Abstract:This research has designed and developed a The Role-Play Method Human Augmentation Learning Model to Enhance Digital Content Creator, aiming to study and synthesize the framework for developing role-playing Method Human Augmentation Simulation Learning models to enhance digital content creators and study feasibility. The development approach is a model for managing, studying or reviewing the content of studying in covid-19 situations, there are 50 undergraduate students in digital media technology, Rajamangala University of Technology Tawan-Ok. Research content uses digital film production course content. Digital Media Technology Program in Multimedia Technology, Rajamangala University of Technology Tawan-Ok, 6 lessons, trialled in semester 2, academic year 2022, the method of conducting research is divided into 5 phases: Phase 1 synthesis of conceptual framework for developing The Role-Play Method Human Augmentation Learning Model to Enhance Digital Content Creator Phase 2 Synthesis of substanceist features. The expected benefit is that it competes with Digital Content Creator that are suitable for the context of Thailand. Educational institutions that offer courses in relevant disciplines have guided them with Role-Play learning methods to develop Digital Content Creator.Published in: 2022 International Conference on Decision Aid Sciences and Applications (DASA)Date of Conference: 23-25 March 2022Date Added to IEEE Xplore: 02 May 2022ISBN Information:DOI: 10.1109/DASA54658.2022.9764987Publisher: IEEEConference Location: Chiangrai, Thailand

P. Thongdee, P. Chatwattana and P. Nilsook, “A Study of Role-Play Method and Human Augmentation to Enhance Digital Content Creator,” 2022 International Conference on Decision Aid Sciences and Applications (DASA), 2022, pp. 201-205, https://doi.org/10.1109/DASA54658.2022.9764987.

Abstract:Unemployment is a global problem which, as well as being the source of scarcity and other problems, threatens people’s well-being. Effectively addressing the issue is one of the new challenges of the workplace in the age of digital technology. Tertiary education institutions strive to develop people’s potential before they enter the world of work. Developing the necessary skills – including operational skills with tools – requires laboratory training. A fabrication laboratory is an open space that promotes tooling skills, along with systematic and creative thought processes and inventiveness. All these can, in turn, form the basis of innovations that will benefit the community as a whole. This study began by looking at the trends and research related to fabrication laboratories. Then, in Step 2, it analysed and synthesised the relevant research, examined the elements of the fabrication laboratory, created a synthetic table and, finally, summarised the results. These showed that most of the research consisted of eight elements: 1) design spaces, 2) rapid prototyping tools, 3) electronic instruments, 4) mechanical tools, 5) scientific instruments, 6) a Group Learning Toolkit, 7) other tools, and 8) learning exchange or publishing spaces. This study is a review, therefore, of the research relating to the elements in the proper learning environment of a tertiary education fabrication laboratory. It is necessary if we are to develop the potential of learners across all sectors before they enter the world of work.Published in: 2022 International Conference on Decision Aid Sciences and Applications (DASA)Date of Conference: 23-25 March 2022Date Added to IEEE Xplore: 02 May 2022ISBN Information:DOI: 10.1109/DASA54658.2022.9765186Publisher: IEEEConference Location: Chiangrai, Thailand

S. Srisawat, P. Wannapiroon and P. Nilsook, “A review of the elements of a fabrication laboratory to develop engineering prototypes,” 2022 International Conference on Decision Aid Sciences and Applications (DASA), 2022, pp. 1122-1126, https://doi.org/10.1109/DASA54658.2022.9765186.

Abstract:Population is the personnel working in higher education institutions in Thailand, the population used in this research included personnel under 155 institutions of higher education under the supervision of the ministry of higher education, science, research, and innovation, divided into 3 groups: state university private university. using a sample of 300 higher education personnel. sampling by cluster sampling used statistics on frequency distribution of data by percentage Arithmetic mean standard deviation inferential statistical analysis. The research objective was to analyze the factors influencing the transition. Higher education institutions to high-performance digital entrepreneurs university. Data were analyzed by using descriptive statistics, frequency distribution of data by percentage. Arithmetic means standard deviation Analysis of inferential statistics and confirmatory factor analysis (CFA).Published in: 2022 International Conference on Decision Aid Sciences and Applications (DASA)Date of Conference: 23-25 March 2022Date Added to IEEE Xplore: 02 May 2022ISBN Information:DOI: 10.1109/DASA54658.2022.9765297Publisher: IEEEConference Location: Chiangrai, Thailand

T. Meepung, P. Nilsook and P. Wannapiroon, “Factors Influencing the Transition of Entrepreneurial University,” 2022 International Conference on Decision Aid Sciences and Applications (DASA), 2022, pp. 1505-1509, https://doi.org/10.1109/DASA54658.2022.9765297

Abstract:This research aims to apply confirmatory factor analysis to identify the enterprise architecture components for higher education institutions. The research sample comprised 300 personnel from agencies within higher education institutions, which are higher education institutions under the Ministry of Higher Education, Science, Research and Innovation that use the database system of educational quality assurance called Commission on Higher Education Quality Assessment online system (CHE QA Online). The selection resulted from multi-stage random sampling from 100 higher education instructions. The research tool was an online questionnaire form on factors influencing the enterprise architecture in the digital transformation for higher education institutions by 5-level rating scale based on the Likert’s scale. The result revealed that the enterprise architecture factor is consistent with empirical data (p-value = 0.370), which comprise 5 components: 1) Business 2) Data/Information 3) Application 4) Infrastructure and 5) Security. The research findings help higher education institutions design their blueprint for the institutional transformation to a digital organization.Published in: 2022 International Conference on Decision Aid Sciences and Applications (DASA)Date of Conference: 23-25 March 2022Date Added to IEEE Xplore: 02 May 2022ISBN Information:DOI: 10.1109/DASA54658.2022.9764970Publisher: IEEEConference Location: Chiangrai, Thailand

C. Tungpantong, P. Nilsook and P. Wannapiroon, “Confirmatory Factor Analysis of Enterprise Architecture for Higher Education Institutions,” 2022 International Conference on Decision Aid Sciences and Applications (DASA), 2022, pp. 965-969, https://doi.org/10.1109/DASA54658.2022.9764970