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Enhancing Social Engagement among Online Learners' Using AI-Driven Tools: National Open University of Nigeria Leaners' Perspective

Ezeanya, Christiana Uchenna, Ukaigwe, Jane Ada, Ogbaga, Ignatius Nwoyibe, Kwanashie, Adako·2024·ABUAD Journal of Engineering Research and Development (AJERD)

Abstract

The need for online education has increased significantly. People now prefer to work to fulfill the necessities of life and pursue education to advance their skills because of the rising difficulty. This quest increases the demand for distance education thereby raising questions about how distance learning institutions can effectively assist their learners. Employment of Artificial Intelligence (AI) tools will not only provide solutions but also improve and render effective service and support to learners. AI-driven tools such as personalized or adaptive learning and chatbots for learner support have significantly helped to improve efficiency in virtual environments. This research aims to investigate how National Open University of Nigeria (NOUN) students view the contribution of AI tools in enhancing social interaction in their virtual learning environment. The study seeks to determine the requirements, inclinations, and challenges related to social interaction in the online learning space and explore how AI-powered solutions might effectively address these challenges to create a more dynamic and engaging learning environment. A survey was conducted to ascertain the level of awareness among the learners on the use of these tools, the challenges related to social interaction in online space and explore the ways AI-powered tools can effectively address issues in the learning environment to create a more dynamic and engaging learning environment. This study has identified that a greater number of learners in NOUN have little or no knowledge of the availability of these tools as well as how they can effectively use it. The level of awareness of the learners on the use of these tools is low. The study found 27.5% awareness and usage of AI tools provided by the institution. Several platforms were identified by respondents; however, ChatGPT was the most widely used AI platform. The study also discusses the importance of AI tools in enhancing collaboration and social engagement among learners. It identifies the challenges in integrating AI in Education and provides possible solutions to the challenges.

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Figure 1 Level of awareness of the available tools
Figure 1 Level of awareness of the available toolsCC-BY-NC-SA · From the PDF
Figure 2 AI driven tools identified by the learners
Figure 2 AI driven tools identified by the learnersCC-BY-NC-SA · From the PDF

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Research works printed but not linked: 27

