills, learners gain more
lexical knowledge and phonological awareness. Therefore, the use of AI technologies in
the language learning setting leads to the enhancement of the language skills of ESL
students. Thus, the idea behind the current study is that AI-oriented language learning
devices can have a positive effect on vocabulary learning and pronunciation training due
to interactive and adaptive learning.

Figure 1. Conceptual framework diagram
Source: Author
4. Research gap
Despite the fact that the role of Artificial Intelligence in language education has
been studied previously, some key gaps still exist. To begin with, the majority of the
previous studies have tested vocabulary acquisition and pronunciation development as
independent variables and have not tested their joint enhancement in the context of a
single instructional intervention. Second, most of the studies are hypothetical or held in a

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