<![CDATA[The difficulty of understanding verb and noun reduplication in Indonesian and English without the aid of Natural Language Processing (NLP) technology. The urgency of this research lies in the gap in computational approaches that are not yet adaptive to morphological and semantic differences between languages. The aim of this research is to analyse the role of NLP technology in identifying reduplication patterns and their implications for language learning. The research approach used a mixed methods approach. The sample size was 300 respondents. Data were collected through questionnaires, semi-structured interviews, and analysis of a bilingual Indonesian-English corpus. Analysis techniques used were descriptive statistics and ANOVA assisted by SPSS 29.0, thematic analysis, and evaluation of a BERT-based NLP model. The results show that NLP is able to recognize cross-language reduplication variations with a high level of reliability. Students demonstrated a good understanding of the form and function of reduplication and a positive attitude towards the use of NLP technology. The conclusion is that NLP is effective in capturing the semantic nuances of reduplication. Practical implications: these results support the development of bilingual curricula, digital learning media, and contextual NLP-based language analysis applications.]]>
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