ARCHIVES
Year 2026 · Volume 6 · Issue 5
Original Article
Leveraging ICT tools to Enhance under Graduate students’ Presentation Skills
M. Suresh1
Dr. Rahamat Shaikh2
1 Research Scholar, Department of English, Pallavi Engineering College, Hyderabad, Telangana, India. 2 Professor & Research Supervisor, Department of English, VFSTR, Guntur, Andhra Pradesh, India.
Published Online: September-October 2026
Pages: 48-57
Cite this article
↗ https://www.doi.org/10.59256/ijrtmr.20260605006
References
1. Hwang, G. J., & Tu, Y. F. (2023). Roles and research trends of artificial intelligence in language education: An integrated bibliographic
analysis and systematic review approach. Educational Technology Research and Development, 71(5), 1895–1914.
https://doi.org/10.1007/s11423-023-10215-7
2. De Grez, L., Valcke, M., & Roozen, I. (2009). The impact of goal orientation, self-reflection and personal characteristics on the acquisition
of oral presentation skills. European Journal of Psychology of Education, 24(3), 293–306. https://doi.org/10.1007/BF03174762
3. Haseski. H.I. (2019). What do Turkish pre-service teachers think about artificial intelligence? International Journal of Computer Science
Education in Schools, 3(2), Doi: 10.21585/ijcses.v3i2.55
4. Carless, David, and David Boud. 2018. “The Development of Student Feedback Literacy: enabling uptake of Feedback.”Assessment &
Evaluation in Higher Education 43 (8): 1315–1325. doi:10.1080/02602938.2018.1463354.
5. Yim, S. Y. (2014). An anxiety model for EFL young learners: A path analysis. System, 42(1), 344–354.
https://doi.org/10.1016/j.system.2013.12.022
6. Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, beliefs, and culture intersect. Journal
of Research on Technology in Education, 42(3), 255–284.
7. Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance.
Psychological Review, 100(3), 363–406.
8. Schindler, L. A., Burkholder, G. J., Morad, O. A., & Marsh, C. (2017). Computer-based technology and student engagement: A critical
review of the literature. International Journal of Educational Technology in Higher Education, 14(1), 25.
9. Li, J., Link, S., & Hegelheimer, V. (2015). Rethinking the role of automated writing evaluation in ESL writing instruction. Journal of
Second Language Writing, 27, 1–18.
10. Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112.
11. Alam, T. H. I., & Windiarti, I. S. (2025). The future of artificial intelligence in interactive learning: Trends, challenges, opportunities.
Engineering Proceedings, 84, 87. https://doi.org/10.3390/engproc2025084087
12. Redecker, C., & Punie, Y. (2023). Digital competence frameworks and AI-supported communication skills in higher education. European
Journal of Education, 58(4), 456–472. https://doi.org/10.1111/ejed.12547
13. Mishra, P., & Koehler, M. J. (2024). Reimagining digital pedagogy in the age of artificial intelligence. Journal of Educational Computing
Research, 62(3), 789–808. https://doi.org/10.1177/0735633124123456
14. Lopez, A., Martins, P., & Silva, R. (2025). Immersive virtual environments for communication skills development in higher education.
Smart Learning Environments, 12, 14. https://doi.org/10.1186/s40561-025-00278-6
15. Chen, L., & Huang, R. (2023). Artificial intelligence–based speech evaluation systems for improving oral presentation skills. Education
and Information Technologies, 28(9), 11245–11263. https://doi.org/10.1007/s10639-023-11845-216. A. Baboo, S. R. Mishra and S. Dash, "An Improvised Diabetes Prediction System Using Hybrid Ensemble Approach," 2024 IEEE 11th
Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), Lucknow, India, 2024,
pp. 1-6, doi: 10.1109/UPCON62832.2024.10983076.
17. A. Baboo, S. Prasad Patro and S. Dash, "A Deep Learning Approach for Enhancing Cardiovascular Disease Prediction Using ECG
Data," 2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES),
Paralakhemundi Campus, Centurion University of Technology and Management, Odisha., India, 2024, pp. 1-5, doi:
10.1109/SCOPES64467.2024.10990827.
18. S. Ranjan Mishra, S. Dash and L. Rath, "Effective Diabetes Mellitus Prediction Using a Hybrid Ensemble Machine Learning Model with
Iot," 2024 International Conference on Integrated Intelligence and Communication Systems (ICIICS), Kalaburagi, India, 2024, pp. 1-8,
doi: 10.1109/ICIICS63763.2024.10859778.
