Using Artificial Intelligence in Online Learning Environments for Positive Student Outcomes: A Scoping Review
DOI:
https://doi.org/10.21649/akemu.v31iSpl2.5811Keywords:
Artificial Intelligence, Online education, Student OutcomesAbstract
With advancing technologies and advances in online learning, the potential of Artificial Intelligence (AI) tools to revolutionize education is undeniable. This scoping review aims to explore the roles that AI can play in online learning environments in higher education. Utilizing the revised Arksey and O’Malley protocol we identified 24 roles and 47 subroles that enhance learning in digital cyberspace. AI technologies using machine learning, natural linguistic processing and predictive analysis can enable cognitive skill development, provide personalized learning and undertake efficient content curation for the learners. These applications are supported by five identified AI Attributes- responsiveness, adaptability, predictiveness, proactiveness and decisiveness, each contributing to an interactive learning environment. By leveraging these attributes, educators and administrators can create data-driven, adaptive learning frameworks that improve student engagement and performance in online platforms. This scoping review consolidates existing research and provides a structured analysis of functions where AI can be used in education. Findings highlight AI’s potential to not only enhance accessibility but also optimize learning outcomes through intelligent automation and personalized learning.
References
1. Bates T, Cobo C, Mariño O, Wheeler S. Can artificial intelligence transform higher education? Int J Educ Technol High Educ. 2020;17(1):1-12. https://doi.org/10.1186/s41239-020-00218-x.
2. Han ER, Yeo S, Kim MJ, Lee YH, Park KH, Roh H. Medical education trends for future physicians in the era of advanced technology and artificial intelligence: An integrative review. BMC Med Educ. 2019;46(1):460.
3. Nalli G, Amendola D, Smith S. Artificial Intelligence to improve learning outcomes through online collaborative activities. European Conference on e-Learning. 2022;21(1):475–9.
4. Wang T, Lund BD, Marengo A, Pagano A, Mannuru NR, Teel ZA, et al. Exploring the Potential Impact of Artificial Intelligence (AI) on International Students in Higher Education: Generative AI, Chatbots, Analytics, and International Student Success. Appl Sci.2023;13(11):6716. https://doi.org/10.3390/app13116716.
5. Naeem N i K, Yusoff MSB, Hadie SNH, Ismail IM, Iqbal H. Understanding the Functional Components of Technology-Enhanced Learning Environment in Medical Education: A Scoping Review. Med Sci Educ. 2023;33(1):1-15.
https://doi.org/10.1007/s40670-023-01747-6
6. Arksey H, O’Malley L. Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology: Theory and Practice. 2005;8(1):19–32.
7. Braun V, Clarke V, Hayfield N, Terry G. Thematic analysis. In: Handbook of Research Methods in Health Social Sciences. Springer, Singapore. 2019:843-60. https://doi.org/10.1007/978-981-10-5251-4_103.
8. Marghany Mahmoud Marghany A. Using artificial intelligence-based instruction to develop EFL higher education students’ essay writing skills. CDELT Occas Pap Dev Engl Educ. 2023;82(1):219–40.
9. Leung ACM, Santhanam R, Kwok RCW, Yue WT. Could Gamification Designs Enhance Online Learning Through Personalization? Lessons from a Field Experiment. Inf Syst Res. 2023;34(1):27–49. https://doi.org/10.1287/isre.2022.1123
10. Jin SH, Im K, Yoo M, Roll I, Seo K. Supporting students’ self-regulated learning in online learning using artificial intelligence applications. Int J Educ Technol High Educ. 2023;20(1):1–21.
11. Tapalova O, Zhiyenbayeva N. Artificial Intelligence in Education: AIEd for Personalised Learning Pathways. EJEL. 2022;20(5):639–53. https://doi.org/10.34190/ejel.20.5.2597
12. Al A, Ahmed A. Creation of Automated Content With Embedded Artificial Intelligence A Study on Learning Management System for Educational Entrepreneurship. Acad Entrep J. 2021;27(3):1–10.
13. Ramos De Melo F, Flôres EL, Diniz De Carvalho S, Gonçalves De Teixeira RA, Batista Loja LF, De Sousa Gomide R. Computational organization of didactic contents for personalized virtual learning environments. Comput Educ. 2014;79:126–37.
14. Perez-Ortiz M, Dormann C, Rogers Y, Bulathwela S, Kreitmayer S, Yilmaz E, et al. X5Learn: A Personalised Learning Companion at the Intersection of AI and HCI. International Conference on Intelligent User Interfaces, Proceedings IUI . 2021;70–4. https://dl.acm.org/doi/10.1145/3397482.3450721
15. Bucea-Manea-țoniş R, Kuleto V, Gudei SCD, Lianu C, Lianu C, Ilić MP, et al. Artificial Intelligence Potential in Higher Education Institutions Enhanced Learning Environment in Romania and Serbia. Sustainability. 2022;14(10):5842.
16. Rodríguez ME, Guerrero-Roldán AE, Baneres D, Karadeniz A. An Intelligent Nudging System to Guide Online Learners. IRRODL. 2022;23(1):41–62.
17. Albright J, Fidas CA, Belk M, Constantinides A, Portugal D, Martins P, et al. Ensuring Academic Integrity and Trust in Online Learning Environments: A Longitudinal Study of an AI-Centered Proctoring System in Tertiary Educational Institutions. Educ Sci. 2023;13(6):566.
18. Giannakos MN, Chorianopoulos K, Chrisochoides N. Making Sense of Video Analytics: Lessons Learned from Clickstream Interactions, Attitudes, and Learning Outcome in a Video-Assisted Course. IRRODL. 2015;16(1):260–83.
