Evaluating the Impact of AI-Based Tools on Language Proficiency and Motivation: Experimental Evidence from Philology Students in Ukraine

This study evaluates the impact of AI-based tools on language learning outcomes-specifically language proficiency and student motivation-among philology students in Ukrainian higher education.Grounded in the Technology Acceptance Model (TAM) and Constructivist Learning Theory, the research employed a controlled experimental design involving 100 students, randomly assigned to experimental (AI-based tools) and control (traditional classroom) groups.Over an 8-week intervention, the experimental group used Duolingo, while the control group followed standard curriculum-based instruction.Statistical analyses (independent t-tests and ANOVA) revealed that the experimental group significantly outperformed the control group in both English and Ukrainian language proficiency, and exhibited higher motivational engagement.These results underscore the pedagogical potential of AI-based applications in enhancing personalized learning experiences in bilingual education settings.Despite its limited duration, the study highlights key benefits of integrating AI into philological education and offers practical implications for curriculum developers, educators, and policymakers.Addressing technical and infrastructural challenges remains critical for scaling such innovations across Ukrainian institutions.