Interdisciplinary Virtual Learning Community Model for Social Engineer

Thananan Areepong, Prachyanun Nilsook and Panita Wannapiroon (2025) Interdisciplinary Virtual Learning Community Model for Social Engineer. Journal of Theoretical and Applied Information Technology
15th May 2025. Vol. 103. No. 9, 2025.
https://www.jatit.org/volumes/Vol103No9/7Vol103No9.pdf

Abstract:The paper suggests developing a Metaverse interdisciplinary learning community model – M-ILC – to develop social engineers. The interdisciplinary learning community process leverages the Metaverse platform tool to foster social engineering skills among students. The study offers a synthesis of materials with regard to interdisciplinary learning communities in various formats. Emphasis is placed on the significance of nurturing human soft skills through utilizing the Metaverse in the learning process to provide learners with a 3D virtual experience. This collaborative learning approach leads to a more profound comprehension of subject content and expands educational opportunities for students. The suitability of the Metaverse Interdisciplinary Learning Community model (M-ILC) developed by experts in Information Technology, Communication Technology, and the Metaverse, was assessed. The evaluation results were rated as “excellent”, indicating the suitability of the overall learning community model. This suggests that the M-ILC model can effectively cultivate students’ social engineering skills and prepare them for the upcoming digital transformation. Furthermore, it contributes to sustaining a consistent quality standard in the education system. The researchers have introduced new teaching concepts and innovations that align with the current situation in the form of a learning model, fostering a boundary-less learning society that can be accessed anytime and anywhere.

Business Intelligence Management with Artificial Intelligence for Prediction Information Technology Infrastructure in Higher Education

Abstract:

This study uses a mixed-methods research approach, combining meta-analysis and systematic Bibliometrix analysis, to explore the use of Business Intelligence (BI) and Artificial Intelligence (AI) in predicting Information Technology (IT) infrastructure in higher education institutions. The synergy between BI and AI serves as a key tool for evaluating and forecasting IT infrastructure, supporting decision-making and strategic IT planning in universities. This research develops predictive models for IT infrastructure investments using BI and AI, ensuring efficient resource allocation and enhancing university decision-making, aligned with the evolving digital landscape in higher education.

Warunee Milinthapunya, Urairat Yamchuti, Anake Nammakhunt, Chatchada Shawarangkoon, Panita Wannapiroon, Prachyanun Nillsook. (2025) Business Intelligence Management with Artificial Intelligence
for Prediction Information Technology Infrastructure in Higher Education.TEM Journal, 14(2), 1378-1387.
https://doi.org/10.18421/TEM142-38

ปัญญาประดิษฐ์ พลังขับเคลื่อนสู่การพัฒนาที่ยั่งยืน

สไลด์ประกอบการบรรยายพิเศษ
การประชุมวิชาการระดับชาติและนานาชาติ “เบญจมิตรวิชาการ” ครั้งที่ 15
“ปัญญาประดิษฐ์ พลังขับเคลื่อนสู่การพัฒนาที่ยั่งยืน”
Artificial Intelligence : A Driving Force for Sustainable Development Goals
มหาวิทยาลัยธนบุรี
วันพฤหัสบดีที่ 15 พฤษภาคม 2568
https://ict.fte.kmutnb.ac.th/prachyanun/2025/AI_for_SDGs.pdf