Abstract

This research aims to 1) synthesize the conceptual framework and 2) develop the architecture and evaluate its applicability. This paper outlines the architectural framework for the digital transformation of enterprises, specifically focusing on an intelligent financial management system. The research is synthesized, and a systematic review employs the PRISMA flow diagram. This system will utilize a financial management database that includes salary management, accounting management, fixed asset management, risk control, report management, financial analysis, and system administration. This framework will integrate advanced artificial intelligence techniques to improve operational efficiency, accuracy, and security in financial operations. It can improve risk assessment, elevate client contacts, and optimize economic decision-making processes, therefore aiding in the formation of organizational support, management supervision, operational plans, and administrative decisions, among other elements. The results showed that this architecture has an excellent level of suitability (mean = 4.63, standard deviation = 0.44). It demonstrates that entities employing advanced financial management systems to facilitate data storage mitigate inaccuracies and assist in the rapid, precise, and efficient analysis of data, which is an outcome of implementing digital transformation. This shift enhances decision-making processes and fosters a culture of accountability and transparency within organizations, ultimately driving sustainable growth and innovation. © 2025 by the authors.

Keywords

Digital transformation; Financial management system; Intelligence financial management system

Pinyaphat Tasatanattakool, Katekeaw Pradit, Prachyanun Nilsook and Panita Wannapiroon (2025) Digital transformation of organizations: Intelligence financial management system. International Journal of Innovative Research and Scientific Studies, 8(1) 2025, pages: 773-783.
https://doi.org/10.53894/ijirss.v8i1.4422

Abstract

As Thailand navigates the challenges of the digital economy, higher education institutions are increasingly compelled to undertake systemic transformation to prepare graduates for employment in AI-integrated environments. This study proposes an AI-driven institutional transformation model specifically tailored to the context of Thai universities. The study was conducted with three main objectives: (1) to synthesize the core components of the model, (2) to develop and validate the proposed model, and (3) to assess its applicability level. A mixed-methods research design was employed to ensure both conceptual rigor and contextual relevance. The research procedure comprised three phases: (1) model synthesis, (2) model development and validation, and (3) model evaluation. The findings revealed that the 3D-POD Model integrates three dimensions: 1) Strategic domains—People, Pedagogy, Process, Platform, and Pathway; 2) Operational phases—Origin, Operation, Output, Outcome, and Optimization; and 3) Digital maturity—Digital Passive, Digitization, Digitalization, Digital Transition, and Digital Transformation. Collectively, these dimensions form a structured matrix (5 Strategic × 5 Operational × 5 Maturity Levels) that provides a practical lens for diagnosing, developing, and enhancing AI-driven transformation in higher education. Quantitative validation confirmed the model’s high content validity and practical applicability. The 3D-POD Model offers a strategic pathway for AI-driven institutional transformation and enhanced graduate employability in Thailand. The model may also serve as a reference for future digital intervention initiatives led by key stakeholders.

Keywords

• AI
• Generative AI
• Data-Driven Decision Making
• Digital Intervention
• Digital Leadership
• Higher Education
• Graduate Employability

Sararuch, S., Buabangplu, P., Nittayathammakul, V., Wannapiroon, P., and Nilsook, P. (2025) The 3D-POD Model for AI-Driven Institutional Transformation and Graduate Employment Readiness in Thailand in Digital Era. Lecture Notes in Computer Science Conference Paper2025.
https://doi.org/10.1007/978-981-96-8430-4_3

Abstract—Emerging technologies, such as the Artificial Intelligence of Things (AIoT), pose challenges in education, particularly when students struggle to connect theoretical concepts with practical applications. This gap limits their ability to engage with AIoT and develop computational thinking competencies, such as Critical Thinking, Algorithmic design, Problem-solving, Creativity, and Cooperativity. To address this issue, the Advance Organizer Integrating Visual-Based Programming for Artificial Intelligence of Things (AOVP-AIoT) model, was developed. The model combines structured scaffolding with visual programming to make AIoT concepts more accessible and engaging, fostering computational thinking skills applicable in formal and informal learning settings, including university courses, online training, and professional workshops. The study was conducted in two phases. Phase I involved designing the AOVP-AIoT model by synthesizing data from research publications (2003–2023). Expert review rated the model highly (mean = 4.39, SD = 0.69) across input components, learning processes, and computational thinking competencies. Phase II involved constructing the AOVP-AIoT platform, following the AIoT System Development Life Cycle (AIoT-SDLC) across eight iterative stages. Unlike existing approaches, the platform emphasizes on personalized learning pathways and interactive AI assistance, enchancing adaptability and real-time support. Evaluation results indicated very high quality in infrastructure, intelligence organizer-based management, learning tracking, and performance assessment (mean = 4.69, SD = 0.43). By equipping learners with transferable computational thinking skills, the AOVP-AIoT model addresses educational challenges in AIoT and prepares students for success in industries increasingly shaped by AI and IoT innovations.