19. V. S. K. Chaitanya, D. Rakesh, S. Dash, B. K. Sahoo, S. Padhy and M. Nayak, "Tomato Leaf Disease Detection using Neural Networks,"
2022 International Conference on Machine Learning, Computer Systems and Security (MLCSS), Bhubaneswar, India, 2022, pp. 53-58,
doi: 10.1109/MLCSS57186.2022.00018.
20. R. Hota, S. Dash, S. Mishra, S. Pradhan, P. K. Pattnaik and G. Pradhan, "Prediction and Diagnosis of Thoracic Diseases using Rough Set
and Machine Learning," 2023 10th International Conference on Computing for Sustainable Global Development (INDIACom), New
Delhi, India, 2023, pp. 206-213.
21. S. Mohanty, J. Mishra, S. K. Mohapatra, S. Dash, S. Padhy and S. K. Das, "Generating Higher Order Mutants using PSO with Levy
Flight(LFPSO) Algorithm," 2022 International Conference on Machine Learning, Computer Systems and Security (MLCSS),
Bhubaneswar, India, 2022, pp. 75-79, doi: 10.1109/MLCSS57186.2022.00022. IEEE
22. Dash S., Das R.K., Guha S., Bhagat S.N., Behera G.K. (2021) An Interactive Machine Learning Approach for Brain Tumor MRI
Segmentation. In: Das S., Mohanty M.N. (eds) Advances in Intelligent Computing and Communication. Lecture Notes in Networks and
Systems, vol 202. Springer, Singapore. https://doi.org/10.1007/978-981-16-0695-3_38
23. Mohanty, S., Gantayat, P. K., Dash, S., Mishra, B. P., & Barik, S. C. (2021). Liver Disease Prediction Using Machine Learning Algorithm.
In Data Engineering and Intelligent Computing: Proceedings of ICICC 2020 (pp. 589-596). Springer Singapore. doi:10.1007/978-981-16-
0171-2
24. S. Dutta, S. Dash, and A. Mitra, “A Model of Socially Connected Things for Emotion Detection,” in 2020 International Conference on
Computer Science, Engineering and Applications (ICCSEA), Mar. 2020, pp. 1–3, doi: 10.1109/ICCSEA49143.2020.9132887.
https://ieeexplore.ieee.org/document/9132887
25. Dash, S., & Das, R. K. (2020). An implementation of neural network approach for recognition of handwritten Odia text. In Advances in
Intelligent Computing and Communication: Proceedings of ICAC 2019 (pp. 94-99). Springer Singapore.
analysis and systematic review approach. Educational Technology Research and Development, 71(5), 1895–1914.
https://doi.org/10.1007/s11423-023-10215-7
2. De Grez, L., Valcke, M., & Roozen, I. (2009). The impact of goal orientation, self-reflection and personal characteristics on the acquisition
of oral presentation skills. European Journal of Psychology of Education, 24(3), 293–306. https://doi.org/10.1007/BF03174762
3. Haseski. H.I. (2019). What do Turkish pre-service teachers think about artificial intelligence? International Journal of Computer Science
Education in Schools, 3(2), Doi: 10.21585/ijcses.v3i2.55
4. Carless, David, and David Boud. 2018. “The Development of Student Feedback Literacy: enabling uptake of Feedback.”Assessment &
Evaluation in Higher Education 43 (8): 1315–1325. doi:10.1080/02602938.2018.1463354.
5. Yim, S. Y. (2014). An anxiety model for EFL young learners: A path analysis. System, 42(1), 344–354.
https://doi.org/10.1016/j.system.2013.12.022
6. Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, beliefs, and culture intersect. Journal
of Research on Technology in Education, 42(3), 255–284.
7. Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance.
Psychological Review, 100(3), 363–406.
8. Schindler, L. A., Burkholder, G. J., Morad, O. A., & Marsh, C. (2017). Computer-based technology and student engagement: A critical
review of the literature. International Journal of Educational Technology in Higher Education, 14(1), 25.
9. Li, J., Link, S., & Hegelheimer, V. (2015). Rethinking the role of automated writing evaluation in ESL writing instruction. Journal of
Second Language Writing, 27, 1–18.
10. Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112.
11. Alam, T. H. I., & Windiarti, I. S. (2025). The future of artificial intelligence in interactive learning: Trends, challenges, opportunities.
