คลังเก็บหมวดหมู่: ผลงานวิจัย

IoT, 6G and Digital Twin For Smart Campus

Tanapeak Pexyean, Kobkiat Saraubon and Prachyanun Nilsook (2023)
T. Pexyean, K. Saraubon and P. Nilsook, “IoT, 6G and Digital Twin For Smart Campus,”
2023 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C), Bangkok, Thailand, 2023, pp. 46-50,
https://doi.org/10.1109/RI2C60382.2023.10355994.

Abstract:Smart Campus This research aims to present the use of the Internet of Things and smart technologies that work with 6G networks to intelligently improve the energy management capabilities of campuses. Whether it’s personal. Teachers and students, including those with disabilities, have a better quality of life. Within the university, energy consumption data is collected. Organizations to manage energy management systems Reduce energy consumption Reduce management by using technology to manage and reduce campus costs, transparently monitor energy consumption and use of campus educational equipment, especially cost and expense management, and sustainable energy use. Control usage data, energy consumption results, and estimate budget allocation related to educational institutions. IoT and Cloud Computing are also integrated into 6G networks embedded in state-of-the-art devices for use in environmental management and intelligent energy management, as well as creating new energy models and management that can solve future emergencies with external on-premises virtual energy control anytime, anywhere. Smart Building Management with twin technologies helps to intelligently manage and control indoor energy systems, such as automation for temperature control in buildings. Air conditioner energy consumption control system Electricity consumption control in lighting system This saves energy and increases the usability of buildings within smart campuses.

System Architecture of Electronic Asset Supply Chain Intelligent Platform for Digital Higher Education

Denchai Panket, Panita Wannapiroon & Prachyanun Nilsook (2024)
System Architecture of Electronic Asset Supply Chain Intelligent
Platform for Digital Higher Education.
Higher Education Studies; Vol. 14, No. 1; 2024, pp.22-32.
https://doi.org/10.5539/hes.v14n1p22

Abstract

This research aims to design an intelligent platform architecture for electronic asset supply chains for digital higher education and to evaluate the architecture of the intelligent platform for electronic asset supply chains for digital higher education. The sample group consists of evaluations of the intelligent platform architecture for the electronic asset supply chains for digital higher education by experts. These experts assess and certify the appropriateness of the architecture, evaluating the content’s suitability and the management processes. The evaluations were conducted by 5 experts who have experience in managing assets in higher education or relevant areas. The research results indicate that the designed intelligent platform architecture for electronic asset supply chains for digital higher education, on average, scored 4.43, which is considered ‘good’. The evaluation of its developmental trend from architecture to platform has an average score of 4.80, considered ‘very good’. Following that, both the system (Administrators) and the (Webserver and Database Server) evaluations yielded the same average score of 4.60, which is also ranked as ‘very good.’

Distributed Communicative Language Training Platform Using Automatic Speech Recognition Technology for Smart University

Keywords: 

Distributed Enterprise, Communicative Language Teaching, Automatic Speech Recognition, Smart University

ABSTRACT

The purpose of this research is to achieve the following objectives: 1) Synthesize documents and international research on the characteristics of a smart university. 2) Synthesize the processes of distributed communicative language training (DCLT). 3) Design the system architecture of a DCLT platform that utilizes automatic speech recognition (ASR) technology for a smart university. 4) Evaluate the appropriateness of a DCLT platform that utilizes ASR technology for a smart university. Nine experts were selected for this research. They were required to have more than five years of relevant experience in the field, including expertise in system architecture, distributed enterprise, language teaching, and ASR. The research instruments included a suitable assessment form for evaluating the system architecture of a DCLT platform that utilizes ASR technology for a smart university. The results of this research indicate that the DCLT platform, which utilizes ASR technology, was considered suitable for a smart university.

Phuengrod, S., Wannapiroon, P., & Nilsook, P. (2023). Distributed Communicative Language Training Platform
Using Automatic Speech Recognition Technology for Smart University.
International Journal of Emerging Technologies in Learning (iJET),
18(24), pp. 96–111. https://doi.org/10.3991/ijet.v18i24.40619

A Fabricator Competency for Engineering Students in Tertiary Education

ABSTRACTThis article presents the development of fabricator competency for engineering students in tertiary education during the seamless era. This study explored the approach to synthesizing, designing, and developing fabricator competency. The study identified six key components of fabricator competency: 1) Knowledge of materials, 2) Problem-solving and design, 3) Using design software, 4) Using hardware and machines, 5) Safety knowledge and awareness, and 6) Communication and publication. This study emphasizes the importance of human poten-tial development, specifically in the case of engineering students in tertiary education. A com-petency framework for a fabricator in the seamless era has been developed by synthesizing, designing, and developing fabricator competencies based on published research on fabrica-tor competency.

Srisawat, S., Wannapiroon, P., Nilsook, P. (2023). A Fabricator Competency for Engineering Students in Tertiary Education.
International Journal of Engineering Pedagogy (iJEP), 13(8), pp. 117–130.
https://doi.org/10.3991/ijep.v13i8.41653

Coordination Mechanisms and Systems to Enhance Thai Early Childhood Development Management Efficiency

Abstract

Objective: The study aimed to enhance the efficiency of Thai early childhood development management by developing coordination mechanisms and systems.

