Adams, W. C. (2015). Conducting semi-structured interviews. In K. E. Newcomer, H. P. Hatry, & J. S. Wholey (Eds.), Handbook of practical program evaluation (pp. 492-505). Wiley. https://doi.org/10.1002/9781119171386.ch19
Afshar, H. S., & Ranjbar, N. (2021). EAP teachers’ assessment literacy: From theory to practice. Studies in Educational Evaluation, 70, 101042. https://doi.org/10.1016/j.stueduc.2021.101042
Amani, S., White, L., Balart, T., Arora, L., Shryock, K. J., Brumbelow, K., & Watson, K. L. (2023). Generative AI perceptions: A survey to measure perceptions of faculty, staff, and students on generative AI tools in academia. arXiv. https://doi.org/10.48550/arXiv.2304.14415
Andujar, A., & Spratt, M. (2023). Using AI to support CLIL teacher language. Journal of Research in Applied Linguistics, 14(2), 7-19. https://doi.org/10.22055/rals.2023.45267.3177
Baidoo-Anu, D., & Owusu Ansah, L. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. SSRN. http://dx.doi.org/10.2139/ssrn.4337484
Bannister, P., Santamaría Urbieta, A., & Alcalde Peñalver, E. (2023a). A Delphi study on generative AI and English medium instruction assessment: Implications for social justice. Iranian Journal of Language Teaching Research, 11(3), 53-90. https://doi.org/10.30466/ijltr.2023.121406
Bannister, P., Santamaría Urbieta, A., & Alcalde Peñalver, E. (2023b). A systematic review of generative AI and (English medium instruction) higher education. Aula Abierta, 52(4), 401-409. https://doi.org/10.17811/rifie.52.4.2023.401-409
Bañeres, D., Rodríguez-González, M. E., Guerrero-Roldán, A.-E., & Cortadas, P. (2023). An early warning system to identify and intervene online dropout learners. International Journal of Educational Technology in Higher Education, 20(1), 1-25. https://doi.org/10.1186/s41239-022-00371-5
Battersby, M. (2019). Appeals to authority: Sources and experts. In J. A. Blair (Ed.), Studies in critical thinking. Windsor in argumentation vol. 8 (pp. 289-305). Open Library.
Bearman, M. & Ajjawi, R. (2023). Learning to work with the black box: Pedagogy for a world with artificial intelligence. British Journal of Educational Technology, 54(5), 1160-1173. https://doi.org/10.1111/bjet.13337
Bearman, M., Ryan, J., & Ajjawi, R. (2022). Discourses of artificial intelligence in higher education: a critical literature review. Higher Education, 86, 369-385. https://doi.org/10.1007/s10734-022-00937-2
Birhane, A., Kasirzadeh, A., Leslie, D., & Wachter, S. (2023). Science in the age of large language models. Nature Reviews Physics, 5(5), 277–280. https://doi.org/10.1038/s42254-023-00581-4
Boden, M. A. (2004). The creative mind myths and mechanisms. Routledge.
Bozkurt, A., & Sharma, R. C. (2023). Challenging the status quo and exploring the new boundaries in the age of algorithms: Reimagining the role of generative AI in distance education and online learning. Asian Journal of Distance Education, 18(1), i-vii. https://doi.org/10.5281/zenodo.7755273
Bozkurt, A., Xiao, J., Lambert, S., Pazurek, A., Crompton, H., Koseoglu, S., Farrow, R., Bond, M., Nerantzi, C., Honeychurch, S., Bali, M., Dron, J., Mir, K., Stewart, B., Costello, E., Mason, J., Stracke, C., Romero-Hall, E., Koutropoulos, A., . . . Jandrić, P. (2023). Speculative futures on ChatGPT and generative artificial intelligence (AI): A collective reflection from the educational landscape. Asian Journal of Distance Education, 18(1), 53-130. https://doi.org/10.5281/zenodo.7636568
Braun, V., & Clarke, V. (2023). Toward good practice in thematic analysis: Avoiding common problems and be(com)ing a knowing researcher. International Journal of Transgender Health, 24(1), 1-6. https://doi.org/10.1080/26895269.2022.2129597
Braun, V., Clarke, V., Hayfield, N. & Terry, G. (2019). Thematic analysis. In P. Liamputtong (Ed.), Handbook of research methods in social sciences (pp. 843-860). Springer. https://doi.org/10.1007/978-981-10-5251-4_103
Brew, M., Taylor, S., Lam, R., Havemann, L., & Nerantzi, C. (2023). Towards developing AI literacy: Three student provocations on AI in higher education. Asian Journal of Distance Education, 18(2), 1-11. https://doi.org/10.5281/zenodo.8032387
Carrigan, M. (2023, April 27). Are universities too slow to cope with Generative AI? Impact of Social Sciences. https://blogs.lse.ac.uk/impactofsocialsciences/2023/04/27/are-universities-to-slow-to-cope-with-generative-ai/
Chan, C. K. Y., & Lee, K. K. W. (2023). The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and Millennial Generation teachers? Smart Learning Environments, 10(1), 1-23. https://doi.org/10.48550/arXiv.2305.02878
Chen, Y., Jensen, S., Albert, L. J., Gupta, S., & Lee, T. (2023). Artificial intelligence (AI) student assistants in the classroom: Designing chatbots to support student success. Information Systems Frontiers, 25(1), 161-182. https://doi.org/10.1007/s10796-022-10291-4
Chen, Z. (2022). Artificial intelligence evaluation for mathematics teaching in colleges under the guidance of wireless network. Mobile Information Systems, 2022, 1-9. https://doi.org/10.1155/2022/3201004
Creswell, J. W., & Plano Clark, V. L. (2011). Designing and conducting mixed methods research. SAGE Publications Ltd.
