Article Per Year (5 Year)
p-Index From 2021 - 2026
2.339
P-Index
This Author published in this journals
All Journal Indonesian Journal of Applied Linguistics (IJAL) CaLLs : Journal of Culture, Arts, Literature, and Linguistics Script Journal: Journal of Linguistic and English Teaching LLT Journal: A Journal on Language and Language Teaching AICLL: ANNUAL INTERNATIONAL CONFERENCE ON LANGUAGE AND LITERATURE Scope: Journal of English Language Teaching Borneo Educational Journal (Borju) Studies in English Language and Education E3L : Journal of English Laguange Teaching, Linguistics and Literature Prosiding Seminar Nasional PPG Universitas Mulawarman Lire Journal (Journal of Linguistics and Literature)
Syamdianita Syamdianita, Syamdianita
Unknown Affiliation
Religion Arts Humanities Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

Published : 21 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 21 Documents
Search

 1   2   3 
EFL STUDENTS’ ACCEPTANCE OF DEEPL TRANSLATION: A TECHNOLOGY ACCEPTANCE MODEL STUDY Cahyani, Reihayyu Dwi; Syamdianita, Syamdianita; Aridah, Aridah; Iswari, Weningtyas Parama; Ahada, Ichi
Lire Journal (Journal of Linguistics and Literature) Vol. 9 No. 3 (2025): In Progress
Publisher : Elite Laboratory Jurusan Sastra Inggris Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/ire.v9i3.535

Abstract

This study applied the Technology Acceptance Modes (TAM)framework to investigates university EFL students' acceptance of DeepL machine translation tool, focusing on how frequency of use influences their perceptions. A descriptive qualitative approach was used involving purposive sampling of four students in semi-structured interviews. A short questionnaire was administered beforehand to classify participants into two categories, two frequent and two infrequent DeepL users. of the machine translation tool DeepL in the context of learning English as Foreign Language (EFL), involving four participants (two frequent users and two infrequent users). The results showed that frequent users found DeepL valuable for vocabulary acquisition, translation accuracy, and academic writing support, whereas infrequent users highlighted limitations such as the lack of a paraphrasing feature and issues with formality. These differences suggest that usage frequency significantly impacts perceived usefulness and ease of use of the tool. This study is among the first to extend the TAM framework to a machine translation tool like DeepL, addressing a gap in MT research by examining the role of usage frequency. The findings offer both theoretical and practical significance, providing insights into how MT tools can be more effectively integrated into EFL learning.
Co-Authors A.K. Amarullah Achmad Nabel Rahmattullah Ahada, Ichi Ahmar Ahmar, Ahmar Ahyu Ningtyas Anjani, Novira Aridah Aridah Aridah, Aridah Asih Santi Hastuti Asrifan, Andi Bambang Yudi Cahyono Cahyani, Reihayyu Dwi Chris Asanti Chris Asanti, Chris Dedi Rahman Nur Febiyani, Febiyani Gita Mutiara Hati Ismail, Nurhijrah Iswari, Weningtyas Parama Iwan Setiawan Kalukar, Ventje Jany Kubra, Zakiyatul Maria Teodora Ping, Maria Teodora Mohpul, Purnamawati Muid, Abdul Nira Miranda Noor Rachmawaty Nur Mukminatien Nurchalis, Nur Fadillah Nurhijrah Ismail Putra, Setoaji Putri, Alma Fadilla Rachmawaty, Noor Rahmat Soe'oed Rubiyah, Rubiyah Rubiyah, Rubiyah Rukayah Rukayah Rusmawaty, Desy Sjamsir, Hasbi Suci, Dewi Nur Susilo, Susilo Weningtyas Parama Iswari Weningtyas Parama Iswari, Weningtyas Parama Yazid Basthomi