A Review Analysis on Using "AIED" to Improve Student Engagement in Hybrid Education

Authors

  • Sylvester Joseph Department of Computer Science & IT, Superior University, Lahore, 54000, Pakistan Author
  • Amna Tahir Department of Computer Science & IT, Superior University, Lahore, 54000, Pakistan Author
  • Farwa Bibi Department of Software Engineering, Superior University Lahore-54000, Pakistan Author
  • Dr. Khalid Hamid Department of Computer Science, Superior University, Lahore, 54000, Pakistan Author
  • Muhammad Waseem Iqbal Department of Software Engineering, Superior University, Lahore, Pakistan. Author
  • Sadaquat Ali Ruk Shah Abdul Latif University, Ghotki Campus, Pakistan Author
  • Saleem Zubair Ahmad Department of Software Engineering, Superior University Lahore-54000, Pakistan Author

DOI:

https://doi.org/10.61506/01.00348

Keywords:

Artificial intelligence, interactive learning, hybrid education, online teaching, student involvement

Abstract

Hybrid learning is a sophisticated blend of in-person and online learning. This concept mixes multimedia assets with traditional classroom activities. Hybrid learning combines virtual and in-person approaches. The goal of the study is to improve student engagement in hybrid learning settings by utilizing artificial intelligence (AI). Maintaining students' interest and motivation is becoming more difficult for educators as online and hybrid learning gain traction. A lot of educational institutions find these models intriguing because they provide peer-to-peer connection, flexibility, and student-teacher involvement. AI can address problems in education by enhancing student collaboration, communication, and real-time feedback. The advantages and disadvantages of hybrid learning are examined in this article, along with the most effective methods for integrating artificial intelligence (AI) into learning settings. AI has the power to revolutionize hybrid learning by fostering a more engaged learning environment and giving teachers and students greater autonomy.

References

Ahmad, S. F., Hameed, Z., & Khan, N. A. (2021). Artificial intelligence and its role in education. Sustainability, 13(22), 12902. DOI: https://doi.org/10.3390/su132212902

Alharbi, W. (2023). AI in the foreign language classroom: A pedagogical overview of automated writing assistance tools. Education Research International, 2023(1), 4253331. DOI: https://doi.org/10.1155/2023/4253331

Almusaed, A., & Almssad, A. (Eds.). (2023). Sustainable Smart Cities: A Vision for Tomorrow. BoD–Books on Demand. DOI: https://doi.org/10.5772/intechopen.100727

Almusaed, A., Almssad, A., & Rico Cortez, M. (2023). Critical interpretation of a non-creative supervision practice for Ph.D. students. Journal of Higher Education Research, 15(1), 26-46.

Almusaed, A., Almssad, A., & Rico-Cortez, M. (2022). CDIO Initiative on Student Engagement by Effective Syncretic (Lectures--Seminars). In Proceedings of the International Society for Technology, Education, and Science (pp. xx-xx). ISTES Organization.

Almusaed, A., et al. (2023). Enhancing student engagement: Harnessing “AIED”’s power in hybrid education—A review analysis. Education Sciences, 13(7), 632. DOI: https://doi.org/10.3390/educsci13070632

Alzahrani, F. K., & Alhalafawy, W. S. (2023). Gamification for learning sustainability in the blackboard system: Motivators and obstacles from faculty members’ perspectives. Sustainability, 15(5), 4613. DOI: https://doi.org/10.3390/su15054613

Costa, R. S., Nogueira, R., & Silva, R. (2021). Personalized and adaptive learning: Educational practice and technological impact. Texto Livre, 14(3), e33445. DOI: https://doi.org/10.35699/1983-3652.2021.33445

Deeva, G., Pechenizkiy, M., & Trieschnigg, D. (2021). A review of automated feedback systems for learners: Classification framework, challenges and opportunities. Computers & Education, 162, 104094. DOI: https://doi.org/10.1016/j.compedu.2020.104094

Dhara, S., Datta, A., & Pramanik, S. (2022). Artificial Intelligence in Assessment of Students' Performance. In A. I. Rehman (Ed.), Artificial Intelligence in Higher Education (pp. 153-167). CRC Press. DOI: https://doi.org/10.1201/9781003184157-8

Finogeev, A., Frengov, I., & Babichev, M. (2018). Life-cycle management of educational programs and resources in a smart learning environment. Smart Learning Environments, 5, 1-14. DOI: https://doi.org/10.1186/s40561-018-0055-0

Gómez-Pulido, J. A., Macías, J. A., & López-Gutiérrez, J. (2023). Data analytics and machine learning in education. Applied Sciences, 13(3), 1418. DOI: https://doi.org/10.3390/app13031418

Guerrero-Roldán, A.-E., et al. (2021). Experiences in the use of an adaptive intelligent system to enhance online learners' performance: A case study in Economics and Business courses. International Journal of Educational Technology in Higher Education, 18, 1-27. DOI: https://doi.org/10.1186/s41239-021-00271-0

Halaweh, M. (2023). ChatGPT in education: Strategies for responsible implementation. Contemporary Educational Technology, 15(2), ep421. DOI: https://doi.org/10.30935/cedtech/13036

Hamid, K., Iqbal, M. waseem, Fuzail, Z., Muhammad, H., Basit, M., Nazir, Z., & Ghafoor, Z. (2022). Detection of Brain Tumor from Brain MRI Images with the Help of Machine Learning & Deep Learning.

Hamid, K., Iqbal, M. waseem, Fuzail, Z., Muhammad, H., Basit, M., Nazir, Z., & Ghafoor, Z. (2022). Detection of Brain Tumor from Brain MRI Images with the Help of Machine Learning & Deep Learning.

