ปัญญาประดิษฐ์: เปลี่ยนโฉมการบริหารสถานศึกษาในศตวรรษที่ 21

Panawan Khamsrithaveewat; Siwakorn Inphusa; Yingsak Hapa

Authors

Panawan Khamsrithaveewat Mahachulalongkornrajavidyalaya University, Khon Kaen Campus, Thailand
Siwakorn Inphusa Mahachulalongkornrajavidyalaya University, Khon Kaen Campus, Thailand
Yingsak Hapa Mahachulalongkornrajavidyalaya University, Khon Kaen Campus, Thailand

Keywords:

Artificial Intelligence (AI), School Management, Educational Innovation

Abstract

The integration of Artificial Intelligence (AI) into school management and education has significantly impacted teaching, learning, and administrative processes. AI enhances the efficiency of resource management and simplifies planning and data tracking. At the same time, teachers and administrators must develop technological skills to adapt to their new roles, shifting from traditional teaching to mentoring. AI is also used to analyze and customize learning experiences to suit individual student abilities. Moreover, AI increases equal access to education, especially through personalized learning. However, there are challenges in implementing AI, including ethical concerns, data privacy for students, and the varying readiness of educational institutions. Preparing and training personnel to understand and use this technology is crucial. In the future, AI will inevitably become a fundamental part of education. Developing policies for data security, creating new innovations, and preparing for this transformation will be key to fostering a sustainable and high-quality education system.

References

กระทรวงศึกษาธิการ. (2546). พระราชบัญญัติการศึกษาแห่งชาติ พ.ศ. 2542 และที่แก้ไขเพิ่มเติม (ฉบับที่ 2) พ.ศ. 2545.องค์การรับส่งสินค้าและพัสดุภัณฑ์ (ร.ส.พ.).

Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies.W. W. Norton & Company.

Chen, C. (2022). Artificial intelligence in education: Current applications and future directions. Journal of Educational Technology, 25(2), 45–60.

Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies(Vol. 1, pp. 4171–4186). Association for Computational Linguistics. https://doi.org/10.18653/v1/N19-1423

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning.MIT Press.

Hinton, G. E. (2018). Deep learning—A technology with the potential to transform health care. JAMA, 320(11), 1101–1102. https://doi.org/10.1001/jama.2018.11100

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning.Center for Curriculum Redesign.

Katz, S. (2021). Preparing educators for the future: The role of AI in teacher training. International Journal of Education Research, 15(1), 22–34.

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017). ImageNet classification with deep convolutional neural networks. Communications of the ACM, 60(6), 84–90. https://doi.org/10.1145/3065386

Liu, Y. (2020). AI in industry: Transforming business processes. Harvard Business Review, 98(3), 12–19.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education.Pearson.

Wilkins, S. (2020). The positioning and competitive strategies of higher education institutions in the United Arab Emirates. International Journal of Educational Management, 34(1), 139–153.

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education—Where are the educators? International Journal of Educational Technology in Higher Education, 16, Article 39. https://doi.org/10.1186/s41239-019-0171-0