Abstracts
Abstract
This study aimed to evaluate the utility of artificial intelligence (AI) in improving the persuasive communication skills of online Master of Business Administration (MBA) students. In particular, this study investigated the influence of personalization through AI using the Google Gemini platform on conventional and online instructional approaches. This quasi-experimental study used a pretest and posttest design to compare two groups of MBA students pursuing persuasive online communication. The experimental group (n = 32) interacted with the AI-based personalized learning materials, whereas the control group (n = 32) used standard instructor-designed online modules. During the 12-week intervention period, the experimental group was provided with customized practice activities. Conversely, the control group was offered conventional online learning material. The effectiveness of both approaches was evaluated using pretests and posttests. The results of Tukey’s Honestly Significant Difference (HSD) test provided insight into the areas where AI-based personalized learning had a statistically significant impact. These results support the conclusions derived from an analysis of variance and further validate the study’s research hypotheses. This study demonstrates the advantages of incorporating AI into language development for remote learners and offers valuable insights for integrating AI-driven technologies into distance education.
Keywords:
- learner agency,
- adaptive technology,
- micro-learning,
- disruptive innovation,
- distributed learning
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Appendices
Biographical notes
Sajida Bhanu is a dedicated research scholar in the English Department at the B.S. Abdur Rahman Crescent Institute of Science & Technology (BSACIST). Specializing in English Language Teaching (ELT) and speaking skills, Sajida's work focuses on innovative methods to enhance communicative competencies and pedagogical strategies within the realm of language education. Her research interests lie at the intersection of applied linguistics and technology-enhanced learning, aiming to bridge gaps in current ELT practices through empirical studies and theoretical insights.
Dr. S. Vijayakumar is an Associate Professor in the English Department at B.S. Abdur Rahman Crescent Institute of Science and Technology. His research interests encompass English Language Teaching (ELT), pedagogy, medical humanities, and Natural Language Processing (NLP). Dr. Vijayakumar's scholarly work is characterized by a commitment to enhancing educational practices through the integration of innovative pedagogical strategies and advanced technologies.
Bibliography
- Andrade, H. G. (2000). Using rubrics to promote thinking and learning. Educational Leadership, 57(5), 13–19.
- Chen, X., Zou, D., Cheng, G., & Xie, H. (2021, July 1). Artificial intelligence-assisted personalized language learning: Systematic review and co-citation analysis. In M. Chang, N.-S. Chen, D. G. Sampson, & A. Tlili (Eds.), Proceedings: IEEE 21st International Conference on Advanced Learning Technologies (ICALT) (pp. 241–245). https://doi.org/10.1109/ICALT52272.2021.00079
- Chiu, T. K. F., Moorhouse, B. L., Chai, C. S., & Ismailov, M. (2023, February 6). Teacher support and student motivation to learn with Artificial Intelligence (AI) based chatbots. Interactive Learning Environments, 1–17. https://doi.org/10.1080/10494820.2023.2172044
- Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, Article 100118. https://doi.org/10.1016/j.caeai.2022.100118
- Crawford, J., Cowling, M., & Allen, K.-A. (2023). Leadership is needed for ethical ChatGPT: Character assessment and learning using artificial intelligence (AI). Journal of University Teaching & Learning Practice, 20(3), Article 02. https://doi.org/10.53761/1.20.3.02
- Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20(1), Article 22. https://doi.org/10.1186/s41239-023-00392-8
- DiBenedetto, M. K., & Bembenutty, H. (2011). Differences between full-time and part-time MBA students’ self-efficacy for learning and for employment: A self-regulatory perspective. The International Journal of Educational and Psychological Assessment, 7(1), 81–110. https://www.researchgate.net/publication/281466153_Differences_between_full-time_and_part-time_MBA_students'_self-efficacy_for_learning_and_for_employment_A_self-regulatory_perspective
- Francis, R. (2012). Business communication courses in the MBA curriculum: A reality check (Corpus ID: 56263598). Semantic Scholar. https://www.semanticscholar.org/paper/Business-Communication-Courses-in-the-MBA-A-Reality-Francis/ebc9594a269889c3c14e91edd8d075c52676fd6b
- Huang, X., Zou, D., Cheng, G., Chen, X., & Xie, H. (2023). Trends, research issues and applications of artificial intelligence in language education. Educational Technology & Society, 26(1), 112–131. https://www.jstor.org/stable/48707971
- Istenič, A. (2021). Online learning under COVID-19: Re-examining the prominence of video-based and text-based feedback. Educational Technology Research and Development, 69(1), 117–121. https://doi.org/10.1007/s11423-021-09955-w
