A Proposed Artificial Intelligence-Based System for Developing E-management Skills in Saudi Primary Schools

  • Ahlam Mahmoud Hagag The National Egyptian E-learning University (EELU) Faculty of Educational Studies, Egypt
  • Mohamed Elsayed Elnaggar Associate Professor of Educational Technology The National Egyptian E-learning University (EELU) Faculty of Educational Studies, Egypt
  • Rasha Saad Sharaf Professor, Comparative Education and Education Administration Faculty of Education - Helwan University, Egypt
Keywords: Artificial intelligence, machine learning, data analytics, chatbot, e-survey, e-management skills

Abstract

This study aims to investigate the impact of Artificial intelligence-driven solutions on school leaders’ proficiencies. Leaders have the responsibility of making decisions in educational institutions as well as carrying out routine tasks daily. Artificial intelligence-assisted applications have noteworthy contributions to the field of educational management. The scope of this study is limited to selected features; data analytics, chatbot, and e-survey. The basic design of this study started with analyzing literature in this domain. This was followed by designing a system consisting of four models: building a dashboard, predicting students’ results, creating a chatbot for responding to parents’ queries and creating an e-survey for measuring staff satisfaction. The participants of this study consist of 35 school leaders, whereas the sample was one group that was exposed to special treatment. A pre/post-test was conducted to examine the impact of the treatment, in addition to an observation card that was used to measure the treatment’s impact on the technical domains. The researchers used SPSS to analyze the study’s results. The prominent finding of this study is the significant impact of Artificial intelligence on leaders’ competencies; the difference between mean scores in both pre and post-test application and post-application for the observation card has proven the positive impact of the proposed treatment.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

