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研究生: 張蓉蓉
Jhang, Rong-Rong
論文名稱: 臺灣大專院校翻譯課程學生使用ChatGPT進行翻譯修訂回饋之接受度初探
Exploring the Acceptance of Taiwanese College Students Using ChatGPT for Translation Revision Feedback
指導教授: 陳子瑋
Chen, Tze-Wei
口試委員: 陳子瑋
Chen, Tze-Wei
郁瑞麟
Yu, Ruei-Lin
詹柏勻
Chan, Po-yun
口試日期: 2024/07/26
學位類別: 碩士
Master
系所名稱: 翻譯研究所軍事口譯碩士在職專班
Graduate Institute of Translation and Interpretation_In-service Master's Program of Military Interpreting
論文出版年: 2024
畢業學年度: 112
語文別: 英文
論文頁數: 203
中文關鍵詞: 整合性科技接受模式ChatGPT翻譯修訂回饋
英文關鍵詞: Unified Theory of Acceptance and Use of Technology (UTAUT), ChatGPT, Translation Revision Feedback
研究方法: 調查研究半結構式訪談法
DOI URL: http://doi.org/10.6345/NTNU202401231
論文種類: 學術論文
相關次數: 點閱:126下載:7
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  • 近年來,人工智慧科技取得了飛速的進展,對各行各業產生了深遠的影響。特別是2022年11月推出的ChatGPT,在教育領域引起了廣泛的討論。本研究旨在以整合性科技接受模式(Unified Theory of Acceptance and Use of Technology, UTAUT)探討學生使用ChatGPT進行翻譯修訂回饋的影響。ChatGPT是一種基於人工智慧的大型語言模型,擁有卓越的語言理解能力,可為學生提供即時翻譯和語言學習支援。此新科技可在翻譯教育中廣泛應用,尤其是在提供翻譯修訂回饋方面,ChatGPT可以即時提供學生回饋,過去的研究大多探討教師回饋和同儕回饋,然而,目前對於學生使用ChatGPT進行翻譯修訂回饋的使用意圖和實際使用情況瞭解尚不充分。
    本研究的結果表明,整合型科技接受模式中的績效期望、努力期望、社會影響以及便利條件對於學生使用ChatGPT進行翻譯修訂回饋具有顯著影響。同時這項研究也顯示出整合性科技接受模式適合用於測量學生對使用ChatGPT進行翻譯修訂回饋的接受程度。學生對使用ChatGPT進行的翻譯修訂回饋給予了正面的評價,認為ChatGPT的即時回饋能夠提高學生翻譯學習效率。因此,這些結果支持了將ChatGPT作為教育工具在翻譯訓練領域中的應用潛力。這項研究為翻譯教育工作者和學習者在教育和人工智慧科技整合上的策略和實施提供了指引。

    In recent years, artificial intelligence technology has evolved rapidly, profoundly impacting various industries. Notably, the release of the ChatGPT in November 2022 sparked widespread discussion in the education field. This research aims to investigate the influence of students using ChatGPT for translation revision feedback by employing the Unified Theory of Acceptance and Use of Technology (UTAUT). ChatGPT, a large language model powered by AI, demonstrates exceptional linguistic comprehension capabilities, offering real-time translation and language learning support to students. This novel technology holds wide-ranging potential in translation education, notably in providing immediate feedback for translation revisions. ChatGPT can deliver prompt feedbacks to students’ translation, enhancing the learning experience. While previous studies have primarily focused on feedback from instructors and peers, current understanding of students' intentions to use ChatGPT for translation revision feedback and their actual usage of this tool remains limited and warrants further exploration.
