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Digital Manpower is very necessary in Thailand today as the growth of technology continues to increase. For example, tech giant Gartner has announced new technology trends every year including 2022, announcing the following technology trends: Total Experience, Composable Application, Decision Intelligence, Hyperautomation, Distributed Enterprises, Autonomic Systems, Generative AI, AI Engineering etc. The application of technology in daily life is increasing. The development of Digital Manpower is therefore very important in order to increase the knowledge and expertise of the country's people in technology. From the statistics, the country has increased internet usage in many ways. For example, from the statistics in 2021, Thai children playing games were number 1 in the world, and in 2022, Thai children playing games are in 2nd place in the world. But the problem faced with Thai education today is that children like to play games and think that they can study in the field of computers. But, in fact, students are not directed into the technology field taking into account their own aptitudes. causing the study to be not fully effective and some leave their courses midway. Therefore, this research is interested in the confirmation factors of children playing games by collecting data on Gamers' Total Experience and Game Motivation in order to analyze the data and discover the confirmation factors that direct the admissions to various computer disciplines. What direction and aptitude do you need to be able to enter a group of computer science disciplines in order to become a Digital Manpower in the country's future development. The researcher has collected data from a sample of 630 people from all six groups in computer science. The confirmation factor was analyzed by the LISREL program. It was found that each group of computer disciplines had different confirmation factors.

The purposes of this research study are to develop an intelligent virtual universal learning (IVUL) model and to evaluate its appropriateness. The study consisted of two phases. Phase 1 involved the development of the IVUL model for univer-sal learning. The conceptual frameworks and theories in the documents and re-search studies on universal design for learning, intelligent learning and virtual learning were studied by the researchers. All main components were then synthe-sised to design the IVUL model. This process can be divided into three main steps: engagement, representation, and action and expression. Each step has sub-steps: access, build and internalise. However, the details of these are dependent on the main steps. The second component is the intelligent learning process, an important process of the model that drives learners to automatically learn by themselves. Artificial intelligence is used as a crucial component that promotes and supports each learner to meet learning goals and objectives according to the universal learning model. The third component is the virtual learning process, which results in learning through computer environments and the Internet. Phase 2 involved an evaluation of the appropriateness of the IVUL model, with in-depth interviews with 20 experts in education and digital technologies. The appropriate-ness of the model was evaluated using the 5-point Likert scale. The findings show that the designed IVUL model can be used for learning development at the highest level.

The research aims to Data Science Performance Synthesis for Higher Education Students and Data Science Performance Suitability Assessment for Higher Education Students. The research instruments include 1) data science performance synthesis tables, 2) expert interviews in data science performance assessments, 3) expert questionnaires to assess the consistency of data science performance. Analytical methods include 1) analyzing the frequency obtained from the content analysis table, 2) synthesis of content from interviews, 3) analyzing performance consistency, and components of data science performance, from data science synthesis for higher education students, finding that data performance for higher education students consists of five performances: 1) programming skills, 2)elementary statistics, 3) fundamentals of data science, 4) data preparation, and 5) Big data analytics.

The objective of this research was as follows: 1) to synthesise the Personalized Cognitive Counseling Process to Promote Digital Health. 2) to develop the Personalized Cognitive Counseling Process to Promote Digital Health. 3) to evaluate the Personalized Cognitive Counseling Process to Promote Digital Health. The documentary research method was used in this study. 4) to adapt the Personalized Cognitive Counseling model for Digital Health. The results showed a model of Personalized Cognitive Counseling Process to Promote Digital Health which consisted of four steps: Step 1: Synthesis of the Personalized Cognitive Counseling Process to Promote Digital Health. This includes the following three components: Personalized Learning, Cognitive Learning and Counseling. Step 2: The development of the Personalized Cognitive Counseling Process to Promote Digital Health. The researchers found that a model of Personalized Cognitive Counseling Process to Promote Digital Health consists of five processes: 1) Understanding 2) Design 3) Development 4) Choosing and Using Tools 5) Evaluation. Step 3: The evaluation of the Personalized Cognitive Counseling Process to Promote Digital Health. The results of the evaluation in terms of suitability revealed that the design process was deemed to be at the highest level. Step 4: Adapting Result of the Personalized Cognitive Counseling model for Digital Health