PlumX Statistics

References

1. Ahmad, K., Qadir, J., Al-Fuqaha, A., Iqbal, W., El-Hassan, A., Benhaddou, D., & Ayyash, M. (2020). Artificial Intelligence in Education: A Panoramic Review.
2. Ahmad, S.F.; Alam, M.M.; Rahmat, M.K.; Mubarik, M.S.; Hyder, S.I. Academic and Administrative Role of Artificial Intelligence in Education. Sustainability 2022, 14, 1101. https://doi.org/10.3390/su14031101
3. Ajuzieneogu U., (2020). The Role of Artificial Intelligence in Modern Computing and Education. Edition: 1st Edition. Publisher: Lulu. Editor: Lulu. ISBN: 978-0-359-72121-4
4. Aldalalah, O., Ababneh, Z. W., & Shatat, F. H. (2015). E-Administration in The Public Schools of The Abu Dhabi Education Council From Teachers' View Point. In Information and Knowledge Management (Vol. 5, No. 7, pp. 131-142).
5. Amadi, E. C. (2008). Introduction to educational administration: A module. Port Harcourt: Harey Publications.
6. Amalia, K., Komariah, A., Sumarto, S., & Asri, K. H. (2020, February). Leadership in Education: Decision-Making in Education. In 3rd International Conference on Research of Educational Administration and Management (ICREAM 2019) (pp. 134-137). Atlantis Press.‏
7. Ashirwadam, J. (2014). Communication Research Methods Methods of Data Analysis. Tamilnadu Theol. Semin, 1-6.
8. Atwi, Jawdat Ezzat (2001). Educational administration and educational supervision: its origins and applications, House of Culture for Publishing and Distribution.
9. Baker, R. S., & Inventado, P. S. (2014). Educational data mining and learning analytics. In Learning analytics (pp. 61-75). Springer, New York, NY.
10. Baker, T., Smith, L., & Anissa, N. (2019). Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges. Retrieved May 12, 2020.
11. Bakhshinategh, B., Zaiane, O. R., ElAtia, S., & Ipperciel, D. (2018). Educational data mining applications and tasks: A survey of the last 10 years. Education and Information Technologies, 23(1), 537-553.
12. Bhila, T., & Maseru, L. (2018). The Benefits and Generic Procedure of Automating an Academic Student System in Primary and Secondary Schools as an Impetus for Educational Technology. International Journal of Innovative Science and Research Technology, 3(11), 480-486.
13. Bikakis, N. (2018). Big data visualization tools. arXiv preprint arXiv:1801.08336.
14. Chantarotwong, B. (2006). The learning chatbot. Final year project.[Online]: http://courses. ischool. berkeley. edu/i256/f06/projects/bonniejc. pdf.
15. Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: a narrative overview. Procedia Computer Science, 136, 16-24.
16. Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: a review. Ieee Access, 8, 75264-75278. doi: 10.1109/ACCESS.2020.2988510
17. De Smedt, J., vanden Broucke, S. K., Vanthienen, J., & De Witte, K. (2017). improved Student Feedback with Process and Data Analytics. In Data Analytics Applications in Education (pp. 11-36). Auerbach Publications. Frank
18. Elnozahy, W. A., El Khayat, G. A., Cheniti-Belcadhi, L., & Said, B. (2019). Question Answering System to Support University Students’ Orientation, Recruitment and Retention. Procedia Computer Science, 164, 56-63.
19. Farkash, Z. (2018). Higher Education Chatbot: Chatbots Are the Future of Higher Education. Chatbots Life.
20. Goksel, N., & Bozkurt, A. (2019). Artificial intelligence in education: Current insights and future perspectives. In Handbook of Research on Learning in the Age of Transhumanism (pp. 224-236). IGI Global.
21. Haenlein, M., & Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California management review, 61(4), 5-14.
22. Hien, H. T., Cuong, P. N., Nam, L. N. H., Nhung, H. L. T. K., & Thang, L. D. (2018, December). Intelligent assistants in higher-education environments: the FIT-EBot, a chatbot for administrative and learning support. In Proceedings of the ninth international symposium on information and communication technology (pp. 69-76).‏
23. Holmes, W., Hui, Z., Miao, F., & Ronghuai, H. (2021). AI and education: A guidance for policymakers. UNESCO Publishing.
24. Hristova, V. (2019). Advantages and limitations of chat bots in human resources management activities. Научные горизонты, (8), 74-80.
25. https://files.eric.ed.gov/fulltext/ED536788.pdf
26. Imran, M., Latif, S., Mehmood, D., & Shah, M. S. (2019). Student Academic Performance Prediction using Supervised Learning Techniques. International Journal of Emerging Technologies in Learning, 14(14).
27. Johnson Jr, B. L., & Kruse, S. D. (2012). Decision making for educational leaders: Underexamined dimensions and issues. SUNY Press.
28. Johnson, B. D., Dunlap, E., & Benoit, E. (2010). Organizing “mountains of words” for data analysis, both qualitative and quantitative. Substance use & misuse, 45(5), 648-670
29. Karsenti, T. (2019). Artificial intelligence in education: the urgent need to prepare teachers for tomorrow’s schools. Formation et profession, 27(1), 112-116.
30. Kengam, J. (2020). Artificial Intelligence in Education. Encyclopedia of Computational Chemistry.
31. Kristjansson, A. L., Sigfusson, J., Sigfusdottir, I. D., & Allegrante, J. P. (2013). Data collection procedures for school‐based surveys among adolescents: The Youth in Europe Study. Journal of School Health, 83(9), 662-667.‏