    Our research demonstrates that performance expectancy, effort expectancy, social influence, and facilitating conditions significantly impact students' use of ChatGPT for translation revision feedback. The findings also confirm the suitability of the UTAUT model for assessing students' acceptance levels when using ChatGPT for translation revision feedback. Students provided positive evaluations of using ChatGPT for translation revision feedback, noting that its instant feedback enhances their translation learning efficiency. These results support the potential of using ChatGPT as an educational tool in the field of translation training. The study provides valuable insights for translation educators and learners for future educational strategies and implementations integrating education with AI technology.

    謝辭 i 摘要 ii Abstract iii Table of Contents iv List of Tables vi List of Figures viii Chapter 1 Introduction 1 1.1 Research Background and Motivation 1 1.2 Research Objectives and Questions 4 1.3 Chapter Arrangement 6 1.4 Definition of Key Terms 10 Chapter 2 Literature Review 13 2.1 UTAUT 13 2.2 ChatGPT 27 2.3 Translation Revision Feedback 32 2.4 Summary 37 Chapter 3 Resaerch Methods 39 3.1 Participants 40 3.2 Instruments 42 3.3 Procedure 47 3.4 Data Analysis 48 3.5 Pilot test 50 3.6 Results of the Pilot Test Data Analysis 51 3.6.1 Reliability Analysis 51 3.6.2 Item Analysis 53 3.7 Semi-Structured Interviews 55 Chapter 4 Results and Findings 59 4.1 Descriptive Statistics 59 4.2 Reliability and Validity 72 4.3 Pearson Correlation Analysis 74 4.4 Multiple Regression Analysis 78 4.5 Independent Samples t-Test and One-Way ANOVA 82 4.6 Interviews 103 Chapter 5 Discussion 127 5.1 The Level of Acceptance and Efficacy of UTAUT Model among Students Using ChatGPT for Translation Revision Feedback 127 5.2 Students' Perceptions of Using ChatGPT for Translation Revision Feedback 136 5.3 Practical Application of Using ChatGPT in Translation Education 148 Chapter 6 Conclusion 153 6.1 Conclusion 153 6.2 Contributions 155 6.3 Limitations 158 6.4 Recommendations 159 6.5 Summary 160 References 162 Appendix A Chinese Questionnaire Survey 176 Appendix B English Questionnaire Survey 181 Appendix C Extracted Transcripts of Interviews 188 Appendix D Prompts for Translation Revision Feedback 202

    Abas, M. A., Arumugam, S. E., Yunus, M. M., & Rafiq, K. R. M. (2023). ChatGPT and personalized learning: Opportunities and challenges in higher education. International Journal of Academic Research in Business and Social Sciences, 13(12), 3536-3545.
    Abbad, M. M. (2021). Using the UTAUT model to understand students’ usage of e-learning systems in developing countries. Education and Information Technologies, 26(6), 7205-7224.
    Abd Rahman, S. F., Md Yunus, M., & Hashim, H. (2021). Applying UTAUT in predicting ESL lecturers intention to use flipped learning. Sustainability, 13(15), 1-13.
    Abdaljaleel, M., Barakat, M., Alsanafi, M., Salim, N. A., Abazid, H., Malaeb, D., Mohammed, A. H., Hassan, B. A. R., Wayyes, A. M., & Farhan, S. S. (2024). A multinational study on the factors influencing university students’ attitudes and usage of ChatGPT. Scientific Reports, 14(1), 1983.
    Agyei, C., & Razi, Ö. (2022). The effect of extended UTAUT model on EFLs’ adaptation to flipped classroom. Education and Information Technologies, 27(2), 1865-1882.
    Aithal, P., & Aithal, S. (2023). Application of ChatGPT in Higher Education and Research–A Futuristic Analysis. International Journal of Applied Engineering and Management Letters (IJAEML), 7(3), 168-194.
    Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control: From cognition to behavior (pp. 11-39). Springer.
    Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
    Al Ghazali, S., Zaki, N., Ali, L., & Harous, S. (2024). Exploring the potential of ChatGPT as a Substitute teacher: A Case Study. International Journal of Information and Education Technology, 14(2), 271-278.