  1. Ali, W. (2020). Online and remote learning in higher education institutes: A necessity in light of COVID-19 pandemic. Higher Education Studies, 10(3), 16–25. · DOI · Paper page
  2. Bello, L. K. (2021). Exploring the Capabilities of Online Facilitation to bridge the Instructional Gaps in Open and Distance Learning Delivery in Nigeria. Journal of Education and Practice, 12(3), 174–184.
  3. Alam, A., Mohanty, A. (2023). Facial Analytics or Virtual Avatars: Competencies and Design Considerations for Student-Teacher Interaction in AI-Powered Online Education for Effective Classroom Engagement. In: Tomar, R.S., et al. Communication, Networks and Computing. CNC 2022. Communications in Computer and Information Science, (1894). Springer, Cham. https://doi.org/10.1007/978-3-031-43145-6_21 · DOI
  4. Aggarwal, D. (2023). Integration of innovative technological developments and AI with education for an adaptive learning pedagogy. China Petroleum Processing and Petrochemical Technology, 23(2), 709-714.
  5. Raffaghelli, J. E., Foschi, L. C., Crudele, F., Doria, B., Grion, V., & Cecchinato, G. (2023). The ENCORE Approach. Pedagogy of an AI-driven system to integrate OER in Higher Education & VET. In ENCORE project results. https://hdl.handle.net/11577/3502320
  6. George, B., & Wooden, O. (2023). Managing the Strategic Transformation of Higher Education through Artificial Intelligence. In Administrative Sciences 13(9). https://doi.org/10.3390/admsci13090196 · DOI
  7. Kopus, T. L., Mikhalat, E. S., Belozerova, E. Y., & Meshcheryakova, O. V. (2021). Instructor presence in online teaching: challenges and opportunities. SHS Web of Conferences, 127(3002). · DOI
  8. Ezeanya, C. U., Onyeji, E. M. & Ejimofor, I. A. (2023), Enhanced Student Retention in Open and Distance Education through Effective Academic Performance Model using Naive Bayes and K-Nearest Neighbour Machine Learning Algorithm. Journal of Applied Sciences, Information and Computing. 4(2), https://doi.org/10.59568/JASIC-2023-4-2-04 · DOI
  9. Kaufmann, R., & Vallade, J. I. (2022). Maximizing the student experience: moving forward with online learning. Communication Education, 71(2), 152–154. · DOI
  10. Becker, T. B., Fenton, J. I., Nikolai, M., Comstock, S. S., Swada, J. G., Weatherspoon, L. J., & Tucker, R. M. (2022). The impact of COVID-19 on student learning during the transition from remote to in-person learning: using mind mapping to identify and address faculty concerns. Advances in Physiology Education, 46(4), 742–751. · DOI
  11. Gillett-Swan, J. (2017). The challenges of online learning: Supporting and engaging the isolated learner. Journal of Learning Design, 10(1), 20–30. · DOI
  12. Clark, C. E. J., & Post, G. (2021). Preparation and synchronous participation improve student performance in a blended learning experience. Australasian Journal of Educational Technology, 37(3), 187–199. · DOI
  13. Srinivasa, K. G., Kurni, M., & Saritha, K. (2022). Harnessing the Power of AI to Education. In Learning, Teaching, and Assessment Methods for Contemporary Learners: Pedagogy for the Digital Generation. 311–342. Springer. · DOI
  14. Brown, C., Czerniewicz, L., & Noakes, T. (2019). Online content creation: Looking at students’ social media practices through a connected learning lens. In Social Media and Education. 140-159. Routledge. · DOI
  15. Amelia, R., & Istianah, T. N. (2021). Teaching strategies: How do teachers in remote area survive during remote learning? ELT Forum: Journal of English Language Teaching, 10(2), 146–153. · DOI
  16. Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y.-S., Kay, J., Knight, S., Martinez-Maldonado, R., Sadiq, S., & Gašević, D. (2022). Explainable artificial intelligence in education. Computers and Education: Artificial Intelligence, 3, 100074. · DOI · Paper page
  17. Khan, R. A., Atta, K., Sajjad, M., & Jawaid, M. (2022). Twelve tips to enhance student engagement in synchronous online teaching and learning. Medical Teacher, 44(6), 601–606. · DOI
  18. Sundaresan, S., & Zhang, Z. (2022). AI-enabled knowledge sharing and learning: redesigning roles and processes. International Journal of Organizational Analysis, 30(4), 983–999. · DOI
  19. Gehred, A. P. (2020). Canva. Journal of the Medical Library Association, 108(2). https://doi.org/10.5195/jmla.2020.940 · DOI
  20. Ogbaga, I. N., Nweke, H. F., & Ndunagu, J. N. (2023). Deploying persuasive technology-based model in the prevention and control of malaria in Nigeria to reduce incidence of deaths. African Scientific Reports, (2)3, 130. · DOI
  21. Baha, T.A., Hajji, M.E., Es-saady, Y., & Fadili, H. (2023). The impact of educational chatbot on student learning experience. Educ. Inf. Technol., 29, 10153-10176. https://doi.org/10.1007/s10639-023-12166-w · DOI · Paper page
  22. Hoti, A., Zenuni, X., Hamiti, M., & Ajdari, J. (2023). Student Performance Prediction Using AI and ML: State of the Art. 2023 12th Mediterranean Conference on Embedded Computing (MECO), 1-6. https://doi.org/10.1109/MECO58584.2023.10154933 · DOI
  23. Rerhaye, L., Altun, D., Krauss, C., & Müller, C. (2021). Evaluation methods for an AI-supported learning management system: ok and qualifying added values for teaching and learning. International Conference on Human-Computer Interaction, 394–411. · DOI
  24. Teng, Y., Zhang, J., & Sun, T. (2023). Data‐driven decision‐making model based on artificial intelligence in higher education system of colleges and universities. Expert Systems, 40(4), e12820. · DOI
  25. James, T., Toth, G., Tomlins, M., Kumar, B., & Bond, K. (2021). Digital disruption in the COVID-19 Era: The impact on learning and students’ ability to cope with study in an unknown world. Student Success, 12(3), 84–95. · DOI
  26. Thacker, I., Seyranian, V., Madva, A., Duong, N. T., & Beardsley, P. (2022). Social connectedness in physical isolation: Online teaching practices that support under-represented undergraduate students’ feelings of belonging and engagement in STEM. Education Sciences, 12(2), 61 · DOI
  27. Ferri, F., Grifoni, P., & Guzzo, T. (2020). Online learning and emergency remote teaching: Opportunities and challenges in emergency situations. Societies, 10(4), 86. · DOI

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Metadata

Authors
Ezeanya, C. U., Ukaigwe, J. A., Ogbaga, I. N., & Kwanashie, A.
Venue
ABUAD Journal of Engineering Research and Development (AJERD)
Published
2024-07-16
Volume
7
Issue
2
Pages
78-85
ISSN
  • 2645-2685
  • 2756-6811
Cited by
6
References
4

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Ezeanya, C. U., Ukaigwe, J. A., Ogbaga, I. N., & Kwanashie, A. (2024). Enhancing Social Engagement among Online Learners' Using AI-Driven Tools: National Open University of Nigeria Leaners' Perspective. ABUAD Journal of Engineering Research and Development (AJERD). https://doi.org/10.53982/ajerd.2024.0702.08-j