This research aims to design and develop a mobile-learning training kit for assessing the depression risk of elderly Muslims using the spiritual dimension of human security. In this research, we compare the achievements before and after the training of village health volunteers using mobilelearning training kits in a simple, random way. The sample is divided into two groups: a sample of 30 individuals is used to determine the performance and the academic achievement of the mobilelearning training kit. In addition, 33 other people are used to assess user satisfaction with the mobile learning training kit. The research indicates that the design and development of the training kits
involving digital storytelling are characterized by two languages: Thai and Malay, consisting of 4 modules, with an efficiency of 81.56. In terms of achievement in a series of training sessions using the mobile-learning training kit, it was found that after training, the results were statistically significantly higher than before training at .05 and that the users’ satisfaction with the training kit was extremely high.
Keywords: mobile learning training kits; digital storytelling; depression risk; spiritual dimensions; Muslim Elderly
Katekeaw Pradit, Anong Phibral and Prachyanun Nilsook (2022)
Digital storytelling training kit for assessing depression risk for the elderly. International Journal of Education and Development using Information and Communication Technology.
(IJEDICT), 2022, Vol. 18, Issue 3, pp. 173-190. (ERIC)
Abstract:The objectives of this study were to investigate the virtual board games and to evaluate the virtual board games compared to the physical board game. The results of this study indicated that the overall composition of a virtual platform was comparable to that of a physical board game. Especially for the functional aspect, experts agreed that the virtual board game was as convenient as or better than the physical board game while in other aspects, including the enjoyment aspect, the virtual board games can be used in the same way as the physical board games. On the other hand, the social aspect was a slightly inferior one.
C. Chukusol, P. Nilsook and P. Wannapiroon, “Virtual Board Games Platform,” 2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C), 2022, pp. 273-277,
Abstract:The Impact of Industry Revolution has been accelerated by global pandemic crisis recently. Disruptive technology is one of the key driving forces of transformation on the rapid change in business model and market demand. Traditional industries, including education, experience the challenge of maintaining business at lower cost while generating high performance (more revenue) and staying relevant in the market. Digital Transformation helps improve collaboration within and between organizations by creating immersive customer experience for better engagement. Enterprise organization wants to grow and give it a better chance of thriving post-pandemic by becoming more innovative and generating higher productivity and making better decisions with insights from data-driven platform. To achieve all the business requirements for transformation is not straightforward. By understanding the alignment of Business and Information Technology Architecture, Higher Education institutions can manage the challenges of the future trends. The success of Digital Transformation in enterprise organizations is determined by an agile implementation framework of Enterprise Architecture (EA). Enterprise Architecture is the critical intermediary between business and IT corporate wide strategy. Through understanding the current situation and performance of an enterprise, EA can help foresight future business challenges and deliver the information needed while simultaneously ensuring opportunities for business growth
S. Sararuch, P. Wannapiroon and P. Nilsook, “Dimensions of Agile Enterprise Architecture,” 2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C), 2022, pp. 304-309,
Abstract:The objective of this research is to Present the use of Digital Twin. Internet of Things and Intelligence Technology to Intelligently Develop The Energy Management Potential of Campuses By using Digital Twin to manage energy consumption, it enables the creation of work and life on campus, whether it is personal. Teachers and students, including those with disabilities, have a better quality of life. Living on campus is more comfortable Collect energy consumption data, organizations to manage power management systems, reduce energy consumption, simplify management in all departments, and reduce campus costs. It can transparently monitor energy consumption and use educational equipment on campus, especially cost and expenditure management, and sustainable energy consumption, as well as management. Control usage data, energy consumption results, and budget allocations related to educational institutions can create reliability in managing information about electrical energy and energy competency assessment results, and can be recorded and controlled in Digital Twin that can be as if it were with a control center. IoT and Cloud Computing are also integrated with AI systems embedded in state-of-the-art equipment for use in environmental management and intelligent energy management. As well as creating new energy models and management that can resolve future emergencies by controlling virtual energy within the organization from outside anytime, anywhere.
T. Pexyean, K. Saraubon and P. Nilsook, “IoT, AI and Digital Twin For Smart Campus,” 2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C), 2022, pp. 160-164,
Critical success factors for smart-professional disruptor in university
Phisit Pornpongtechavanich, Kawitsara Eumbunnapong, Therdpong Daengsi, Prachyanun Nilsook
Current and emerging technologies have changed a lot. Consequently, every year, Gartner Technology has made many new changes in accordance with global developments. For example, in terms of artificial intelligence (AI), mixed reality (MR), extended reality (XR), collaboration platforms, online learning, distributed cloud, internet of behaviors (IoB), and cybersecurity. Due to changes in technology, disruptors have to constantly learn new technology in order to be up to date in the transfer of knowledge to learners. Therefore, in this research, critical success factors (CSFs) have been studied, which help them become highly skilled professionals by developing their own skills with technology to be a successful disruptor at university. The study found the CSFs, which were derived from the synthesis of international research papers. Disruptors’ success consists of 12 internal and 10 external success factors. Smart-professional disruptors in universities were assessed using a focus group method with eight experts. Focus group results found that there were seven important internal factors for smart-professional disruptors in universities and seven minor internal factors. Including all internal factors, smart-professional disruptors have 14 factors; external factors are the most important ones for smart-professional disruptors in universities. In total, smart-professional disruptors have a total of 11 external factors.
Phisit Pornpongtechavanich, Kawitsara Eumbunnapong, Therdpong Daengsi and Prachyanun Nilsook (2022)
Critical success factors for smart-professional disruptor in university.
