What question did this study set out to answer?

This research aims to evaluate the effectiveness of AI-assisted language learning tools on students' proficiency in English across various domains.

June 2, 2026

Measuring the Impact of AI-Assisted Language Learning on English Language Education: A Mixed-Methods Study

Key Points

This research aims to evaluate the effectiveness of AI-assisted language learning tools on students' proficiency in English across various domains.
Mixed-methods approach combining qualitative interviews with students and teachers and quantitative pre- and post-intervention language skill tests.
Qualitative data focused on experiences, privacy issues, and concerns related to AI feedback.
Quantitative data included assessments of speaking, reading, writing, and grammar proficiency before and after AI tool implementation.
Statistically significant improvements in grammar (42%), speaking (33%), vocabulary (31%), and writing (26%).
Identification of challenges such as data privacy, unequal access to technology, and potential overreliance on AI hindering critical skills.
AI tools improved access and participation in language learning, supporting teaching tasks and increasing engagement in higher-order functions.

Abstract

The use of AI tools in English language pedagogy is changing classroom practices by helping to develop students’ communicative competence and confidence and to assist teachers with their teaching tasks. This research examines the efficacy of existing artificial intelligence tools and applications for supporting English language teaching and learning, with a particular focus on the impact they have on the key language domains of speaking, reading, writing, and grammar. It explores how AI tools enhance personalization, instant feedback in language learning as well as addressing challenges such as data privacy, technology dependence and algorithmic bias. The design of this research combined both qualitative and quantitative methods. Qualitative data are collected using semi-structured interviews with students and teachers on their experiences, thoughts, and concerns about AI-assisted language teaching and learning, particularly in relation to issues of privacy, equity of access, and trust in AI-generated feedback. Quantitative data are pre- and post-intervention language skill tests that are used to measure the level of language expertise of the learners before and after the implementation of AI-assisted language learning tools. The findings suggest that AI has the potential to improve access and participation in learning and teaching, support administrative and instructional tasks, and reduce the burden on teachers, thereby enabling them to engage in higher-order pedagogical functions. The study also identified privacy and storage issues, unequal access to reliable hardware and software, and concerns that student overreliance on AI tools may obstruct language development in areas such as critical thinking, creativity, and independent problem-solving, as challenges to the successful adoption of AI. The results also revealed statistically significant improvements in grammar (42%), speaking (33%), vocabulary (31%), and writing (26%).

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