Hamid, K., Iqbal, M. waseem, Muhammad, H., Fuzail, Z., & Nazir, Z. (2022). ANOVA Based Usability Evaluation Of Kid’s Mobile Apps Empowered Learning Process. Qingdao Daxue Xuebao(Gongcheng Jishuban)/Journal of Qingdao University (Engineering and Technology Edition), 41, 142–169.

Hamid, K., Muhammad, H., Iqbal, M. waseem, Nazir, A., shazab, & Moneeza, H. (2023). ML-Based Meta Model Evaluation Of Mobile Apps Empowered Usability Of Disables. Tianjin Daxue Xuebao (Ziran Kexue Yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology, 56, 50–68.

Hargreaves, S. (2023). 'Words Are Flowing out Like Endless Rain into a Paper Cup': ChatGPT & Law School Assessments. Legal Education Review, 33, 69. DOI: https://doi.org/10.53300/001c.83297

Hwang, G.-J., & Chang, C.-Y. (2023). A review of opportunities and challenges of chatbots in education. Interactive Learning Environments, 31(7), 4099-4112. DOI: https://doi.org/10.1080/10494820.2021.1952615

Khan, I., Ali, S., & Khan, W. (2021). An artificial intelligence approach to monitor student performance and devise preventive measures. Smart Learning Environments, 8, 1-18. DOI: https://doi.org/10.1186/s40561-021-00161-y

Kim, J., Lee, H., & Cho, Y. H. (2022). Learning design to support student-AI collaboration: Perspectives of leading teachers for AI in education. Education and Information Technologies, 27(5), 6069-6104. DOI: https://doi.org/10.1007/s10639-021-10831-6

Krenn, M., et al. (2022). On scientific understanding with artificial intelligence. Nature Reviews Physics, 4(12), 761-769. DOI: https://doi.org/10.1038/s42254-022-00518-3

Kuhail, M. A., Al-Zoubi, A. M., & Alsmadi, M. K. (2023). Interacting with educational chatbots: A systematic review. Education and Information Technologies, 28(1), 973-1018. DOI: https://doi.org/10.1007/s10639-022-11177-3

Lameras, P., & Arnab, S. (2021). Power to the teachers: An exploratory review on artificial intelligence in education. Information, 13(1), 14. DOI: https://doi.org/10.3390/info13010014

Lee, Y.-F., Hwang, G.-J., & Chen, P.-Y. (2022). Impacts of an AI-based chatbot on college students’ after-class review, academic performance, self-efficacy, learning attitude, and motivation. Educational Technology Research and Development, 70(5), 1843-1865. DOI: https://doi.org/10.1007/s11423-022-10142-8

Liu, Z., Chen, Y., Wang, J., Wang, X., Zhang, H., & Sun, M. (2023). Deid-gpt: Zero-shot medical text de-identification by GPT-4. arXiv preprint arXiv, 2303.11032.

Manzali, Y., et al. (2024). Prediction of Student Performance Using Random Forest Combined With Naïve Bayes. The Computer Journal. Advance online publication. DOI: https://doi.org/10.1093/comjnl/bxae036

Moorhouse, B. L., & Wong, K. M. (2022). Blending asynchronous and synchronous digital technologies and instructional approaches to facilitate remote learning. Journal of Computers in Education, 9(1), 51-70. DOI: https://doi.org/10.1007/s40692-021-00195-8

Muhammad, H., Basit, M., Hamid, K., Iqbal, M. waseem, Shahzad, S., Muneem, F., & Shaheryar, M. (2022). Usability Impact of Adaptive Culture in Smart Phones.

Neha, K. (2020). Role of Artificial Intelligence in Education. Alochana Chakra Journal, 9(IX), 305-309.

Rathore, B. (2023). Future of AI & generation alpha: ChatGPT beyond boundaries. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 12(1), 63-68. DOI: https://doi.org/10.56614/eiprmj.v12i1y23.254

Schiff, D. (2021). Out of the laboratory and into the classroom: The future of artificial intelligence in education. AI & Society, 36(1), 331-348. DOI: https://doi.org/10.1007/s00146-020-01033-8

Tan, S. (2023). Harnessing Artificial Intelligence for innovation in education. In S. Tan (Ed.), Learning intelligence: Innovative and digital transformative learning strategies: Cultural and social engineering perspectives (pp. 335-363). Springer Nature Singapore. DOI: https://doi.org/10.1007/978-981-19-9201-8_8

Wei, X., Zhang, Y., & Hu, B. (2021). Personalized online learning resource recommendation based on artificial intelligence and educational psychology. Frontiers in Psychology, 12, 767837. DOI: https://doi.org/10.3389/fpsyg.2021.767837

Zancajo, A., Verger, A., & Bolea, P. (2022). Digitalization and beyond: The effects of Covid-19 on post-pandemic educational policy and delivery in Europe. Policy and Society, 41(1), 111-128. DOI: https://doi.org/10.1093/polsoc/puab016

Zheng, F. (2022). [Retracted] Personalized Education Based on Hybrid Intelligent Recommendation System. Journal of Mathematics, 2022(1), 1313711. DOI: https://doi.org/10.1155/2022/1313711

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Published

2024-06-01

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Articles

How to Cite

Sylvester Joseph, Amna Tahir, Farwa Bibi, Hamid, K. ., Iqbal, M. W. ., Sadaquat Ali Ruk, & Saleem Zubair Ahmad. (2024). A Review Analysis on Using "AIED" to Improve Student Engagement in Hybrid Education. Bulletin of Business and Economics (BBE), 13(2), 424-435. https://doi.org/10.61506/01.00348