Engineering Proceedings, 84, 87. https://doi.org/10.3390/engproc2025084087
12. Redecker, C., & Punie, Y. (2023). Digital competence frameworks and AI-supported communication skills in higher education. European
Journal of Education, 58(4), 456–472. https://doi.org/10.1111/ejed.12547
13. Mishra, P., & Koehler, M. J. (2024). Reimagining digital pedagogy in the age of artificial intelligence. Journal of Educational Computing
Research, 62(3), 789–808. https://doi.org/10.1177/0735633124123456
14. Lopez, A., Martins, P., & Silva, R. (2025). Immersive virtual environments for communication skills development in higher education.
Smart Learning Environments, 12, 14. https://doi.org/10.1186/s40561-025-00278-6
15. Chen, L., & Huang, R. (2023). Artificial intelligence–based speech evaluation systems for improving oral presentation skills. Education
and Information Technologies, 28(9), 11245–11263. https://doi.org/10.1007/s10639-023-11845-216. A. Baboo, S. R. Mishra and S. Dash, "An Improvised Diabetes Prediction System Using Hybrid Ensemble Approach," 2024 IEEE 11th
Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), Lucknow, India, 2024,
pp. 1-6, doi: 10.1109/UPCON62832.2024.10983076.
17. A. Baboo, S. Prasad Patro and S. Dash, "A Deep Learning Approach for Enhancing Cardiovascular Disease Prediction Using ECG
Data," 2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES),
Paralakhemundi Campus, Centurion University of Technology and Management, Odisha., India, 2024, pp. 1-5, doi:
10.1109/SCOPES64467.2024.10990827.
18. S. Ranjan Mishra, S. Dash and L. Rath, "Effective Diabetes Mellitus Prediction Using a Hybrid Ensemble Machine Learning Model with
Iot," 2024 International Conference on Integrated Intelligence and Communication Systems (ICIICS), Kalaburagi, India, 2024, pp. 1-8,
doi: 10.1109/ICIICS63763.2024.10859778.
19. V. S. K. Chaitanya, D. Rakesh, S. Dash, B. K. Sahoo, S. Padhy and M. Nayak, "Tomato Leaf Disease Detection using Neural Networks,"
2022 International Conference on Machine Learning, Computer Systems and Security (MLCSS), Bhubaneswar, India, 2022, pp. 53-58,
doi: 10.1109/MLCSS57186.2022.00018.
20. R. Hota, S. Dash, S. Mishra, S. Pradhan, P. K. Pattnaik and G. Pradhan, "Prediction and Diagnosis of Thoracic Diseases using Rough Set
and Machine Learning," 2023 10th International Conference on Computing for Sustainable Global Development (INDIACom), New
Delhi, India, 2023, pp. 206-213.
21. S. Mohanty, J. Mishra, S. K. Mohapatra, S. Dash, S. Padhy and S. K. Das, "Generating Higher Order Mutants using PSO with Levy
Flight(LFPSO) Algorithm," 2022 International Conference on Machine Learning, Computer Systems and Security (MLCSS),
Bhubaneswar, India, 2022, pp. 75-79, doi: 10.1109/MLCSS57186.2022.00022. IEEE
22. Dash S., Das R.K., Guha S., Bhagat S.N., Behera G.K. (2021) An Interactive Machine Learning Approach for Brain Tumor MRI
Segmentation. In: Das S., Mohanty M.N. (eds) Advances in Intelligent Computing and Communication. Lecture Notes in Networks and
Systems, vol 202. Springer, Singapore. https://doi.org/10.1007/978-981-16-0695-3_38
23. Mohanty, S., Gantayat, P. K., Dash, S., Mishra, B. P., & Barik, S. C. (2021). Liver Disease Prediction Using Machine Learning Algorithm.
In Data Engineering and Intelligent Computing: Proceedings of ICICC 2020 (pp. 589-596). Springer Singapore. doi:10.1007/978-981-16-
0171-2
24. S. Dutta, S. Dash, and A. Mitra, “A Model of Socially Connected Things for Emotion Detection,” in 2020 International Conference on
Computer Science, Engineering and Applications (ICCSEA), Mar. 2020, pp. 1–3, doi: 10.1109/ICCSEA49143.2020.9132887.
https://ieeexplore.ieee.org/document/9132887
25. Dash, S., & Das, R. K. (2020). An implementation of neural network approach for recognition of handwritten Odia text. In Advances in
Intelligent Computing and Communication: Proceedings of ICAC 2019 (pp. 94-99). Springer Singapore.
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