- Jadhav, S. V., Shinde, S. R., Dalal, D. K., Deshpande, T. M., Dhakne, A. S., & Gaherwar, Y. M. (2023). Improve communication skills using AI. In P. B. Mane & A. R. Buchade (Chairs), Proceedings of the 2023 International Conference on Emerging Smart Computing and Informatics (ESCI) (pp. 1–5). IEEE. https://doi.org/10.1109/ESCI56872.2023.10099941
- Liang, J.-C., Hwang, G.-J., Chen, M.-R. 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
- Liu, C., Hou, J., Tu, Y.-F., Wang, Y., & Hwang, G.-J. (2021). Incorporating reflective thinking promoting mechanism into artificial intelligence-supported English writing environments. Interactive Learning Environments, 31(9), 5614–5632. https://doi.org/10.1080/10494820.2021.2012812
- Long, S., & McLaren, M.-R. (2024). Belonging in remote higher education classrooms: The dynamic interaction of intensive modes of learning and arts-based pedagogies. Journal of University Teaching and Learning Practice, 21(2), Article 03. https://doi.org/10.53761/1.21.2.03
- Lund, B. D., Wang, T., Mannuru, N. R., Nie, B., Shimray, S., & Wang, Z. (2023). ChatGPT and a new academic reality: Artificial Intelligence‐written research papers and the ethics of the large language models in scholarly publishing. Journal of the Association for Information Science and Technology, 74(5), 570–581. https://doi.org/10.1002/asi.24750
- Maghsudi, S., Lan, A., Xu, J., & van der Schaar, M. (2021). Personalized education in the artificial intelligence era: What to expect next. IEEE Signal Processing Magazine, 38(3), 37–50. https://doi.org/10.1109/msp.2021.3055032
- McGraw, P., & Tidwell, A. (2001). Teaching group process skills to MBA students: A short workshop. Education + Training, 43(3), 162–171. https://doi.org/10.1108/EUM0000000005461
- Moskal, B. M. (2000). Scoring rubrics: What, when, and how? Practical Assessment, Research, and Evaluation, 7(3). https://doi.org/10.7275/a5vq-7q66
- Obari, H., Lambacher, S., & Kikuchi, H. (2020). The impact of using AI and VR with blended learning on English as a foreign language teaching. In F. Karen-Margrete, L. Sanne, B. Linda, & T. Sylvie (Eds.), CALL for widening participation: Short papers from EUROCALL 2020 (pp. 253–258). Research-publishing.net. https://doi.org/10.14705/rpnet.2020.48.1197
- Ongus, R. W., Gekara, M. M., & Nyamboga, C. M. (2017). Library and information service provision to part-time postgraduate students: A case study of Jomo Kenyatta Memorial Library, University of Nairobi, Kenya. Journal of Information and Knowledge, 54(1), 1–17. https://doi.org/10.17821/srels/2017/v54i1/108529
- Paterson, C., Paterson, N., Jackson, W., & Work, F. (2020). What are students’ needs and preferences for academic feedback in higher education? A systematic review. Nurse Education Today, 85, Article 104236. https://doi.org/10.1016/j.nedt.2019.104236
- Palincsar, A. S., & Herrenkohl, L. R. (2002). Designing collaborative learning contexts. Theory Into Practice, 41(1), 26–32. https://doi.org/10.1207/s15430421tip4101_5
- Randolph, W. A. (2008). Educating part-time MBAs for the global business environment. Journal of College Teaching & Learning (TLC), 5(8). https://doi.org/10.19030/tlc.v5i8.1236
- Sánchez-Villalon, P. P. S., & Ortega, M. (2007). AWLA and AIOLE for personal learning environments. International Journal of Continuing Engineering Education and Life-Long Learning, 17(6), 418–431. https://doi.org/10.1504/IJCEELL.2007.015591
- Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin.
- Shevchenko, V., Malysh, N., & Tkachuk-Miroshnychenko, O. (2021). Distance learning in Ukraine in COVID-19 emergency. Open Learning: The Journal of Open, Distance and E-Learning, 39(1), 4–19. https://doi.org/10.1080/02680513.2021.1967115
- Suen, H.-Y., Hung, K.-E., & Lin, C.-L. (2020). Intelligent video interview agents used to predict communication skill and perceived personality traits. Human-Centric Computing and Information Sciences, 10(1), Article 3. https://doi.org/10.1186/s13673-020-0208-3
- Tomasik, M. J., Helbling, L. A., & Moser, U. (2020). Educational gains of in‐person vs. distance learning in primary and secondary schools: A natural experiment during the COVID-19 pandemic school closures in Switzerland. International Journal of Psychology, 56(4), 566–576. https://doi.org/10.1002/ijop.12728
- Wang, J., & Mendori, T. (2012). A customizable language learning support system using course-centered ontology and teaching method ontology. In T. Matsuo, K. Hashimoto, & S. Hirokawa (Eds.), 2012 IIAI International Conference on Advanced Applied Informatics (pp. 149–152). IEEE. https://doi.org/10.1109/IIAI-AAI.2012.38
- Wang, X., Liu, Q., Pang, H., Tan, S. C., Lei, J., Wallace, M. P., & Li, L. (2023). What matters in AI-supported learning: A study of human-AI interactions in language learning using cluster analysis and epistemic network analysis. Computers & Education, 194, Article 104703. https://doi.org/10.1016/j.compedu.2022.104703
- Zhao, X. (2022). Leveraging artificial intelligence (AI) technology for English writing: Introducing Wordtune as a digital writing assistant for EFL writers. RELC Journal, 54(3), 890–894. https://doi.org/10.1177/00336882221094089