    Albonico, M., & Varela, P. J. (2023). A Report on the Use of ChatGPT in Software Engineering and Systems Analysis Courses. Proceedings of the XXXVII Brazilian Symposium on Software Engineering,
    Alharbi, W. (2023). AI in the foreign language classroom: A pedagogical overview of automated writing assistance tools. Education Research International, 2023(1), 4253331.
    Almaiah, M. A., Alamri, M. M., & Al-Rahmi, W. (2019). Applying the UTAUT model to explain the students’ acceptance of mobile learning system in higher education. Ieee Access, 7, 174673-174686.
    Almogren, A. S. (2022). Art education lecturers’ intention to continue using the blackboard during and after the COVID-19 pandemic: An empirical investigation into the UTAUT and TAM model. Frontiers in Psychology, 13, 944335.
    Andrews, J. E., Ward, H., & Yoon, J. (2021). UTAUT as a model for understanding intention to adopt AI and related technologies among librarians. The Journal of Academic Librarianship, 47(6), 102437.
    Antunović, G., & Pavlović, N. (2011). Here and now: Self-revision in student translation processes from L2 and L3. Across Languages and Cultures, 12(2), 213-234.
    Bahrini, A., Khamoshifar, M., Abbasimehr, H., Riggs, R. J., Esmaeili, M., Majdabadkohne, R. M., & Pasehvar, M. (2023). ChatGPT: Applications, opportunities, and threats. 2023 Systems and Information Engineering Design Symposium (SIEDS),
    Baidoo-Anu, D., & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52-62.
    Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986, 23-28.
    Baskara, R. (2023). Exploring the implications of ChatGPT for language learning in higher education. Indonesian Journal of English Language Teaching and Applied Linguistics, 7(2), 343-358.
    Bin-Nashwan, S. A., Sadallah, M., & Bouteraa, M. (2023). Use of ChatGPT in academia: Academic integrity hangs in the balance. Technology in society, 75, 102370.
    Bitzenbauer, P. (2023). ChatGPT in physics education: A pilot study on easy-to-implement activities. Contemporary Educational Technology, 15(3), ep430.
    Black, J., & Chaput, T. (2024). A Discussion of Artificial Intelligence in Visual Art Education. Journal of Computer and Communications, 12(5), 71-85.
    Bozkurt, A. (2023). Generative artificial intelligence (AI) powered conversational educational agents: The inevitable paradigm shift. Asian Journal of Distance Education, 18(1), 198-204.
    Budhathoki, T., Zirar, A., Njoya, E. T., & Timsina, A. (2024). ChatGPT adoption and anxiety: a cross-country analysis utilising the unified theory of acceptance and use of technology (UTAUT). Studies in Higher Education, 1-16.
    Cao, S., & Zhong, L. (2023). Exploring the effectiveness of ChatGPT-based feedback compared with teacher feedback and self-feedback: Evidence from Chinese to English translation. arXiv preprint arXiv:2309.01645.
    Chao, C.-M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in Psychology, 10.
    Chi, M. T. (1996). Constructing self‐explanations and scaffolded explanations in tutoring. Applied cognitive psychology, 10(7), 33-49.
    Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
    Dai, W., Lin, J., Jin, H., Li, T., Tsai, Y.-S., Gašević, D., & Chen, G. (2023). Can large language models provide feedback to students? A case study on ChatGPT. 2023 IEEE International Conference on Advanced Learning Technologies (ICALT),
    Dalgıç, A., Yaşar, E., & Demir, M. (2024). ChatGPT and learning outcomes in tourism education: The role of digital literacy and individualized learning. Journal of Hospitality, Leisure, Sport & Tourism Education, 34, 100481.
    Davis, F. D. (1989a). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340.
    Davis, F. D. (1989b). Technology acceptance model: TAM. Al-Suqri, MN, Al-Aufi, AS: Information Seeking Behavior and Technology Adoption, 205-219.
    Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace 1. Journal of applied social psychology, 22(14), 1111-1132.
    Duong, C. D. (2024). Modeling the determinants of HEI students’ continuance intention to use ChatGPT for learning: a stimulus–organism–response approach. Journal of Research in Innovative Teaching & Learning.
    Endong, F., & Inyang, J. B. (2014). Gate-Keeping and Feedback as Determinants of the Translation/Interpretation Process. African Research Review, 8(4), 56-67.
    Fan, P., Gong, H., & Gong, X. (2023). The Application of ChatGPT in Translation Teaching: Changes, Challenges, and Responses. International Journal of Education and Humanities, 11(2), 49-52.
    Ferreira, A. P., & Loureiro, A. (2024). STUDENTS'PERCEPTIONS OF THE USE OF ARTIFICIAL INTELLIGENCE IN TRANSLATION PRACTICES CLASSES. PRATICA-Revista Multimédia de Investigação em Inovação Pedagógica e Práticas de e-Learning, 7(1), 33-49.
    Fianu, E., Blewett, C., & Ampong, G. O. (2020). Toward the development of a model of student usage of MOOCs. Education+ Training, 62(5), 521-541.
    Firat, M. (2023). What ChatGPT means for universities: Perceptions of scholars and students. Journal of Applied Learning and Teaching, 6(1), 57-63.
    Fishbein, M., & Ajzen, I. (1975). The Theory of Reasoned Action as applied to moral behaviour: A confirmatory analysis. In: Addison-Wesley Publishing Company, Reading. MA.
    Habibi, A., Muhaimin, M., Danibao, B. K., Wibowo, Y. G., Wahyuni, S., & Octavia, A. (2023). ChatGPT in higher education learning: Acceptance and use. Computers and Education: Artificial Intelligence, 5, 100190.
    Hair Jnr, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis.
    Harrington, S. A. (2023). The ultimate study partner: Using a custom chatbot to optimize student studying during law school. Available at SSRN 4457287.
    Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81-112. https://doi.org/10.3102/003465430298487
    Hong, W. C. H. (2023). The impact of ChatGPT on foreign language teaching and learning: Opportunities in education and research. Journal of Educational Technology and Innovation, 5(1), 37-45.
    Hsu, L. (2023). EFL learners’ self-determination and acceptance of LMOOCs: The UTAUT model. Computer Assisted Language Learning, 36(7), 1177-1205.
    Huang, J., & Li, S. (2023). Opportunities and challenges in the application of ChatGPT in foreign language teaching. International Journal of Education and Social Science Research, 6(04), 75-89.
    Hyland, K., & Hyland, F. (2006). Feedback on second language students' writing. Language teaching, 39(2), 83-101.
    Južnič, T. M. (2013). Assessment feedback in translator training: A dual perspective. New Horizons in Translation Research and Education, 1, 75-98.
    Kalla, D., & Smith, N. (2023). Study and analysis of chat GPT and its impact on different fields of study. International Journal of Innovative Science and Research Technology, 8(3), 827-833.
    Khechine, H., Lakhal, S., Pascot, D., & Bytha, A. (2014). UTAUT model for blended learning: The role of gender and age in the intention to use webinars. Interdisciplinary journal of E-Learning and Learning objects, 10(1), 33-52.
    Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. Relc Journal, 54(2), 537-550.
    Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., & Maningo, J. (2023). Performance of ChatGPT on USMLE: potential for AI-assisted medical education using large language models. PLoS digital health, 2(2), e0000198.
    Kwak, Y., Seo, Y. H., & Ahn, J.-W. (2022). Nursing students' intent to use AI-based healthcare technology: Path analysis using the unified theory of acceptance and use of technology. Nurse Education Today, 119, 105541.
