<![CDATA[This systematic literature review (SLR) examines the functions, limitations, and effectiveness of machine translation (MT) tools in English language learning. Most of the reviewed studies addressed the context of English as a Foreign Language (EFL), with few references to other linguistic environments. MT tools have been successful in translating text quickly and improving personalized learning experiences. Yet, these tools continue to grapple with context-sensitive translation, including that which demands cultural sensitivity or gender fidelity. The review identifies an increasing demand for incorporating MT tools into pedagogical approaches, underlining learner attitudes and cultural as well as linguistic difference challenges like gender bias. Even so, the research also necessitates better MT systems, proposing a blended approach with human post-editing to counter these weaknesses. The research identifies a wide knowledge gap in areas such as the Philippines and other underrepresented scopes, restricting the generalizability of findings to various learning settings. Consequently, overcoming biases, improving tools accuracy, and offering transparent usage instructions remains an unexplored area. Subsequent research needs to broaden the scope through a range of research designs, especially mixed methods and experimental studies, and investigating the utilization of MT tools in various learning environments. Furthermore, researchers need to enhance the incorporation of MT in language instruction, fixing biases, and refashioning these tools for more inclusive, sensitive applications. Lastly, more research needs to examine the sociolinguistic effects of gender bias in MT and AI tools for a variety of gendered and low resource languages to promote an ideal and productive learning environment.]]>
