Teachers’ Perspectives on AI-Driven Quillionz for Generating EFL Reading Comprehension Quizzes

Authors

DOI:

https://doi.org/10.54855/paic.2462

Keywords:

AI, reading comprehension, teachers’ perspectives, quizzes, Quillionz

Abstract

Emerging artificial intelligence (AI) has significant impacts on language learning and teaching, providing innovative pedagogies in sustainable educational settings. Among the powerful tools stands Quillionz (https://www.quillionz.com), a free AI-powered platform for building questions, quizzes, and assessments. Nevertheless, there has been little research on teachers’ experiences and perceptions of using Quillionz in EFL classroom settings. This study set out to explore teachers’ perspectives on utilizing Quillionz to generate reading comprehension quizzes for non-English major students through a pre and post-survey design. The research employed both qualitative and quantitative methods with Likert-scale questionnaires distributed to 48 English teachers from a vocational college in Hanoi before and after using Quillionz over four weeks. A paired sample T-Test was conducted to explore shifts in teachers’ perceptions. Subsequently, in-depth interviews were carried out with 10 randomly selected participants for further investigation. The findings revealed positive views among teachers towards Quillionz, its identified potential, and suggestions for more effective implementation. This paper makes a significant contribution to the integration of technology in language teaching, thereby enhancing students’ learning experiences.

Author Biographies

Nguyen Thi Luong, FPT university, Ha Noi, Vietnam

Ms. Luong Nguyen is an English lecturer at FPT Polytechnic College, FPT University, Vietnam. She is interested in applying technology in teaching and classroom management.

Nguyen Hai Linh, FPT university, Ha Noi, Vietnam

Ms. Linh Nguyen is an English teacher for non-English-major students at FPT Polytechnic College, FPT University, Vietnam. Her research interest is language teaching methodology, especially for teaching listening and speaking skills. She always tries her best to help non-English-majored students enhance their English competency.

Le Duc Hanh, School of Languages and Tourism, Hanoi University of Industry, Vietnam

Ms. Hanh Le has been working as an English lecturer at the School of Languages and Tourism, Hanoi University of Industry, Vietnam since 2007. Besides teaching, she currently works as the deputy director of the center of training and partnership development at her school. She has taken responsibility for designing and teaching EOP blended programs for technical students. Her areas of professional interest include professional development, EMI, and ICTs in education.

References

Alam, A. (2023). Harnessing the power of AI to create intelligent tutoring systems for enhanced classroom experience and improved learning outcomes. Lecture notes on data engineering and communications technologies, 571–591. https://doi.org/10.1007/978-981-99-1767-9_42 DOI: https://doi.org/10.1007/978-981-99-1767-9_42

Bowman, M. A., Vongkulluksn, V. W., Jiang, Z., & Xie, K. (2020). Teachers’ exposure to professional development and the quality of their instructional technology use: The mediating role of teachers’ value and ability beliefs. Journal of Research on Technology in Education, 54(2), 188–204. https://doi.org/10.1080/15391523.2020.1830895 DOI: https://doi.org/10.1080/15391523.2020.1830895

Chen, X., Zou, D., Cheng, G., & Xie, H. (2021). Artificial intelligence-assisted Personalized Language Learning: systematic review and co-citation analysis. In 2021 International Conference on Advanced Learning Technologies (ICALT) (pp. 241-245). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/icalt52272.2021.00079 DOI: https://doi.org/10.1109/ICALT52272.2021.00079

Deng, X., & Yu, Z. (2023). A meta-analysis and systematic review of the effect of chatbot technology use in sustainable education. Sustainability, 15(4), 29-40. https://doi.org/10.3390/su15042940 DOI: https://doi.org/10.3390/su15042940

Dijkstra, R., Genç, Z., Kayal, S., & Kamps, J. (2022). Reading Comprehension Quiz Generation using Generative Pre-trained Transformers. In iTextbooks@ AIED (pp. 4-17). https://e.humanities.uva.nl/publications/2022/dijk_read22.pdf

Duong, N. H., Le, D. H., Nguyen, H. L., & Nguyen, T. L. (2024). Applying AI in Teaching English through The Language Hub System at a Vocational College in Hanoi from Teachers’ Perspective. In The 12th OpenTESOL International Conference 2024 Proceedings (pp. 183-195). https://opentesol.org/wp-content/uploads/2024/08/FINALIZED-PROCEEDINGS-OF-THE-12TH-OPENTESOL-INTERNATIONAL-HYBRID-CONFERENCE-2024-final.pdf

Ertmer, P. A., Ottenbreit-Leftwich, A. T., Sadik, O., Sendurur, E., & Sendurur, P. (2012). Teacher beliefs and technology integration practices: A critical relationship. Computers & Education, 59(2), 423–435. https://doi.org/10.1016/j.compedu.2012.02.001 DOI: https://doi.org/10.1016/j.compedu.2012.02.001

Hoang, N. T., Han, D. N., & Le, D. H. (2023). Exploring Chatbot AI in improving vocational students’ English pronunciation. AsiaCALL Online Journal, 14(2), 140–155. https://doi.org/10.54855/acoj.231429 DOI: https://doi.org/10.54855/acoj.231429

Kaplan-Rakowski, R., & Grotewold, C. (2023). Exploring teacher attitudes toward AI-powered educational tools: A case study of Quillionz in the classroom. Journal of Educational Technology Research and Development, 71(2), 245-262. https://doi.org/10.1007/s11423-023-10123-4

Kaplan-Rakowski, R., Grotewold, K., Hartwick, P., & Papin, K. (2023). Generative AI and teachers' perspectives on its implementation in education. Journal of Interactive Learning Research, 34(2), 313-338. https://eric.ed.gov/?id=EJ1403113

Khan, S., Hamer, J., & Almeida, T. (2021). Generate: A NLG system for educational content creation. In EDM. https://finetunelearning.com/wp-content/uploads/2021/06/Generate_EDM2021.pdf

Klapwijk, N. M. (2012). Reading strategy instruction and teacher change: implications for teacher training. South African Journal of Education, 32(2), 191–204. https://doi.org/10.15700/saje.v32n2a618 DOI: https://doi.org/10.15700/saje.v32n2a618

Konar, A. (2018). Artificial intelligence and soft computing: behavioral and cognitive modeling of the human brain. CRC press.