This research aimed to: develop a model for vocational instructors’ acceptance of online instruction after they had arranged online instruction for one year; and investigate the consistency of this model using the empirical evidence gained from 1,818 vocational instructors from five regions in Thailand: the Northern Region, the Northeastern Region, the Central Region, the Eastern Region and Bangkok, and the Southern Region. The research instrument used to collect the data was a questionnaire on the vocational instructors’ acceptance of online instruction. The data were analysed using construct validity and the consistency of the causal relationship model. The research findings revealed that social distancing during the COVID-19 pandemic resulted in the vocational instructors’ adjusted attitudes towards online instruction for the better. This adjustment directly affected some changes in the instructors’ behaviour in physical classroom instruction to online instruction in the following period. Keywords: online learning, technology acceptance model, vocational education and training

Knowledge of all disciplines is more or less equally important and crucial but, in education management, it is important to integrate disciplines so that the knowledge is useful and can be applied to create new things, solve problems and prevent future threats. STEM education for vocational student is not only a trend in education, but also an instructional approach that focuses on students and will lead to sustainable knowledge and learning. This research studied documents that explored the importance of STEM literacy for vocational school students in Thailand. Vocational education must be aligned with Thailand 4.0 and Industrial 4.0 models, and thus vocational schools must adjust their learning approach to be aligned with the Education 4.0 model. As vocational school students will be valuable to the development of the country, STEM literacy must be integrated into a project-based learning model which is a teaching approach for creating invention and innovation. The result of the study shows that STEM literacy for Thai vocational education consists of six components: identifying a STEM problem, exploring and acquiring new knowledge, applying STEM concepts, solving the STEM problem, communicating STEM information and making a STEM decision. The aforementioned components can be used to create a STEM literacy evaluation form for vocational school students.

The objective of this research is to create an augmented reality interactive learning model, using the Imagineering process for the SMART classroom. The overall method is divided into 4 stages: (1) development of the augmented reality interactive learning model; (2) development of using augmented reality learning materials; (3) development of best practices teachers of ICT; and (4) expanding these results with the augmented reality interactive learning model. The target group for the research is 30 excellent tertiary teachers, 20 vocational instructors, 600 vocational students and 900 tertiary students. Qualified experts certified that the interactive learning model developed is at the most appropriate level. The interactive learning material activities consist of four main processes: preparation, prototype teacher development, outreach, and evaluation. The results of evaluation indicate that the quality of creative innovation is at the highest level.

Constructionism imagineering learning model via metaverse is an instrument for promoting self-learning through hands-on. To create new knowledge for young innovators by combining the concepts of technology and new learning platforms to create new ideas. Designing teaching and learning that can be used to learn in the new normal focuses on continuous learning at any time, anywhere, with the benefits of using technology. The sample group is six experts in designing and developing learning models and learning systems from various institutions in higher education by purposive sampling. The research instruments are as follows. 1) The constructionism imagineering learning model via metaverse to enhance young innovators. 2) The constructionism imagineering learning process via metaverse to enhance young innovators. 3) An assessment form for the constructionism imagineering learning model via metaverse to enhance young innovators. 4) An assessment form for the constructionism imagineering learning process via metaverse to enhance young innovators. Analyse data using mean and standard deviation. The researchers found that the constructionism imagineering learning model via metaverse and the constructionism imagineering learning model via metaverse, which is developed is appropriate to enhance young innovators at the highest level, following the research hypotheses.

This research was undertaken by synthesizing theories, documents, textbooks, research articles, and related academic articles relating to the wisdom repository management process. The objective is to present a system architecture and develop a knowledge management system which culminates in a repository of crystallized intelligence with a conversational agent that can promote learning for medical students by introducing a system architecture to develop intelligent agent technology. Through mobile technology, accessible anytime, anywhere, lifelong learning for medical students will be supported via an intelligent crystallized intelligence inventory management system. This keynote includes a comprehensive implementation and has API. The application has been tested with a trial run of all commands, with satisfactory results in the communication of the system that the user accesses through chatbots.