Dalalah, D., & Dalalah, O. M. A. (2023). The false positives and false negatives of generative AI detection tools in education and academic research: The case of ChatGPT. The International Journal of Management Education, 21(2), 100822. https://doi.org/10.1016/j.ijme.2023.100822
Dawson, P. (2021). Defending assessment security in a digital world: Preventing e-cheating and supporting academic integrity in higher education. Routledge.
Dawson, P. (2020). Cognitive offloading and assessment. In M. Bearman, P. Dawson, R. Ajjawi, J. Tai, & D. Boud (Eds.), Re-imagining university assessment in a digital world (pp. 37-48). Springer. https://doi.org/10.1007/978-3-030-41956-1_4
Dearden, J. (2014). English as a medium of instruction —a growing global phenomenon. British Council. https://www.britishcouncil.org/sites/default/files/e484_emi_cover_option_3_final_web.pdf
Deng, C., Ji, X., Rainey, C., Zhang, J., & Lu, W. (2020). Integrating Machine Learning with Human Knowledge. IScience, 23(11), 101656. https://doi.org/10.1016/j.isci.2020.101656
Derakhshan, A., & Shakki, F. (2024). Opportunities and challenges of implementing online English courses in Iranian public and private schools. Journal of Research in Applied Linguistics, 15(1), 17-31. https://doi.org/10.22055/rals.2023.44418.3111
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., & Carter, L. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Eager, B., & Brunton, R. (2023). Prompting higher education towards AI-augmented teaching and learning practice. Journal of University Teaching & Learning Practice, 20(5), 1-19. https://doi.org/10.53761/1.20.5.02
Eaton, S. E. (2021). Plagiarism in higher education: Tackling tough topics in academic integrity. Bloomsbury Publishing.
Eke, D. O. (2023). ChatGPT and the rise of generative AI: Threat to academic integrity? Journal of Responsible Technology, 13, 100060. https://doi.org/10.1016/j.jrt.2023.100060
Elkhatat, A. M. (2023). Evaluating the authenticity of ChatGPT responses: A study on text-matching capabilities. International Journal for Educational Integrity, 19(15), 1-23. https://doi.org/10.1007/s40979-023-00137-0
Farazouli, A., Cerratto-Pargman, T., Bolander-Laksov, K., & McGrath, C. (2023). Hello GPT! Goodbye home examination? An exploratory study of AI chatbots impact on university teachers’ assessment practices. Assessment & Evaluation in Higher Education, 49(3), 363-375. https://doi.org/10.1080/02602938.2023.2241676
Fergus, S., Botha, M., & Ostovar, M. (2023). Evaluating academic answers generated using ChatGPT. Journal of Chemical Education, 8, 423-438. https://doi.org/10.1021/acs.jchemed.3c00087
Fido, D., & Wallace, L. (2023). The unique role of ChatGPT in closing the awarding gap. The Interdisciplinary Journal of Student Success. https://cdspress.ca/wp-content/uploads/2023/02/IJSS_FEB_2023_8_Final.pdf
Fulcher, G. (2012). Assessment literacy for the language classroom. Assessment Quarterly, 9, 113-132. https://doi.org/10.1080/15434303.2011.642041
Gan, L., & Lam, R. A review on language assessment literacy: Trends, foci and contributions. Language Assessment Quarterly, 19(5), 503-525. https://doi.org/10.1080/15434303.2022.2128802
Harding, L., Kremmel, B., & Erberharter, K. (2022). Language assessment literacy in second spoken language assessment contexts. In T. Huag, W. Mann, & U. Knoch (Eds.), The handbook of language assessment across modalities (pp. 373-382). Oxford University Press. https://doi.org/10.1093/oso/9780190885052.003.0032