    Lazareva, A., Vindbo, S., & Spanos, A. (2024). Student experiences with using ChatGPT in History classes. INTED2024 Proceedings,
    Lee, J. (2018). Feedback on feedback: Guiding student interpreter performance [Journal Article]. Translation & Interpreting: The International Journal of Translation and Interpreting Research, 10(1), 152-170.
    Lee, M.-K. (2015). Peer feedback in second language writing: Investigating junior secondary students' perspectives on inter-feedback and intra-feedback. System, 55, 1-10.
    Lee, U., Jeong, Y., Koh, J., Byun, G., Lee, Y., Hwang, Y., Kim, H., & Lim, C. (2024). Can ChatGPT be a debate partner? Developing ChatGPT-based application “DEBO” for debate education, findings and limitations. Educational Technology & Society, 27(2), 321-346.
    Lera, I., Moyà-Alcover, G., Guerrero, C., & Jaume-I-Capó, A. (2023). MAXIMIZING LEARNING EFFICIENCY WITH CHATGPT: WAYS TO INTEGRATE ARTIFICIAL INTELLIGENCE INTO EDUCATION. EDULEARN23 Proceedings,
    Li, J. (2024). The Application of Artificial Intelligence Technology in Optimizing Translation Systems Supported by ChatGPT. 2024 Third International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE),
    Li, J., Ren, X., Jiang, X., & Chen, C.-H. (2023). Exploring the Use of ChatGPT in Chinese Language Classrooms. International Journal of Chinese Language Teaching, 4(3), 36-55.
    Limna, P., Kraiwanit, T., Jangjarat, K., Klayklung, P., & Chocksathaporn, P. (2023). The use of ChatGPT in the digital era: Perspectives on chatbot implementation. Journal of Applied Learning and Teaching, 6(1), 64-74.
    Limna, P., Siripipatthanakul, S., Siripipattanakul, S., Woodeson, K., & Auttawechasakoon, P. (2022). Applying the UTAUT to explain factors affecting english learning intention via Netflix (English Subtitle) among Thai people. Asia-Pacific Review of Research in Education, 1(1), 1-19.
    Limo, F. A. F., Tiza, D. R. H., Roque, M. M., Herrera, E. E., Murillo, J. P. M., Huallpa, J. J., Flores, V. A. A., Castillo, A. G. R., Peña, P. F. P., & Carranza, C. P. M. (2023). Personalized tutoring: ChatGPT as a virtual tutor for personalized learning experiences. Przestrzeń Społeczna (Social Space), 23(1), 293-312.
    Lin, X. (2023). Exploring the role of ChatGPT as a facilitator for motivating self-directed learning among adult learners. Adult Learning, 35(3), 156-166.
    Liu, T., Kim, E., Li, X., Yuizono, T., Nagai, Y., & Lu, Y. (2020). Research and Practice of Hybrid Teaching Based on AI technology for Foreign Language Translation. 2020 International Conference on Computer Engineering and Application (ICCEA),
    Liu, Y. C., & Huang, Y.-M. (2015). Using the UTAUT model to examine the acceptance behavior of synchronous collaboration to support peer translation. Jalt Call Journal, 11(1), 77-91.
    Lyster, R., Saito, K., & Sato, M. (2013). Oral corrective feedback in second language classrooms. Language teaching, 46(1), 1-40.
    Ma, X., & Huo, Y. (2023). Are users willing to embrace ChatGPT? Exploring the factors on the acceptance of chatbots from the perspective of AIDUA framework. Technology in society, 75, 102362.
    Mahmoud, R. H. (2022). Implementing AI-based conversational chatbots in EFL speaking classes: an evolutionary perspective.
    Menon, D., & Shilpa, K. (2023). “Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model. Heliyon, 9(11).
    Minh, A. N. (2024). Leveraging ChatGPT for enhancing English writing skills and critical thinking in university freshmen. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 3(2), 51-62.
    Mohamed, A. M. (2024). Exploring the potential of an AI-based Chatbot (ChatGPT) in enhancing English as a Foreign Language (EFL) teaching: perceptions of EFL Faculty Members. Education and Information Technologies, 29(3), 3195-3217.