International Journal of Evaluation and Research in Education.Vol. 11, No. 4, December 2022, pp. 1696-1703. (SCOPUS), (ERIC)
The research titled career skills and entrepreneurship for students by collaborative project-based learning management model aimed to study the results of learning management to develop students to have career skills and entrepreneurship by collaborative project-based pedagogy. The population consisted of 15 undergraduates who were teacher students at the Business Education Program, the Faculty of Education, Chiang Mai University, Thailand. This group of students had to attend an internship at schools after enrolling in this course in, and they had to teach career subjects at schools. The instruments used for data collection consisted of a lesson plan for the self-employment course, a behavior observation form, a journal form after teaching, student products from assignment tasks, students’ reflections in a journal, an in-depth interview, a focus group, and a questionnaire to gauge the level of satisfaction of students, writing and presenting reflections on students’ learning, and projects evaluation. The research separated students into three groups upon their interests, each group was composed of 5 students volunteer, they learned better in a small group. Students learned the theory of the self-employment program and the principles of project work step by step. After that, students studied field trips for data collection from career surveys and entrepreneurs’ interviews, and a special lecture from an entrepreneur, students conducted self-employment projects for selling products both on-site and online, then analyzed the results presented, to listen to suggestions for improvement, and developed knowledge and skills on the self-employment program. Data were analyzed by using content analysis, statistical calculation, and percentage, and were presented in the form of a description and table. The findings showed the results of the collaborative project-based learning to train students to have career skills and entrepreneurship and conduct projects for selling products successfully. The students had a change in their attitudes, behaviors, knowledge, career skills, and experiences in conducting self-employment projects, and their satisfaction with collaborative project-based learning showed at the highest level (100%). Students were satisfied with the project-based learning at the highest level (90%). and especially the opportunity to gain knowledge and experiences from conducting self-employ programs at the highest level (95%).
Phetcharee Rupavijetra, Prachyanun Nilsook, Jira Jitsupa and Uraiwan Hanwong (2022) Career Skills and Entrepreneurship for Students by Collaborative Project-Based Learning Management Model. Journal of Education and Learning.Vol. 11, No. 6 (2022), pp.48-61.
This research aims to apply confirmatory factor analysis to identify the digital transformation components for higher education institutions. The research sample consisted of 300 personnel from agencies within higher education institutions, which are higher education institutions under the Ministry of Higher Education, Science, Research and Innovation, Thailand that use the database system on educational quality assurance called Commission on Higher Education Quality Assessment online system (CHE QA Online). The selection was the result of multi-stage random sampling from 100 higher education instructions. The research tool was an online questionnaire form on factors influencing the success of information systems in the digital transformation for higher education institutions by 5-level rating scale based on the Likert’s scale. The result revealed that digital transformation factor consistent with empirical data (p-value = 0.860), which consist of 6 components: 1) Strategy 2) Process 3) Product/Service 4) People 5) Data) and 6) Technology. The research findings help higher education institutions prepare for the elements necessary for the institutional transformation to a digital organization.
Chanin Tungpantong, Prachyanun Nilsook and Panita Wannapiroon. (2022) Factors Influencing Digital Transformation Adoption among Higher Education Institutions during Digital Disruption. Higher Education Studies. Vol. 12, No. 2 (2022) ; pp.9-19.
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.
Chaiyarak, S., Nilsook , P., & Wannapiroon, P. (2022). IVUL Model: An Intelligent Learning Development Process.
International Journal of Emerging Technologies in Learning (iJET), 17(14), pp. 39–51. https://doi.org/10.3991/ijet.v17i14.31527
Transform universities with digital technology drives changes in both operations. The procedures in accordance with the planned goal or long-term university development plan are in accordance with state policy guidelines. According to the national strategic plan, national economic and social development plan, long-term higher education plan, national development plan. The purpose of this research the content to propose the structural equation model for high performance digital entrepreneurial university. The research instituted the hypothesized digital transformation, entrepreneurial university, digital organization, enterprise architecture and high-performance organization. The research was conducted in both quantitative and qualitative survey and interview were conducted with 300 representatives were selected by cluster sampling working in the higher education institutions. The results of research the analysis of structural equation model found that the evaluation was consistent with the empirical data. The conclusions are as follows: (Chi-square=90.267 df. =75) (CMIN/DF = 1.204) (GFI =. 974) and (RMSEA =. 026). The results showed that all factors had a direct effect on the significant statistics of 0.001
Tippawan Meepung, Prachyanun Nilsook, and Panita Wannapiroon (2022).Higher Education Management to Digital Entrepreneurial University. Journal of Theoretical and Applied Information Technology. May 2022. Vol.100. No 10.
Abstract—This research aims to develop online teaching plan through applying gamification. The results reveal learning performance, motivation, and satisfaction of the undergraduate towards the intervention. The sampling group is the undergraduate enrolling in Digital Literacy course in the second semester of the 2020 academic year of 154. The research tools consist of online teaching plan incorporating gamification, achievement test, motivation level evaluation form, and satisfaction survey of the undergraduate with this teaching plan. The results inform that the online teaching plan generates performance according to the specified 80/80 criteria. The learning performance of the undergraduate is significantly higher than that before the implementation of the online teaching plan incorporating gamification at .01. Learning motivation of the undergraduate is significantly different with the statistical level of .01. Also, the undergraduate is highly satisfied with online teaching applying gamification.
Jira Jitsupa, Mutita Takomsane, Sasanun Bunyawanich, Nualsri Songsom, and Prachyanun Nilsook, “Combining Online Learning with Gamification: An Exploration into Achievement, Motivation, and Satisfaction of the Undergraduate,” International Journal of Information and Education Technology vol. 12, no. 7, pp. 643-649, 2022.