This paper presents the conceptual framework, value chain model and the system architecture of intelligent student relationship management based on cognitive technology with conversational agent for enhancing student’s loyalty in higher education. The purposes were to synthesize the conceptual framework and apply it to develop the value chain model and the system architecture of intelligent student relationship management based on cognitive technology with conversational agent for enhancing student’s loyalty in higher education and assess the developed value chain model and system architecture. The questionnaire was employed as the instrument to assess and certify the value chain model and the system architecture by the experts. The 5 point-Likert scale was used to identify the level of agreement of the value chain model and system architecture certification assessment. The instrument was verified by five experts using content validity index (CVI). After that, the value chain model and the system architecture were verified based on the consensus assessments of seventeen experts using mean, standard deviation (S.D.), median, interquartile range and quartile deviation. The results revealed that the experts had a consensus on the value chain model developed based on the conceptual framework (Mean = 4.89, S.D. = 0.27, Median = 5, Interquartile Range: I.R. = 0.00, Quartile Deviation: Q.D. = 0.00). They also had a consensus to approve the system architecture developed based on the value chain model (Mean = 4.70, S.D. = 0.55, Median = 5, Interquartile Range: I.R. = 1.00, Quartile Deviation: Q.D. = 0.50).

This research is research and development aims to develop a creative design thinking learning (CDTL) model integrated immersive experiential marketing to enhance digital entrepreneurs’ competence. The research methodology are as follows: study CDTL process integrated immersive experiential marketing, study digital entrepreneurs, develop CDTL models, develop CDTL systems, and evaluate digital entrepreneurs' competence. The samples were 30 vocational diploma students of the business computer program of Intrachai Commercial College. The instrument was the digital entrepreneurs’ competence evaluation forms. Data were statistically analyzed with mean and standard deviation. The results indicated that (1) the CDTL process has 3 steps: preparation, implementation, and evaluation; (2) digital entrepreneur’s competence has 3 competence: digital entrepreneurship competence, digital competence, creative digital economy innovation; (3) the learning model efficiency score was at the highest level; (4) the students study through the learning model obtained digital entrepreneurship competence score at the highest level and creative digital economy innovation at a high level.

Face recognition technology is widely used in applications. But in some activities it may be too difficult to install the device and the registration boot. That requires both manpower and time, such as enrolling students to attend university activities. If you will use the face scanning system, one by one will waste a lot of time. The other method. It may be easy to falsify. Using digital imagery in student participation to solve problems by developing a system that can detect participants' faces in digital photographs obtained by taking still images and videos from several photographers. And collecting detailed pictures and videos throughout the event it is a digital proof to find the participants to verify their faces match with any student in the database. Who participate in that activity, the system will have Finding and comparing data of pre-recorded students' photographs and the algorithm would checks for duplicate data and records the activity in the database. Where users can specify category or activity name for later inspection

This research aims to develop a creative history learning model using digital storytelling through cloud learning to enhance analytical thinking. The research methodology is divided into 3 steps involving the use of digital storytelling through cloud learning to enhance analytical thinking. This involves 1) studying the creative history learning process, 2) developing the creative history learning model, 3) comparing the students’ analytical thinking scores before and after learning. The sample consisted of Mathayomsuksa 5 students of the Chonburi Sukkhabot School in the 2nd semester of the academic year 2019. The research instrument was an assessment of the students’ analytical thinking. Data were statistically analyzed with the use of mean and standard deviation measurements. The research findings were as follows 1) The creative history learning process using digital storytelling through cloud learning to enhance analytical thinking consisted of 4 steps: 1) The introductory stage included student orientation, specification of the learning objectives and historical topics; 2) The instruction stage included researching historical information, summarizing historical facts, creating digital storytelling media 3) The summary stage included presenting material by digital storytelling 4) Evaluation. The cloud learning resources used were Facebook Group, Google Drive, Google Form, and YouTube. The suitability evaluation score was at the highest level (x̅= 4.63, S.D. = 0.41) 2) The students who learned through the creative history learning model using digital storytelling through cloud learning had analytical thinking scores after learning (x̅ = 26.13, S.D. = 1.63) which were higher than scores before learning (x̅ = 10.70, S.D. = 2.58). The results were statistically significant at the .05 level.