Exploring Sudanese Faculty Members' Perceptions of AI Tools in Enhancing Speaking Skills
DOI:
https://doi.org/10.59675/S321Keywords:
AI tools, speaking skills, language education, Sudanese faculty, higher education, personalized learning, teacher trainingAbstract
This study investigates the perceptions of 93 Sudanese faculty members (51 female, 42 male) at Central Governmental Universities in Khartoum regarding the use of Artificial Intelligence (AI) tools to improve students' speaking skills. Utilizing a quantitative approach through online questionnaires, the research identifies both the advantages and obstacles associated with integrating AI into language instruction. Findings reveal that while most faculty members view AI tools positively, especially for promoting interactivity, individualized learning, and real-time feedback there remain challenges related to training needs and infrastructural limitations. The paper concludes with actionable recommendations for effective AI integration in higher education settings in Sudan.
References
Akbari, J. (2018). Enriching speaking fluency through conversational gambits and routines among Iranian intermediate EFL learners. International Journal of Research in English Education, 3(1), 35–43. https://doi.org/10.29252/IJREE.3.1.35
Chen, X., & Yang, Y. (2024). Exploring EFL learners’ technology acceptance in online learning in collaborative education programs. Journal of Education, Teaching and Social Studies, 6(2), 195. https://doi.org/10.22158/jetss.v6n2p195
Chisega-Negrilă, A.M. (2023). The new revolution in language learning: The power of artificial intelligence and Education 4.0. Bulletin of “Carol I” National Defense University, 12(2), 16–27. https://doi.org/10.53477/2284-9378-23-17
Daweli, T.W., & Mahoub, R.A.M. (2024). Exploring EFL learners’ perspectives on using AI tools and their impacts in reading instruction: An exploratory study. Arab World English Journal, 160–171. https://doi.org/10.24093/awej/call10.11
Deshmukh, S.P. (2024). Factors influencing English speaking fluency among second language learners. Educational Administration: Theory and Practice, 30(5), 6410–6414. https://doi.org/10.53555/kuey.v30i5.3951
Fathi, J., Rahimi, M., & Derakhshan, A. (2024). Improving EFL learners’ speaking skills and willingness to communicate via artificial intelligence-mediated interactions. System, 121, 103254. https://doi.org/10.1016/j.system.2024.103254
Graesser, A.C., Li, H., & Forsyth, C. (2014). Learning by communicating in natural language with conversational agents. Current Directions in Psychological Science, 23(5), 374–380. https://doi.org/10.1177/0963721414540680
Hill, J., Ford, W.R., & Farreras, I.G. (2015). Real conversations with artificial intelligence: A comparison between human-human online conversations and human–chatbot conversations. Computers in Human Behavior, 49, 245–250. https://doi.org/10.1016/j.chb.2015.02.026
Junaidi, J. (2020). Artificial intelligence in EFL context: Rising students’ speaking performance with Lyra virtual assistance. International Journal of Advanced Science and Technology, 29(5), 6735–6741.
Kang, H. (2022). Effects of artificial intelligence (AI) and native speaker interlocutors on ESL learners’ speaking ability and affective aspects. Multimedia-Assisted Language Learning, 25(2), 9–43.
Kovalenko, I., & Baranivska, N. (2024). Integrating artificial intelligence in English language teaching: Exploring the potential and challenges of AI tools in enhancing language learning outcomes and personalized education. Journal of Language & Education, 2024(1), 86–95. https://doi.org/10.61345/2734-8873.2024.1.9
Mahmoud, R.H. (2022). Implementing AI-based conversational chatbots in EFL speaking classes: An evolutionary perspective. https://doi.org/10.21203/rs.3.rs-1911791/v1
Massaro, D.W., Liu, Y., & Chen, T.H. (2006). A multilingual embodied conversational agent for tutoring speech and language learning. Proceedings of the Ninth International Conference on Spoken Language Processing (Interspeech 2006–ICSLP), Universität Bonn, Germany, 17–21 September, pp. 825–828.
Michot, J., Hürlimann, M., Deriu, J., et al. (2024). Error-preserving automatic speech recognition of young English learners’ language. https://doi.org/10.48550/arxiv.2406.03235
Monica, M. (2022). Enhancing EFL undergraduate students’ speaking fluency through chunking
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Academic International Journal of Social Sciences and Humanities

This work is licensed under a Creative Commons Attribution 4.0 International License.