    Montenegro-Rueda, M., Fernández-Cerero, J., Fernández-Batanero, J. M., & López-Meneses, E. (2023). Impact of the implementation of ChatGPT in education: A systematic review. Computers, 12(8), 153.
    Mosaiyebzadeh, F., Pouriyeh, S., Parizi, R., Dehbozorgi, N., Dorodchi, M., & Macêdo Batista, D. (2023). Exploring the Role of ChatGPT in Education: Applications and Challenges. Proceedings of the 24th Annual Conference on Information Technology Education,
    Mossop, B. (2019). Revising and Editing for Translators. Routledge.
    Mukred, M., Asma, M. U., & Hawash, B. (2023). Exploring the acceptance of ChatGPT as a learning tool among academicians: a qualitative study. J. Komunikasi Malays. J. Commun., 39(4), 306-323.
    Mungoli, N. (2023). Exploring the Synergy of Prompt Engineering and Reinforcement Learning for Enhanced Control and Responsiveness in Chat GPT. Journal of Electrical Electronics Engineering, 2(3), 201-205.
    Nassaji, H. (2015). The interactional feedback dimension in instructed second language learning.
    Nazir, A., & Wang, Z. (2023). A comprehensive survey of ChatGPT: Advancements, applications, prospects, and challenges. Meta-Radiology, 100022.
    Neunzig, W., & Tanqueiro, H. (2005). Teacher feedback in online education for trainee translators. Meta, 50(4).
    Ngo, T. T. A. (2023). The perception by university students of the use of ChatGPT in education. International Journal of Emerging Technologies in Learning (Online), 18(17), 4-19.
    Nguyen, H. T., & Chu, Q. P. (2021). Estimating university students’ acceptance of technological tools for studying English through the UTAUT model. International Journal of TESOL & Education, 1(3), 209-234.
    Nida, E. A. (1964). Toward a science of translating: with special reference to principles and procedures involved in Bible translating. Brill Archive.
    Niyozov, N., Bijanov, A., Ganiyev, S., & Kurbonova, R. (2023). The pedagogical principles and effectiveness of utilizing ChatGPT for language learning. E3S Web of Conferences,
    Odewumi, M. O., Yusuf, M. O., & Oputa, G. O. (2018). UTAUT Model: Intention to Use Social Media for Learning Interactive Effect of Postgraduate Gender in South-West Nigeria. International Journal of Education and Development using Information and Communication Technology, 14(3), 239-251.
    Opara, E., Mfon-Ette Theresa, A., & Aduke, T. C. (2023). ChatGPT for teaching, learning and research: Prospects and challenges. Opara Emmanuel Chinonso, Adalikwu Mfon-Ette Theresa, Tolorunleke Caroline Aduke (2023). ChatGPT for Teaching, Learning and Research: Prospects and Challenges. Glob Acad J Humanit Soc Sci, 5, 33-40.
    Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., & Ray, A. (2022). Training language models to follow instructions with human feedback. Advances in neural information processing systems, 35, 27730-27744.
    Polyportis, A., & Pahos, N. (2024). Understanding students’ adoption of the ChatGPT chatbot in higher education: the role of anthropomorphism, trust, design novelty and institutional policy. Behaviour & Information Technology, 1-22.
    Radford, A., Narasimhan, K., Salimans, T., & Sutskever, I. (2018). Improving language understanding by generative pre-training.
    Rahaman, M. S. (2023). Can chatgpt be your friend? emergence of entrepreneurial research. Emergence of Entrepreneurial Research
    Raj, R., Singh, A., Kumar, V., & Verma, P. (2023). Analyzing the potential benefits and use cases of ChatGPT as a tool for improving the efficiency and effectiveness of business operations. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 3(3), 100140.
