The Application of Artificial Intelligence in Academic Management of School Administrators in the Mae Charao School Cluster under the Tak Primary Educational Service Area Office 2

Abstract

The purposes of this research article were 1) to study the current application of Artificial Intelligence (AI) in academic administration by school administrators in the Mae Charao school cluster; and 2) to study guidelines for developing the application of AI in academic administration by school administrators in the Mae Charao school cluster under the Tak Primary Educational Service Area Office 2. A mixed-methods research approach was used, combining quantitative and qualitative research. For the quantitative research, the population consisted of 12 school administrators and 171 teachers, totaling 183 individuals, in the Mae Charao school cluster, under the Tak Primary Educational Service Area Office 2, during the 2025 academic year. A questionnaire with a reliability coefficient of 0.97 was used. The sample size was determined using the Krejcie-Morgan formula, resulting in a sample of 123 individuals: 12 school administrators and 111 teachers. Data were analyzed using frequency, percentage, and mean, and presented in tabular form with descriptive captions. The qualitative research method involved purposive interviews with five key informants: two school administrators with at least the professional qualification of "Expert" and three teachers with at least the professional qualification of "Expert". Data were analyzed using content analysis techniques. The research findings revealed that 1) the overall application of artificial intelligence (AI) in academic administration by school administrators in the Mae Charao school cluster under the Tak Primary Educational Service Area Office 2 was at a high level (  = 3.55, S.D.= 0.59); and 2) the guidelines for developing the application of AI in academic administration by school administrators indicated that it was recommended to promote the use of AI in data analysis and predicting student needs in order to develop up-to-date curricula and learning management, support teachers in developing learning materials and tools, and reduce workload and increase the efficiency of teaching. In addition, AI should be applied in educational data analysis, supervision, evaluation of learning management, and data compilation for educational quality assurance to support administrator decision-making and develop the academic administration of schools effectively and sustainably.