Volume 5 • Issue 2 • PP: 24–30 • 2026
Optimizing Translation Accuracy and Contextual Sensitivity in Language: A Comparative Evaluation of AI-Based and Human Translation Approaches
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This study examines the effectiveness of artificial intelligence (AI)–based language translation in comparison with human translation, with particular attention to accuracy and contextual sensitivity in educational settings. As higher education institutions increasingly integrate AI tools into language instruction and multilingual course delivery, evaluating their pedagogical reliability and cultural appropriateness has become essential. Using a mixed-methods design, the study analyzes translation outputs produced by leading AI systems and professional human translators across academic texts, lectures, and instructional materials in multiple language pairs. Quantitative measures assess linguistic accuracy, while qualitative analysis focuses on cultural nuance, disciplinary appropriateness, and contextual meaning. Semi-structured interviews with university lecturers and students further explore perceptions of the benefits and limitations of AI-assisted translation in academic contexts. Findings indicate that although AI tools offer substantial advantages in speed and accessibility, they remain less effective in maintaining disciplinary precision and cultural depth. The study recommends a complementary model in which AI technologies support, rather than replace, human expertise in multilingual academic communication.
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