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All Journal Journal of English Language Studies CALL Journal of Language and Literature Studies
Rakhmi, Fanny Puji
Politeknik Negeri Jakarta
Arts Humanities Education Languange, Linguistic, Communication & Media Other

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Language Learning Strategies Among Vocational Generation Z Students: Insights from A Digital Native Perspective Sofa, Nidia; Rakhmi, Fanny Puji; Mariam, Iis; Onida, Mawarta
Journal of English Language Studies Vol 10, No 2 (2025): Available Online in September 2025
Publisher : English Department - University of Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/jels.v10i2.32504

Abstract

This study explores the English language learning strategies employed by vocational Generation Z students at Politeknik Negeri Jakarta, focusing on their integration of digital-native characteristics within an English for Specific Purposes (ESP) context. Employing a quantitative survey design, data were collected from second-semester vocational students through two adapted instruments: Oxford’s Strategy Inventory for Language Learning (SILL) and Teo’s Digital Natives Assessment Scale (DNAS). A total of 108 students participated in the study. Data analysis revealed that students employed direct, indirect, and digital-native strategies at comparably high frequencies, with no statistically significant differences among the strategy types (p > 0.05). At the subscale level, instant gratification or rewards was most prominent, followed by metacognitive and technology use, whereas graphic communication was least used, with compensation and affective relatively lower. It is recommended that ESP educators should blend strategies within each task: begin with brief targeted language practice (direct), include a short plan/monitor step or peer check (indirect/metacognitive), and complete the task with approved digital support      in order to optimize ESP learning for vocational education contexts. Future work should validate the adapted digital-native scale in local contexts, replicate across diverse ESP settings, and link reported strategies to objective learning outcomes using longitudinal and mixed-methods designs.  
POPULAR OR POPULER? COMPARING AI AND HUMAN TRANSLATION OF NONCE WORDS IN WICKED’S INDONESIAN SUBTITLES Abdillah, Taufik Eryadi; Fanny Puji Rakhmi; Ina Sukaesih; Farizka Humolungo; Septina Indrayani
CALL Vol. 7 No. 2 (2025): CALL
Publisher : Universitas Islam Negeri Sunan Gunung Djati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/call.v7i2.51205

Abstract

This study investigates the process of translating nonce words in Indonesian subtitles of the musical fantasy film Wicked, focusing on the challenges posed by highly creative and humorous expressions that remain underexplored in audiovisual translation studies. Set in the magical land of Oz, the film incorporates playful and imaginative expressions like Galindafied and braverism, which present unique translation difficulties. The study employs content analysis to compare human-generated subtitles from Apple TV with AI-generated subtitles produced by ChatGPT. While both human and AI translations tend to convey the general meaning of the nonce words, they fail to capture the stylistic and humorous nuances present in the source language. Human translations can be literal or omit creative expressions entirely, suggesting that neither method fully encapsulates the inventiveness and playfulness of the source language. This study underscores the importance of developing more adaptable strategies for translating highly creative audiovisual texts.
Investigating Romantic-Tone Transfers in the Human Translation Compared to AI Subtitling: A Case Study of the Dilan 1990 Film Rakhmi, Fanny Puji; Abdillah, Taufik Eryadi; Humolungo, Farizka; Sukaesih, Ina; Indrayani, Septina
Journal of Language and Literature Studies Vol. 6 No. 1 (2026): March
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/jolls.v6i1.3570

Abstract

This paper examines how romantic tone is carried across languages in film subtitling, where text must be brief, well-timed, and easy to read. We focus on Dilan 1990, a popular Indonesian teen romance known for playful, indirect lines that rely on inference and rhythm. Today, many studios generate first-pass subtitles with neural machine translation and then rely on human post-editors to refine style and timing. We ask how well AI handles this kind of subtle, affect-rich dialogue and where human editing still adds value. We compare 24 well-known lines addressed by Dilan to Milea in two versions: the official English subtitles and outputs produced by ChatGPT under the same line-level constraints. Using a practical set of translation techniques (e.g., modulation, compression, adaptation) and a tone rubric (playfulness/coyness, warmth, persona/rhythm), we perform a line-by-line analysis. The human subtitles tend to keep implicature and pace through concise, idiomatic choices that fit character and reading speed. The AI versions are fluent but more likely to explain subtext or lengthen the line, which can blunt teasing and shift the scene’s mood. AI can match human choices when the source line is already compact and direct. Where meaning depends on ellipsis, metaphor, and micro-timing, human post-editing remains crucial. We close with practical guidelines for NMT-plus-post-editing workflows in romance subtitling.
Co-Authors Farizka Humolungo Ina Sukaesih Ina Sukaesih Indrayani, Septina Mariam, Iis Onida, Mawarta Septina Indrayani Sofa, Nidia Taufik Eryadi Abdillah