Hultgren, A. K., Owen, N., Shrestha, P., Kuteeva, M., & Mežek, S. (2022). Assessment and English as a medium of instruction. Challenges and opportunities. Journal of English Medium Instruction, 1(1), 105-123. https://doi.org/10.1075/jemi.21019.hul
Johinke, R., Cummings, R., & Di Lauro, F. (2023). Reclaiming the technology of higher education for teaching digital writing in a post—pandemic world. Journal of University Teaching and Learning Practice, 20(2), 1-16. https://doi.org/10.53761/1.20.02.01
Koszowy, M., & Walton, D. (2019). Epistemic and deontic authority in the argumentum ad verecundiam. Pragmatics and Society, 10(2), 287-315. https://doi.org/10.1075/ps.16051.kos
Kremmel, B., & Harding, L. (2020). Towards a comprehensive, empirical model of language assessment literacy across stakeholder groups: Developing the language assessment literacy survey. Language Assessment Quarterly, 17(1), 100-120. https://doi.org/10.1080/15434303.2019.1674855
Lasagabaster, D. (2022). Teacher preparedness for English-medium instruction. Journal of English-Medium Instruction, 1(1), 48-64. https://doi.org/10.1075/jemi.21011.las
Liang, W., Yusekgonul, M., Mao, Y., Wu, E., & Zou, J. (2023). GPT detectors are biased against non-native English writers. Patterns, 4, 100779. https://doi.org/10.48550/arXiv.2304.02819
Liu, J. E., Lo Y. Y., & Xin, J. J. (2023). CLIL teacher assessment literacy: A scoping review. Teaching and Teacher Education, 129, 104150. https://doi.org/10.1016/j.tate.2023.104150
Macaro, E. (2022). English medium instruction: What do we know so far and what do we still need to find out? Language Teaching, 55, 533-546. https://doi.org/10.1017/S0261444822000052
Macaro, E. (2018). English medium instruction: Content and language in policy and practice. Oxford University Press.
Mancho-Barés, G., Khan, S., & Aguilar-Pérez, M. (2022). An EMI lecturer’s assessment practices with engineering laboratory reports. Journal of English-Medium Instruction, 1(2), 232-254. https://doi.org/10.1075/jemi.21008.man
McKinley, J., & Rose, H. (2022). English language teaching and English-medium instruction. Journal of English-Medium Instruction, 1(1), 85–104. https://doi.org/10.1075/jemi.21026.mck
Nieminen, J. H., & Carless, D. (2023). Feedback literacy: A critical review of an emerging concept. Higher Education, 85, 1381-1400. https://doi.org/10.1007/s10734-022-00895-9
Nikolic, S., Daniel, S., Haque, R., Belkina, M., Hassan, G. M., Grundy, S., Lyden, S., Neal, P., & Sandison, C. (2023). CHATGPT versus engineering education assessment: A multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity. European Journal of Engineering Education, 48(4), 559–614. https://doi.org/10.1080/03043797.2023.2213169
Pack, A., & Maloney, J. (2023). Using generative artificial intelligence for language education research: Insights from using OpenAI’s ChatGPT. TESOL Quarterly, 57(4), 1571-1582. https://doi.org/10.1002/tesq.3253
Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning & Teaching, 6(1), 342-363. https://doi.org/10.37074/jalt.2023.6.1.9
Ruslin, R., Mashuri, S., Rasak, M. S. A., Alhabsyi, F., & Syam, H. (2022). Semi-structured interview: A methodological reflection on the development of a qualitative research instrument in educational studies. Journal of Research & Method in Education, 12(1), 22-29. https://doi.org/10.9790/7388-1201052229
Russell, S. (2019). Artificial intelligence and the problem of human control. Viking.