19. Toribio NF. Analysis Of Chatgpt And Other AI’s Ability To Reduce Anxiety Of Science-Oriented Learners In Academic Engagements. J Namib Stud: History Politics Culture. 2023;33(1):5320–37. https://doi.org/10.59670/jns.v33i.3132
20. Luckin R, Cukurova M, Kent C, du Boulay B. Empowering educators to be AI-ready. Computers and Education: AI. 2022 ;3(1):100076.
21. Stoll A, Ziegele M, Quiring O. Detecting impoliteness and incivility in online discussions: Classification approaches for german user comments. Comput Commun Res. 2020;2(1):109–34. https://doi.org/10.5117/CCR2020.1.005.KATH.
22. Al-Abdullatif AM, Al-Dokhny AA, Drwish AM. Implementing the Bashayer chatbot in Saudi higher education: measuring the influence on students’ motivation and learning strategies. Front Psychol. 2023;14(1): 1129070. https://doi.org/10.3389/fpsyg.2023.1129070.
23. Chandel S, Yuying Y, Yujie G, Razaque A, Yang G. Chatbot: Efficient and utility-based platform. Advances in Intelligent Systems and Computing. Springer International Publishing. 2019 ;858(1):109–22.
24. Ahmed T, Bulathwela S. Towards Proactive Information Retrieval in Noisy Text with Wikipedia Concepts. CEUR Workshop Proc. 2022;3318(1).
https://doi.org/10.48550/arXiv.2210.09877.
25. Noriega P, Verhagen H, Padget J, D’Inverno M. Ethical Online AI Systems through Conscientious Design. IEEE Internet Comput. 2021;25(6):58–64.
26. Bañeres D, Rodríguez ME, Guerrero-Roldán AE, Karadeniz A. An Early Warning System to Detect At-Risk Students in Online Higher Education. Appl Sci. 2020;10(13):4427. https://doi.org/10.3390/app10134427.
27. Seo K, Tang J, Roll I, Fels S, Yoon D. The impact of artificial intelligence on learner–instructor interaction in online learning. Int J Educ Technol High Educ. 2021;18(1):54.
28. Kim JH, Kim M, Kwak DW, Lee S. Home-Tutoring Services Assisted with Technology: Investigating the Role of Artificial Intelligence Using a Randomized Field Experiment. J Mark Res. 2022;59(1):79–96.
29. Wang Q, Jing S, Goel AK. Co-Designing AI Agents to Support Social Connectedness Among Online Learners: Functionalities, Social Characteristics, and Ethical Challenges. DIS 2022 - Proceedings of the 2022 ACM Designing Interactive Systems Conference: Digital Wellbeing. 2022;13:541–56.
30. Kim J, Merrill K, Xu K, Kelly S. Perceived credibility of an AI instructor in online education: The role of social presence and voice features. Comput Human Behav. 2022;136(1):107383.
31. Bennani S, Maalel A, Ben Ghezala H. Adaptive gamification in E-learning: A literature review and future challenges. Comput Appl Eng Educ.2022:30(2):628–42. https://doi.org/10.1002/cae.22477.
32. Kaswan KS, Dhatterwal JS, Ojha RP. AI in personalized learning. In: Advances in Technological Innovations in Higher Education: Theory and Practices. 2024:14(1)103–17.
33. Minn S, Vie JJ, Takeuchi K, Kashima H, Zhu F. Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations. Proceedings of the AAAI Conference on Artificial Intelligence. 2022;36(11):12810–8.
34. Shu X, Gu X. An Empirical Study of A Smart Education Model Enabled by the Edu-Metaverse to Enhance Better Learning Outcomes for Students. Systems .2023;11(2):75. https://doi.org/10.3390/systems11020075.
35. Van der Niet AG, Bleakley A. Where medical education meets artificial intelligence: ‘Does technology care?’ Med Educ. 2021;55(1):30-6.
36. Gunness A, Matanda MJ, Rajaguru R. Effect of student responsiveness to instructional innovation on student engagement in semi-synchronous online learning environments: The mediating role of personal technological innovativeness and perceived usefulness. Comput Educ. 2023;205(1):104884.
37. Kang J, Kang C, Yoon J, Ji H, Li T, Moon H, et al. Dancing on the inside: A qualitative study on online dance learning with teacher-AI cooperation. Educ Inf Technol (Dordr).2023;28(9):12111–41.
38. Li S, Du J, Yu S. Diversified resource access paths in MOOCs: Insights from network analysis. Comput Educ. 2023; 204(1); 104869.
39. Chang YS, Wang YY, Ku Y Te. Influence of online STEAM hands-on learning on AI learning, creativity, and creative emotions. Interact Learn Environ. 2023;32 (8):4719-38
Available from: https://www.tandfonline.com/doi/abs/10.1080/10494820.2023.2205898
40. Wingström R, Hautala J, Lundman R. Redefining Creativity in the Era of AI? Perspectives of Computer Scientists and New Media Artists. Creat Res J. 2022; 36(2), 177–93. https://doi.org/10.1080/10400419.2022.2107850
41. Bearman M, Ajjawi R. Learning to work with the black box: Pedagogy for a world with artificial intelligence. Br J Educ Technol. 2023;54(5):1160–73.
42. Gunness A, Matanda MJ, Rajaguru R. Effect of student responsiveness to instructional innovation on student engagement in semi-synchronous online learning environments: The mediating role of personal technological innovativeness and perceived usefulness. Comput Educ. 2023;205(1):104884.
43. Liu B, Gui W, Gao T, Wu Y, Zuo M. Understanding self-directed learning behaviors in a computer-aided 3D design context. Comput Educ.2023;205(3):104882. https://doi.org/10.1016/j.compedu.2023.104882.
44. Chen B, Zhu X. Integrating generative AI in knowledge building. Computers and Education: Artif Intell. 2023;5(1):100184.
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