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

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

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

ABSTRACT
The research aims to redesign and develop the Imagineering MOOC Instructional Design model (I-MOOC ID model) to enhance creative thinking and creative health media innovation. The exploratory sequential design mixed-method research method was used, and it was
divided into three phases: (1) investigation and synthesis of the composition of the I-MOOC ID model based on qualitative research methods by using scoping reviews; (2) redesign and validation of the I-MOOC ID model based on quantitative research methods through measurement of items with the Content Validity Index (CVI); and (3) assessment of the suitability of the I-MOOC ID model based on quantitative research methods. The findings indicate that:
(1) The I-MOOC ID model is composed of five compositions: 1) educational stakeholders; 2) the Imagineering learning experience cycle, which consists of nine steps: inspire, imagine, design, develop, present, publish, improve, evaluate, and reflect; 3) the MOOC learning platform;
4) the course syllabus; and 5) authentic assessment; (2) The I-MOOC ID model has five main processes and 16 sub-processes; and (3) The experts agreed with the overall model in terms of the instructional design based on integrating technological pedagogical content knowledge (TPACK) in the digital age to develop learners’ learning outcomes and rated the suitability of the model as most suitable, with a combined mean of 4.72. The standard deviation was 0.47.
KEYWORDS
Imagineering, MOOC, Instructional Design model, creative thinking, creative health media innovation

Nittayathammakul, V., Rattanasak, S., Wannapiroon, P., Nilsook, P., Arora, R., Thararattanasuwan, K. (2023). Imagineering MOOC Instructional Design Model to Enhance Creative Thinking and Creative Health Media Innovation. International Journal of Emerging Technologies in Learning (iJET), 18(19), pp. 84–102. https://doi.org/10.3991/ijet.v18i19.38129

ABSTRACT: The constructionist, imagineering learning system with the metaverse (CILM) is a tool that was designed to promote self-directed learning in both the virtual and physical world. In the metaverse world, users must simulate themselves into avatars to access the system, so they can learn by doing and present their works by means of virtual
technology. This study is based mainly on the concepts related to technologies and platforms in the virtual world, as well as teaching platforms in the new normal era in Thailand. The aim is to facilitate continuous learning anywhere and anytime by making the ultimate use of existing technologies in education management in Thailand, and to pave ways for young innovators in the digital age. The results of this study indicate that the CILM is an efficient tool to promote learning through the virtual world, and that young learners capable of creating innovations can work and add new knowledge to that space that can be further utilised or transferred to others. Furthermore, the system can increase the learning achievement of its users thanks to the application of digital technologies and tools that satisfy the needs of learners.

Suputtra Sapliyan, Pinanta Chatwattana & Prachyanun Nilsook (2023)
A constructionist, imagineering learning system with the metaverse: a study of learning outcomes at secondary schools in Thailand.
Global Journal of Engineering Education. Vol. 25, No.2 (2023) ; pp 90-98.
http://www.wiete.com.au/journals/GJEE/Publish/vol25no2/05-Chatwattana-P.pdf

Abstract

The total learning experience (TLE) model on the cloud with an intellectual repository is a tool that can be employed to promote limitless self-learning by means of active learning. In this model, learners are encouraged to have real experiences and face challenges leading to the creation of new knowledge and enrichment of their existing knowledge. This model can also be applied in other contexts, which can be done by integrating the concepts of technologies and new platforms offering experience-based instruction to create new ways of instructional design. Moreover, the model can be utilised in the current instruction management approach that usually focuses on continuous learning with the aid of technology. The results of this research can be used as a guideline for the design and development of the TLE system using an intellectual repository, which encourages experiential learning and generates new knowledge through self-learning with the aid of digital technology. In addition, this kind of learning promotes the exchange of knowledge through on-line social networks, thus contributing to the development of digital empathy and literacy skills, and the creation of a learning society. © WIETE 2022.

Author keywords

digital empathy; intellectual repository; literacy skills; Total learning experience on the cloud

Chatwattana, P., Piriyasurawong, P., Nilsook, P., & Wannapiroon, P. (2023). Total learning experience (TLE) on the cloud with an intellectual repository to enhance digital empathy and literacy skills. Global Journal of Engineering Education, 24(3), 193-201.

http://www.wiete.com.au/journals/GJEE/Publish/vol24no3/04-Chatwattana-P.pdf