Keywords—advance organizer, visual programming, artificial intelligence of things, computational thinking

Sant Phanichsiti, Prachyanun Nilsook, and Pallop Piriyasurawong,
“Advance Organizer Integrating Visual-Based Programming via Artificial Intelligence of Things to Enhance Advanced Computational Thinking Competency,” International Journal of Information and Education Technology, vol. 15, no. 7, pp. 1355-1367, 2025.
https://doi.org/10.18178/ijiet.2025.15.7.2337

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—This research aims to use artificial intelligence technology to create micro-learning approach. The goal is to develop students’ skills in designing character movements to look more realistic and interesting, as well as in using Mixed Reality (MR). This research was conducted in the form of a cross-sectional study and a literature review. During October–December 2024, the sample population were recruited from among undergraduate students at the Faculty of Mass Communication Technology, Multimedia Technology, and Rajamangala University of Technology Thanyaburi. The research data were collected from a total sample of 30 students through a questionnaire to assess whether micro-learning approach with artificial intelligence technology can be used to develop skills in character movement design in game design and utilizing mixed reality. The research results found that this learning format is very effective. In terms of the quality of the content and learning media, it has an average score of 4.85 ± 0.03 (the highest quality). As a result, learners can effectively develop important skills and engage strongly in the learning process. The use of mixed reality technology enhances the immersive and engaging learning experience for learners. This learning style is extremely effective and suitable for developing movement design skills for in-game characters.

Keywords—micro-learning, Artificial Intelligence (AI), skills in designing character movements, Mixed Reality (MR)

Vipusit Piankarnka, Prachyanun Nilsook, and Panita Wannapiroon,
“A Micro-Learning Approach with Artificial Intelligence for Improving Skills in Designing the Movement of In-Game Characters and Using Mixed Reality,” International Journal of Information and Education Technology, vol. 15, no. 4, pp. 847-857, 2025.
https://doi.org/10.18178/ijiet.2025.15.4.2291

Abstract—This research was aimed at creating and developing digital influencers with generative artificial intelligence to strengthen a university’s image and communicate with a target group, and comparing their use to traditional forms of communication. We conducted the research as an observational study. A literature review was conducted to study the elements of the process of using digital influencers created with generative artificial intelligence through an intelligent platform as university goodwill ambassadors. Research data was collected from a sample group of 150 people. We used a questionnaire to assess the effectiveness of using digital influencers created with generative artificial intelligence through an intelligent platform as university goodwill ambassadors. In the analysis, the use of digital influencers created with generative artificial intelligence through an intelligent platform was compared with regular communication by using the paired t-test statistic. A total of 150 participants were included in the study. The results showed that most of them were female (n = 87; 58 percent), aged 15–25 years (n = 106, 70.67 percent) and students (n = 99, 66 percent); 23 persons were university personnel (15.33 percent) and 28 persons were members of the general public (18.67 percent). From the results of the evaluation of the quality of using digital influencers created with artificial intelligence through an intelligent platform as university goodwill ambassadors, it was found that digital influencers created with artificial intelligence and used through an intelligent platform as university goodwill ambassadors could represent the university, and provide public relations and support for university activities. They could promote relationships between the university and third parties. As a result, communication within the organization became convenient and fast. It was even found to be more modern compared to traditional forms of communication, with statistical significance. Artificial intelligence is effective in improving communication; organizations can provide accurate information immediately and reduce the workloads of personnel. Artificial intelligence can also analyze insights from user conversations. This university can use this information to improve communication to better meet the needs of the target audience.

Keywords—digital influencers, generative artificial intelligence, intelligent platform, university goodwill ambassador

Vipusit Piankarnka, Prachyanun Nilsook, and Panita Wannapiroon,
“Generative AI-Created Digital Influencers to Be University Goodwill Ambassadors,” International Journal of Information and Education Technology, vol. 15, no. 1, pp. 106-116, 2025.
https://doi.org/10.18178/ijiet.2025.15.1.2223

Abstract

Processing speed is a critical component of cognitive apprenticeship, which is essential for developing cognitive skills for high-pressure environments. This study highlighted the limitations of traditional teaching methods in fostering rapid decision-making skills and proposed a simulation game-based learning (SGBL) model as an innovative instructional approach. It aimed to (1) develop a targeted SGBL model, (2) assess its effectiveness in enhancing cognitive apprenticeship and processing speed and (3) evaluate student satisfaction. The methodology was divided into three phases: a primary study to identify student needs, system design and development, and implementation. The SGBL model included theoretical and practical sessions, encompassing real-world scenario-based games for practicing life-saving skills. The study involved 73 undergraduate students, split into two experimental groups, and utilised a learning achievement test and a satisfaction questionnaire as research instruments. The findings revealed significant improvements in processing speed and learning outcomes (p < .01). Students expressed high levels of satisfaction, indicating the effectiveness and potential applicability of the model in other fields. Future implications include expanding SGBL with AR/VR and multiplayer functions to enhance engagement and applicability.

Keywords: 

• Simulation game-based learning
• cognitive apprenticeship
• processing speed
• cognitive skill develop

Sounthornwiboon, P., Sriprasertpap, K., & Nilsook, P. (2025).
Simulation game-based learning for cognitive apprenticeship development: a focus on processing speed. Cogent Education, 12(1).
https://doi.org/10.1080/2331186X.2024.2449280