32. Król, K., & Zdonek, D. (2020). Analytics Maturity Models: An Overview. Information, 11(3), 142.
33. Mader, C., & Hilty, L. (2008). Artificial intelligence in schools. Education, 25(2), 177-203.
34. Madhu, H. K., & Prakash, B. R. (2019). A Survey: Big Data Ethics and Challenges in Healthcare Division. International Journal of Computer Science and Engineering, 7(3), 16-24.
35. Markow, D., Macia, L., & Lee, H. (2013). The MetLife survey of the American teacher: Challenges for school leadership. New York, NY: Metropolitan Life Insurance Company
36. Massud & Khalifa (2008).Human and materialistic requirements of applying electronic management in public school from the own point of view of the principals and vice-principles in al-Rass Governorate.
37. Naggar &Habib (2021). Artificial Intelligent Program based on Chatbot and Learning Style in E-Training Environment and its Impact on developing E-Learning Management System usage skills among Preparatory Stage. Learning Technology: Research and studies 31(2), 91-201.
38. Nawaz, N., & Gomes, A. M. (2019). Artificial intelligence chatbots are new recruiters. IJACSA) International Journal of Advanced Computer Science and Applications, 10(9).
39. Nguyen, A., Gardner, L., & Sheridan, D. (2020). Data analytics in higher education: An integrated view. Journal of Information Systems Education, 31(1)
40. Nicol, D. J., & Macfarlane‐Dick, D. (2006). Formative assessment and self‐regulated learning: A model and seven principles of good feedback practice. Studies in higher education, 31(2), 199-218.
41. Obied, T.( 2020). Role of School Administrators in Providing an Attractive and Safe School Environment to Students under Vision 2030. Propositos y Representaciones, 8 ( SPE3), e748
42. Owoc, M. L., Sawicka, A., & Weichbroth, P. (2021). Artificial Intelligence Technologies in Education: Benefits, Challenges and Strategies of Implementation. arXiv preprint arXiv:2102.09365.
43. Riahi, Y., & Riahi, S. (2018). Big data and big data analytics: Concepts, types and technologies. International Journal of Research and Engineering, 5(9), 524-528.
44. Rogge, N., Agasisti, T., & De Witte, K. (2017). Big data and the measurement of public organizations’ performance and efficiency: The state-of-the-art. Public Policy and Administration, 32(4), 263-281.
45. Roos, S. (2018). Chatbots in education: A passing trend or a valuable pedagogical tool?.
46. Shrestha, Y. R., Ben-Menahem, S. M., & Von Krogh, G. (2019). Organizational decision-making structures in the age of artificial intelligence. California Management Review, 61(4), 66-83.‏
47. Smutny, P., & Schreiberova, P. (2020). Chatbots for learning: A review of educational chatbots for the Facebook Messenger. Computers & Education, 151, 103862.
48. Supriyanto, G., Widiaty, I., Abdullah, A. G., & Mupita, J. (2018, November). Application of expert system for education. In IOP Conference Series: Materials Science and Engineering (Vol. 434, No. 1, p. 012304). IOP Publishing.
49. Tyson, Matthew, "Educational Leadership in the Age of Artificial Intelligence." Dissertation, Georgia State University, 2020. doi: https://doi.org/10.57709/18723065
50. Ugurlu, C.T(2013). “Effects of decision making styles of school administrators on general procrastination behaviors” . Egitim Arastirmalari-Eurasian Journal of Educational Research, 51,253-272
51. Vanthienen, J., & De Witte, K. (Eds.). (2017). Data analytics applications in education. CRC press.
52. Vehovar, V., & Manfreda, K. L. (2008). Overview: online surveys. The SAGE handbook of online research methods, 1.
53. Weinstock, P., Yumoto, F., Abe, Y., Meyers, C., & Wan, Y. (2016). How to Use the School Survey of Practices Associated with High Performance. REL 2016-162. Regional Educational Laboratory Midwest.
54. https://iite.unesco.org/publications/ai-in-education-change-at-the-speed-of-learning/ ISBN/ISSN: ISBN 978-5-6046449-2-8 (eng); ISBN 978-5-6046449-1-1 (rus)
55. Lunenburg, F. C. (2010, September). THE DECISION MAKING PROCESS. In National Forum of Educational Administration & Supervision Journal (Vol. 27, No. 4).
56. Ranoliya, B. R., Raghuwanshi, N., & Singh, S. (2017, September). Chatbot for university related FAQs. In 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI) (pp. 1525-1530). IEEE.
57. Hussain, S., Sianaki, O. A., & Ababneh, N. (2019, March). A survey on conversational agents/chatbots classification and design techniques. In Workshops of the International Conference on Advanced Information Networking and Applications (pp. 946-956). Springer, Cham.
58. Abdelhamid, S., & Katz, A. (2020, July). Using Chatbots as Smart Teaching Assistants for First-Year Engineering Students. In 2020 First-Year Engineering Experience.
Published
2023-04-29
How to Cite
Hagag, A. M., Elnaggar, M. E., & Sharaf, R. S. (2023). A Proposed Artificial Intelligence-Based System for Developing E-management Skills in Saudi Primary Schools. European Scientific Journal, ESJ, 19(11), 111. https://doi.org/10.19044/esj.2023.v19n11p111
Section
ESJ Humanities