Theoretical framework: A mixed-methods approach was utilized, including an online structured interview of six ECDM policymakers, content analysis of the data, and four focus group discussions with ten individuals from various sectors.

Method: A draft handbook for coordination mechanisms and systems was processed using an online connoisseurship seminar, and an opinion questionnaire was collected from 200 executives and practitioners in four Thai regions using Google Forms.

Results and conclusion: The results identified four mechanisms for driving an effective early childhood development management coordination system: national, provincial, subdistrict, and coordination. These mechanisms comprised an information and communication technology system, a management system, a resource management system combined with budget planning, and a supervision, monitoring, and evaluation system. In conclusion, three stages of policy recommendations were proposed: urgent, intermediate, and long-term.

Implications of the research: The study provides valuable insights into how a developing nation in Southeast Asia can direct critical resources in developing early childhood management efficiency at all levels.

Originality/value: The study gives a unique insight into early childhood development management in a developing Southeast Asian nation and significantly contributes to the literature because of its uniqueness.

Werayut Chatakan, Phanagrid Boonpob, Nopparat Chairueang, Julalax Sutra, Naruporn Thitipraserth and Prachyanun Nilsook. (2023)
Coordination Mechanisms and Systems to Enhance Thai Early Childhood Development Management Efficiency. Tuijin Jishu/Journal of Propulsion Technology. Vol. 44 No. 5 (2023) ; pp.830-842.
https://www.propulsiontechjournal.com/index.php/journal/article/view/2699

Constructionism Imagineering Learning Model via Metaverse to Enhance Young Innovators

Abstract

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.

Suputtra Sapliyan, Pinanta Chatwattana & Prachyanun Nilsook (2023)
Constructionism Imagineering Learning Model via Metaverse to Enhance Young Innovators. Journal of Education and Learning; Vol. 12, No. 4; 2023 ; pp.81-91. (ERIC)
https://doi.org/10.5539/jel.v12n4p81

An Information Service Platform for Decision Support in Academic Admissions Using Data Fabrics and Artificial Intelligence

ABSTRACT

This paper presents the architecture of an information service platform for decision support in academic admissions, utilizing data fabrics and artificial intelligence. The factors affecting students’ further education can be classified into four main types: (1) the course, (2) image, (3) personal reasoning of the student, and (4) public relations. The process of providing information for decision support in academic admissions can be divided into six stages: (1) collecting information, (2) matching study guidance, (3) recommending appropriate education, (4) confirming information, (5) assessing student admissions, and (6) providing feedback. Data fabric is an increasingly popular technology application for data management. The data fabric architecture consists of six layers: (1) an augmented data catalog, (2) a knowledge graph enriched with semantics, (3) metadata activation, (4) a recommendation engine for active metadata, (5) data preparation and integration, and (6) orchestration and data operations. A smart decision support system (DSS) technology is used to assist in decision-making. The results showed that this architecture has an excellent level of suitability (mean = 4.56, standard deviation = 0.35). It can be applied to a university to help it become a digital university and align with its mission.

Tasatanattakool, P., Nongnuch, K., Wannapiroon, P., & Nilsook, P. (2023).
An Information Service Platform for Decision Support in Academic Admissions Using Data Fabrics and Artificial Intelligence.
International Journal of Interactive Mobile Technologies (iJIM), 17(21), pp. 34–49. https://doi.org/10.3991/ijim.v17i21.41757

Crystallized Intelligence Wisdom Repository Management System with a Conversational Agent

Abstract

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.

Mathuwan Srikong, Panita Wannapiroon & Prachyanun Nilsook (2023)
Crystallized Intelligence Wisdom Repository Management System with a Conversational Agent. International Education Studies, Vol. 16, No.2 (2023) ; p150-163.
https://doi.org/10.5539/ies.v16n2p150

The System Architecture of Intelligent Student Relationship Management Based on Cognitive Technology with Conversational Agent for Enhancing Student’s Loyalty in Higher Education

Abstract

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).

Nutthapat Kaewrattanapat, Panita Wannapiroon & Prachyanun Nilsook (2023) The System Architecture of Intelligent Student Relationship Management Based on Cognitive Technology with Conversational Agent for Enhancing Student’s Loyalty in Higher Education.
International Education Studies, Vol. 16, No.2 (2023) ; p103-116.
https://doi.org/10.5539/ies.v16n2p103

The Landscape of Digital Technology to Enhance the Digital Researcher

Abstract

The objectives of this research were to synthesize the competencies of the digital researcher, carry out an empirical investigation of the digital researcher landscape, and evaluate the results of a synthesis of digital researcher competency. To conduct the research, the researchers carried out a review of the literature related to researcher competency, digital competency, digital researcher competency and digital technology for researchers. Then, a focus group discussed the conclusion of the digital technology landscape used to enhance the digital researcher. The results showed that digital researchers’ competency had six features: 1) Personalize and Security Competency, 2) Literature Review and Reference Management Competency, 3) Communication and Collaboration Management Competency, 4) Analyzing and Reporting Competency, 5) Proofreading and Plagiarism Checking Competency, and 6) Publication Competency.

Siwaporn Linthaluek, Panita Wannapiroon & Prachyanan Nilsook (2023)
The Landscape of Digital Technology to Enhance the Digital Researcher.
International Education Studies, Vol. 16, No.2 (2023) ; p180-192
https://doi.org/10.5539/ies.v16n2p180