    Rakap, S. (2023). Chatting with GPT: Enhancing Individualized Education Program Goal Development for Novice Special Education Teachers. Journal of Special Education Technology, 0(0), 1-10. https://doi.org/10.1177/01626434231211295
    Rapanta, C., Botturi, L., Goodyear, P., Guàrdia, L., & Koole, M. (2021). Balancing technology, pedagogy and the new normal: Post-pandemic challenges for higher education. Postdigital Science and Education, 3(3), 715-742.
    Rashid, M. (2023). How is The Development and Deployment of AI Models Like ChatGPT Affecting The Job Market and What Are The Implications For Workers in Various Industries.
    Rasul, T., Nair, S., Kalendra, D., Robin, M., de Oliveira Santini, F., Ladeira, W. J., Sun, M., Day, I., Rather, R. A., & Heathcote, L. (2023). The role of ChatGPT in higher education: Benefits, challenges, and future research directions. Journal of Applied Learning and Teaching, 6(1), 41-56.
    Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 121-154.
    Rogers, E. M. (1995). Lessons for guidelines from the diffusion of innovations. The Joint Commission journal on quality improvement, 21(7), 324-328.
    Romero Rodríguez, J. M., Ramírez-Montoya, M. S., Buenestado Fernández, M., & Lara Lara, F. (2023). Use of ChatGPT at university as a tool for complex thinking: Students' perceived usefulness. Journal of New Approaches in Educational Research, 12(2), 323-339.
    Roza, V., & Zulhirawati, Z. (2023). Higher Students’ Perception of Using Chat GPT in Translating English Texts. BiCED Proceeding, 1, 64-73.
    Sánchez-Ruiz, L. M., Moll-López, S., Nuñez-Pérez, A., Moraño-Fernández, J. A., & Vega-Fleitas, E. (2023). ChatGPT challenges blended learning methodologies in engineering education: a case study in mathematics. Applied Sciences, 13(10), 6039.
    Sattari, A., Abdekhoda, M., & Zarea Gavgani, V. (2017). Determinant factors affecting the web–based training acceptance by health students, applying UTAUT model. International Journal of Emerging Technologies in Learning (iJET), 12(10), 112-126.
    Scholl, A., Schiffner, D., & Kiesler, N. (2024). Analyzing Chat Protocols of Novice Programmers Solving Introductory Programming Tasks with ChatGPT. arXiv preprint arXiv:2405.19132.
    Shadiev, R., & Feng, Y. (2023). Using automated corrective feedback tools in language learning: a review study. Interactive Learning Environments, 1-29.
    Shih, C. Y.-y. (2006). Revision from translators’ point of view: An interview study. Target. International Journal of Translation Studies, 18(2), 295-312.
    Sinaga, J. N., Panjaitan, E. S., & Nurjanah, S. (2024). Analysis of Factors Affecting the Use of ChatGPT at Mikroskil University: A Study Based on the Extended UTAUT2 Model. Brilliance: Research of Artificial Intelligence, 4(1), 151-161.
    Smith, A., Hachen, S., Schleifer, R., Bhugra, D., Buadze, A., & Liebrenz, M. (2023). Old dog, new tricks? Exploring the potential functionalities of ChatGPT in supporting educational methods in social psychiatry. International Journal of Social Psychiatry, 69(8), 1882-1889.
    Sobaih, A. E. E., Elshaer, I. A., & Hasanein, A. M. (2024). Examining Students’ Acceptance and Use of ChatGPT in Saudi Arabian Higher Education. European Journal of Investigation in Health, Psychology and Education, 14(3), 709-721.
    Sok, S., & Heng, K. (2023). ChatGPT for education and research: A review of benefits and risks. Cambodian Journal of Educational Research, 3(1), 110-121.
    Songsiengchai, S., Sereerat, B.-o., & Watananimitgul, W. (2023). Leveraging Artificial Intelligence (AI): Chat GPT for Effective English Language Learning among Thai Students. English Language Teaching, 16(11), 1-68.
