<![CDATA[The increasing integration of information technology into translation studies has repositioned alignment and bilingual corpora as central resources for both linguistic analysis and English language teaching. Although extensive research has explored corpus-based translation and natural language processing, existing studies remain scattered across technical, pedagogical, and sociocultural perspectives. This systematic literature review addresses this fragmentation by synthesizing empirical evidence on alignment practices and bilingual corpus construction in IT-based translation. Guided by PRISMA procedures, twenty-two peer-reviewed journal articles published between 2020 and 2025 were retrieved from Scopus, Crossref, and Google Scholar and analyzed through thematic synthesis. The findings reveal a clear shift from manual and rule-based alignment toward semi-automated and hybrid models that integrate NLP techniques with human linguistic validation. While technological innovation has enhanced scalability, accuracy, and analytical efficiency, persistent challenges remain in domain adaptation, low-resource languages, and the interpretation of culturally embedded meaning. The review further demonstrates that bilingual corpora play a significant pedagogical role by supporting data-driven learning, learner autonomy, and critical language awareness in translation and English language teaching contexts. Beyond technical application, aligned corpora also function as sociocultural artifacts that reflect ideology, identity, and communicative purpose across languages. This study contributes an integrative framework that connects computational alignment, linguistic interpretation, and pedagogical application within a unified perspective. The findings highlight the importance of hybrid human–machine approaches for sustainable corpus development and suggest broader implications for translation education, ELT practice, and inclusive multilingual research in digitally mediated learning environments.]]>
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