Sadasivan, V. S., Kumar, A., Balasubramanian, S., Wang, W., & Feizi, S. (2023). Can AI-generated text be reliably detected? arXiv. https://doi.org/10.48550/arXiv.2303.11156
Sah, P. K. (2022). A research agenda for English-medium instruction. Conversations with scholars at the research fronts. Journal of English-Medium Instruction, 1(1), 124-136. https://doi.org/10.1075/jemi.21022.sah
Scarino, A. (2013). Language assessment literacy as self-awareness: Understanding the role of interpretation in assessment and teacher learning. Language Testing, 30(3), 309–327. https://doi.org/10.1177/0265532213480128
Shahzadi, A., & Ducasse, A. M. (2022). Language assessment literacy of teachers in an English medium of instruction university: Implications for ELT training in Pakistan. Studies in Language Assessment, 11(1), 92-118. https://doi.org/10.58379/BZWF5085
Sharples, M. (2023). Towards social generative AI for education: Theory, practices and ethics. Learning: Research and Practice, 9(2), 159-167. https://doi.org/10.48550/arXiv.2306.10063
Sharples. M. (2022). Automated essay writing: An AIED opinion. International Journal of Artificial Intelligence in Education, 32, 1119-1126. https://doi.org/10.1007/s40593-022-00300-7
Sharples. M. & Pérez y Pérez, R. (2022). Story machines: How computers have become creative writers. Routledge.
Stobart, G. (2008). Testing times: The uses and abuses of assessment. Routledge.
Su, J., & Yang, W. (2023). Unlocking the power of ChatGPT: A framework for applying generative AI in education. ECNU Review of Education, 6(3), 355-503. https://doi.org/10.1177/20965311231168423
Sudajit-apa, M. (in press). Dismantling the discursive representation of women in AI-generated life-changing narratives: A critical discourse analysis. Journal of Research in Applied Linguistics. https://doi.org/10.22055/rals.2024.46100.3232
Sullivan, M., Kelly, A., & McLaughlan, P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning & Teaching, 6(1), 1-10. https://doi.org/10.37074/jalt.2023.6.1.17
Taylor, L. (2013). Communicating the theory, practice and principles of language testing to test stakeholders: Some reflections. Language Testing, 30, 403–412. https://doi.org/10.1177/0265532213480338
Tzirides, A. O., Saini, A., Zapata, G. Searsmith, D., Cope, B., Kalantzis, M., Castro, V., Kourkoulou, T., Jones, J., Abrantes da Silva, R., Whiting, J., & Polyxeni Kastania, N. (2023). Generative AI: Implications and applications for education. arXiv. https://doi.org/10.48550/arXiv.2305.07605
Tsagari, D. (2020). Language assessment literacy. Concepts, challenges and prospects. In S. Hidri (Ed.), Perspectives on language assessment literacy: Challenges for improved student learning (pp. 13-32). Taylor & Francis Books. https://doi.org/10.4324/9781003016083-2
Tsagari, D., & Vogt, K. (2017). Assessment literacy of language teachers around Europe: Research, challenges, and future prospects. Papers in Language Testing and Assessment, 6(1), 41-63. https://doi.org/10.58379/UHIX9883
Vogt, K., & Tsagari, D. (2014). Assessment literacy of foreign language teachers: Findings of a European study. Language Assessment Quarterly, 11(4), 374-402. https://doi.org/10.1080/15434303.2014.960046
Wang, T., Lund, B. D., Marengo, A., Pagano, A., Mannuru, N. R., Teel, Z. A., & Pange, J. (2023). Exploring the potential impact of artificial intelligence (AI) on international students in higher education: Generative AI, chatbots, analytics, and international student success. Applied Sciences, 13(11), 6716. https://doi.org/10.3390/app13116716
Yildirim-Erbasli, S. N., & Bulut, O. (2023). Conversation-based assessment: A novel approach to boosting test-taking effort in digital formative assessment. Computers and Education: Artificial Intelligence, 4, 100135. https://doi.org/10.1016/j.caeai.2023.100135
Yu, H., & Guo, Y. (2023). Generative artificial intelligence empowers educational reform: Current status, issues, and prospects. Frontiers in Education, 8, 1183162. https://doi.org/10.3389/feduc.2023.1183162
Yufik, Y. M., Friston, K. J., & Moran, R. J. (2022). Editorial: Understanding in the human and the machine. Frontiers in Systems Neuroscience, 16, 10811112. https://doi.org/10.3389/fnsys.2022.1081112
Zajko, M. (2022). Artificial Intelligence, algorithms, and social inequality: Sociological contributions to contemporary debates. Sociology Compass, 16(3), e12962. https://doi.org/10.1111/soc4.12962
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