    Stojanov, A., Liu, Q., & Koh, J. H. L. (2024). University students’ self-reported reliance on ChatGPT for learning: A latent profile analysis. Computers and Education: Artificial Intelligence, 6, 100243.
    Strzelecki, A. (2023). To use or not to use ChatGPT in higher education? A study of students’ acceptance and use of technology. Interactive Learning Environments, 1-14.
    Stutz, P., Elixhauser, M., Grubinger-Preiner, J., Linner, V., Reibersdorfer-Adelsberger, E., Traun, C., Wallentin, G., Wöhs, K., & Zuberbühler, T. (2023). Ch (e) atGPT? an anecdotal approach addressing the impact of ChatGPT on teaching and learning Giscience.
    Swanson, P. B., & Schlig, C. (2010). Improving second language speaking proficiency via interactional feedback. International Journal of Adult Vocational Education and Technology (IJAVET), 1(4), 17-30.
    Synekop, O., Lytovchenko, I., Lavrysh, Y., & Lukianenko, V. (2024). Use of Chat GPT in English for Engineering Classes: Are Students’ and Teachers’ Views on Its Opportunities and Challenges Similar? International Journal of Interactive Mobile Technologies, 18(3), 129-146.
    Tajik, E., Tajik, F. (2023). A comprehensive Examination of the potential application of Chat GPT in Higher Education Institutions. TechRxiv. https://doi.org/https://doi.org/10.36227/techrxiv.22589497
    Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information systems research, 6(2), 144-176.
    Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 125-143.
    Tian, W., Ge, J., Zhao, Y., & Zheng, X. (2024). AI Chatbots in Chinese higher education: adoption, perception, and influence among graduate students—an integrated analysis utilizing UTAUT and ECM models. Frontiers in Psychology, 15, 1268549.
    Tseng, T. H., Lin, S., Wang, Y.-S., & Liu, H.-X. (2022). Investigating teachers’ adoption of MOOCs: the perspective of UTAUT2. Interactive Learning Environments, 30(4), 635-650.
    Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017). Attention is all you need. Advances in neural information processing systems, 30.
    Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
    Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 157-178.
    Washbourne, K. (2014). Beyond error marking: written corrective feedback for a dialogic pedagogy in translator training. The Interpreter and Translator Trainer, 8(2), 240-256.
    Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT): a literature review. Journal of Enterprise Information Management, 28(3), 443-488. https://doi.org/10.1108/JEIM-09-2014-0088
    Wu, T., He, S., Liu, J., Sun, S., Liu, K., Han, Q.-L., & Tang, Y. (2023). A brief overview of ChatGPT: The history, status quo and potential future development. IEEE/CAA Journal of Automatica Sinica, 10(5), 1122-1136.
    Yang, J. (2017). Using computer assisted translation tools’ translation quality assessment functionalities to assess students’ translations. The Language Scholar, 1(1), 90-104.
    Yao, G. (2023). Using UTAUT Model to Examine Acceptance of Online Interpreting Learning in China. 2023 IEEE 12th International Conference on Educational and Information Technology (ICEIT),
    Yildiz Durak, H. (2019). Examining the acceptance and use of online social networks by preservice teachers within the context of unified theory of acceptance and use of technology model. Journal of Computing in Higher Education, 31(1), 173-209.
    Yuxiu, Y. (2024). Application of translation technology based on AI in translation teaching. Systems and Soft Computing, 6, 200072.
    Zacharis, G., & Nikolopoulou, K. (2022). Factors predicting University students’ behavioral intention to use eLearning platforms in the post-pandemic normal: an UTAUT2 approach with ‘Learning Value’. Education and Information Technologies, 27(9), 12065-12082.
    Zhang, K., & Yu, Z. (2022). Extending the UTAUT model of gamified English vocabulary applications by adding new personality constructs. Sustainability, 14(10), 6259.

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