The impact of artificial intelligence on language learning and linguistic research

Ivanović, Đina and Chukwuma-Nwankwo, Ifeoma Francisca and Francis, Ruth Sabina (2026) The impact of artificial intelligence on language learning and linguistic research. Qubahan Political Journal, 5 (3). pp. 24-42. ISSN 3078-3356

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Abstract

This explanatory sequential mixed-methods study examines how AI-supported tools are perceived to affect language learning and linguistic research in applied-linguistic settings. The study focuses on conversational assistants, automated writing support, machine translation, speech-recognition applications, adaptive learning platforms, corpus-analysis tools, and linguistic data-processing technologies rather than on artificial intelligence as a general technological category. A structured questionnaire was completed by 420 participants, including language learners, language teachers, and linguistics researchers, followed by 36 semi-structured interviews selected from high-, moderate-, and low-use profiles. Quantitative analysis used descriptive statistics, reliability testing, exploratory factor analysis, correlation analysis, regression models with role controls, and diagnostic checks. Qualitative analysis used Reflexive Thematic Analysis supported by intercoder review, negative-case attention, and an audit trail. The results show that perceived usefulness, feedback quality, critical AI literacy, accessibility, and tool-use frequency were positively associated with perceived learning effectiveness and research efficiency, whereas dependency risk and ethical concern complicated uncritical acceptance of AI-supported work. Interview evidence indicated that participants valued AI when it supported explanation, feedback, translation, accessibility, and research organization, but they remained cautious about accuracy, privacy, authorship, bias, and loss of independent judgment. The main limitation is that outcomes are self-reported rather than measured directly as proficiency growth or productivity. The study contributes a responsible integration framework, showing that AI-supported language learning and linguistic research are perceived as most valuable when guided by human expertise, transparent policy, critical verification, and pedagogical purpose.

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