Designing digital teachers with generative AI through mixed reality technology to increase practical learning in designing characters for animation

Abstract

The purpose of this research is to study the elements and processes of digital teacher design. Generative AI can be processed visually for navigation in conjunction with visual intelligence through mixed reality technology, thereby adding practical learning and character design for animation purposes. This research focuses on the application of generative AI technology combined with visual processing to develop digital teachers with intelligent visual abilities using mixed reality technology, to enable the creation of more dimensional and interactive practical learning experiences, especially in the field of character design for animation. Using visual intelligence allows learners to learn better using a hands-on approach, which improves learners’ design and creative skills in a hybrid reality and digital environment. Education for digital teacher design can use generative AI that can be processed visually for navigation with the aid of visual intelligence. This study was conducted in the form of an observational study supported by a literature review to study the elements and processes for modeling the design of digital teachers. Use questionnaires to assess the modeling process and digital teacher design process. The researcher evaluated the design process using 3 practical teachers, 3 gen-ai experts, 3 visual intelligence experts, and 3 MR technology experts, for a total of 12 people. The evaluation led to an average value of 4.69 ± 0.40, with an average value of 4.69 ± 0.40 (the highest quality). Generative AI that can process visuals for navigation with visual intelligence through mixed reality technology enhances the practical learning of character design for animation, resulting in learners being able to effectively develop important skills and be highly involved in the learning process. The use of mixed reality technology enhances the immersive and engaging learning experience for learners. It is effective and can increase the learning of character design for animation work, which can be applied in teaching and learning management in the future.

Vipusit Piankarnka, Pinyaphat Tasatanattakool and Prachyanun Nilsook (2025) Designing digital teachers with generative AI through mixed reality technology to increase practical learning in designing characters for animation. International Journal of Innovative Researchand Scientific Studies,8(4) 2025, pages: 1129-1144.
https://doi.org/10.53894/ijirss.v8i4.8017

Advance Organizer Integrating Visual-Based Programming via Artificial Intelligence of Things to Enhance Advanced Computational Thinking Competency

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

การปรับตัวในโลกยุคใหม่ อยู่ร่วมกับ AI อย่างรู้เท่าทัน

งานประชุมวิชาการระดับชาติ “นอร์ทเทิร์นวิจัย” ครั้งที่ 11 ประจำปีการศึกษา 2567 “เทคโนโลยี AI เพื่อการพัฒนาชุมชนอย่างยั่งยืน”
วันศุกร์ที่ 30 พฤษภาคม 2568 ณ วิทยาลัยนอร์ทเทิร์น จังหวัดตาก
“การปรับตัวในโลกยุคใหม่ อยู่ร่วมกับ AI อย่างรู้เท่าทัน”

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

innovations for the future of education

Abstract

The study of innovations for the future of education is a synthesis of content from interviews with AI through chat rooms which key informants were specifically selected from ChatGPT, Copilot, Gemini, Deepseek, and Grok, with the same interview questions. The research results found that innovations for the future have three characteristics: new innovations, specific innovations, and continuous innovations from the present. It reflects that the data from AI interviews provide fast, clear, and reliable results that are consistent with general searchable data. It is useful for the future of education

Keywords: Educational innovation , Educational future, AI chat

Nilsook, P. (2025). INNOVATION FOR THE FUTURE OF EDUCATION.
Journal of Industrial Education, 24(1), A1-A6.
https://ph01.tci-thaijo.org/index.php/JIE/article/view/261865
https://doi.org/10.55003/JIE.24101

A Micro-Learning Approach with Artificial Intelligence for Improving Skills in Designing the Movement of In-Game Characters and Using Mixed Reality

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

Adaptive Micro-Learning Model Based on Dhamma Using Mixed Reality to Develop Students to Be Good Citizens.

Abstract

The COVID-19 pandemic forced school closures globally, leading to significant learning regression in academic performance, skills, and ethical development. This study aims to: 1) synthesize and develop an adaptive micro-learning model based on Dhamma principles using mixed reality (MR), 2) compare pre-and post-test results, and 3) assess the model’s impact on students’ good citizenship. Participants included 19 experts and 39 Grade 6 students. The methodology involved synthesizing and developing an adaptive micro-learning model, comparing pre- and post-study scores, and evaluating academic achievement and good citizenship development. The study identified seven key steps in the adaptive micro-learning model: 1) testing prior knowledge (Dhammannuta), 2) reporting prior knowledge results (Atthanyuta), 3) explaining learning objectives (Attanyuta), 4) outlining the learning path (Mattanyuta), 5) video-based learning (Kalanyuta), 6) collaborative learning via MR (Parisanyuta), and 7) peer knowledge exchange (Pukkalanyuta). The model’s effectiveness was rated highly (x̅ = 4.78, S.D. = 0.34). Students’ good citizenship scores significantly improved, increasing from a pre-test average of 15.87 points (52.90%) to a post-test average of 25.72 points (85.73%), with statistical significance at the 0.01 level.

Kitiya Promsron, Prachyanun Nilsook & Pallop Piriyasurawong (2025)
Adaptive Micro-Learning Model Based on Dhamma Using Mixed
Reality to Develop Students to Be Good Citizens.
International Education Studies; Vol. 18, No. 2; 2025 ; pp. 123-136.
https://doi.org/10.5539/ies.v18n2p123

“ธมฺโม หเว รกฺขติ ธมฺมจารึ” ธรรมย่อมรักษาผู้ประพฤติธรรม