Lelkes, A. D., Tran, V. Q., & Yu, C. (2021). Quiz-Style question generation for news stories. Proceedings of the Web Conference 2021, 2501–2511. https://doi.org/10.1145/3442381.3449892 DOI: https://doi.org/10.1145/3442381.3449892

Liang, J., Hwang, G., Chen, M. A., & Darmawansah, D. (2021). Roles and research foci of artificial intelligence in language education: an integrated bibliographic analysis and systematic review approach. Interactive Learning Environments, 31(7), 4270–4296. https://doi.org/10.1080/10494820.2021.1958348 DOI: https://doi.org/10.1080/10494820.2021.1958348

Marr, B. (2018). The key definitions of artificial intelligence (AI) that explain its importance. Forbes, 4(02), 2018. Retrieved from: https://www.forbes.com/sites/bernardmarr/2018/02/14/the-key-definitions-of-artificial-intelligence-ai-that-explain-its-importance/?sh=3d8b9c024f5d

McNulty, N. (2023). Exploring teachers’ perspectives on AI in the classroom. Niall McNulty. Retrieved from https://www.niallmcnulty.com

Nguyen, H. L., Le, D. H., Nguyen, T. L., & Duong, N. H. (2024). Students’ Perceptions towards AI Application in English Classes via The Language Hub System at a vocational College. In The 12th OpenTESOL International Conference 2024 Proceedings (pp. 196-210). https://opentesol.org/wp-content/uploads/2024/08/FINALIZED-PROCEEDINGS-OF-THE-12TH-OPENTESOL-INTERNATIONAL-HYBRID-CONFERENCE-2024-final.pdf

Nguyen, T. Q. Y. (2024). Unraveling the Potential of ChatGPT: Investigating the Efficacy of reading Text Adaptation. Proceedings of the AsiaCALL International Conference, 4, 159–169. https://doi.org/10.54855/paic.23412 DOI: https://doi.org/10.54855/paic.23412

Perrotta, C., & Selwyn, N. (2020). Deep learning goes to school: Towards a relational understanding of AI in education. Learning, Media and Technology, 45(3), 251-269. https://doi.org/10.1080/17439884.2020.1686017 DOI: https://doi.org/10.1080/17439884.2020.1686017

Pokrivcakova, S. (2019). Preparing teachers for the application of AI-powered technologies in foreign language education. Journal of Language and Cultural Education, 7(3), 135–153. https://doi.org/10.2478/jolace-2019-0025 DOI: https://doi.org/10.2478/jolace-2019-0025

Pretorius, E. J., & Machet, M. P. (2004). Literacy and disadvantage: learners’ achievements in the early primary school years. Africa Education Review, 1(1), 128–146. https://doi.org/10.1080/18146620408566274 DOI: https://doi.org/10.1080/18146620408566274

Ribeiro, R. (2020). Artificial Intelligence in English language learning. Cambridge.Org. https://www.cambridge.org//elt/blog/2020/03/09/artificialintelligence-english-language-learning/

Richards, J. C., & Rodgers, T. S. (2001). Approaches and methods in language teaching. Cambridge University Press. https://doi.org/10.1017/cbo9780511667305 DOI: https://doi.org/10.1017/CBO9780511667305

Rusmiyanto, R., Huriati, N., Fitriani, N., Tyas, N. K., Rofi’i, A., & Sari, M. N. (2023). The role of artificial intelligence (AI) in developing English language learner’s communication skills. Journal on Education, 6(1), 750–757. https://doi.org/10.31004/joe.v6i1.2990 DOI: https://doi.org/10.31004/joe.v6i1.2990

Russell, S. J., & Norvig, P. (2016). Artificial intelligence: a modern approach. Pearson.

Shin, M.-H. (2018). How to use artificial intelligence in the English language learning classroom. Indian Journal of Public Health Research & Development, 9(9), 557-561. https://doi.org/10.5958/0976-5506.2018.01058.6 DOI: https://doi.org/10.5958/0976-5506.2018.01058.6

Siyam, N., Abdallah, S., & Latif, Y. (2022). Acceptance of artificial intelligence among pre-service teachers: A multigroup analysis. International Journal of Educational Technology in Higher Education, 19(23), 1-21. https://doi.org/10.1186/s41239-022-00316-4

Wang, X., Wrede, S., van Rijn, L., & Wöhrle, J. (2023). AI-Based Quiz System For Personalised Learning. In ICERI2023 Proceedings (pp. 5025-5034). IATED. https://www.dfki.de/fileadmin/user_upload/import/14536_106756.pdf DOI: https://doi.org/10.21125/iceri.2023.1257

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Published

2024-11-01

How to Cite

Nguyen, T. L., Nguyen, H. L., & Le, D. H. (2024). Teachers’ Perspectives on AI-Driven Quillionz for Generating EFL Reading Comprehension Quizzes. Proceedings of the AsiaCALL International Conference, 6, 20–34. https://doi.org/10.54855/paic.2462

Issue

Vol. 6 (2024): Proceedings of the 21th AsiaCALL International Conference

Section

Research Article

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Copyright (c) 2024 Nguyen Thi Luong, Nguyen Hai Linh, Le Duc Hanh

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