Knowledge engineering management system on cloud technology for externship students

Anupan, Anuchit; Nilsook, Prachyanun; Wannapiroon, Panita

doi:10.1109/tale.2016.7851826

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…Moreover, the score results were arranged in the same group; thus, this study can be applied to the future development of a MOOCs knowledge repository system to enhance digital entrepreneurs' competencies in relation to knowledge, skills, and attitudes [14]. This is consistent with the concepts of Farquhar [15] Anupan, A., Nilsook, P., and Wannapiroon, P. [16], and Thanachawengsakul, N., Wannapiroon, P., and Nilsook. P. [17] "knowledge engineering process can be applied to learning and teaching management in educational institutions alongside digital technology and instructional tool [18] engaging learners in online collaboration activities through e-learning system and MOOCs learning system with its resources and elements helping learners to develop their learning progress", which is consistent with Gamage Perera and Fernando's concept of [19] and Hanif, A., Siddiqi, A, F., and Jalil, Z.…”

Section: Discussionsupporting

confidence: 68%

Development of a Learning Ecosystem Using Digital Knowledge Engineering Through MOOCs Knowledge Repository System

Thanachawengsakul¹,

Wannapiroon²

2021

Int. J. Eng. Ped.

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This paper presents the development of a learning ecosystem using digital knowledge engineering through a MOOCs knowledge repository system. This system comprises four parts: (1) Stakeholders, including instructors and learners; (2) A digital knowledge engineering learning process that describes the roles of instructors and learners, learning activities, and instructional tools; (3) A MOOCs knowledge repository system, which is the software de-veloped to enhance digital entrepreneurs’ competencies; and (4) Digital entrepreneurs’ competencies, which describe learning outcomes using the digital knowledge engineering learning process. The suitability of the learning ecosystem was assessed by twelve experts possessing at least three years of related experience. They judged its suitability to be at the highest level. This study can be used to support further development of the MOOCs knowledge repository system assess digital entrepreneurs’ competencies according to digital knowledge engineering learning process.

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Section: Discussionsupporting

confidence: 68%

Development of a Learning Ecosystem Using Digital Knowledge Engineering Through MOOCs Knowledge Repository System

Thanachawengsakul¹,

Wannapiroon²

2021

Int. J. Eng. Ped.

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“…In fact, technology is integrated into everything, resulting in a digital service based on intelligent systems. Stepping into the digital world, HEIs need to be driven by advanced information technology to streamline workflows [2] [3]. Not only does technological innovation have an important role to play in HEIs, but it also focuses on innovative strategies and information technology designed for dealing with new innovations which promote added value within HEIs.…”

Section: Introductionmentioning

confidence: 99%

Asset Supply Chain Management System-based IoT Technology for Higher Education Institutions

2019

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The purpose of this research is to design and develop an asset supply chain management system-based IoT technology for Higher Education Institutions (HEIs). Although nowadays there are computer-based asset information management systems, the problem is that such a system cannot immediately monitor the status of the asset. There is some information that is not related to reality, including a lack of asset movement records and information as to the status of each asset, which could lead to the mistake in terms of the working process which is unable to control and monitor a situation. Therefore, this re-search applied the concept of supply chain management (SCM) and IoT tech-nology in order to unsure good governance on the part of HEIs. This research is focused on durable articles and the use of a Near Field Communication (NFC) tag to communicate and exchange information with NFC-compatible smartphones. In this case, it can identify and monitor the asset under considera-tion and also assess associated information from any device. This solution can increase efficiency and value in terms of the organization. Moreover, the design diagram of the system leads to the development of asset supply chain manage-ment system (ASCMS)-based IoT technology for HEIs. The evaluation of the performance of this technology shows that the system operates at a great level, and that ASCMS-based IoT technology for HEIs it can be applied to ensure the good governance of such institutions. In addition, this research can serve the in-ternal organizational administration of Thai HEIs, involving dealing with working processes in line with real-life situations, relating to budget management, organizational working behaviors, and service users’ requirements. All of these aspects are analyzed based on good governance, including the rules of law, transparency and values.

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“…This means that this study can be applied to future developments of the KRMS-SWE and tested on undergraduates. This corresponds with the theories of Chang and Zhang [17], Anupan [18], Anupan, Nilsook and Wannapiroon [19] and Chotijiraphan [20]. It comprises four components as follows:…”

Section: Discussionmentioning

confidence: 93%

The Knowledge Repository Management System Architecture of Digital Knowledge Engineering using Machine Learning to Promote Software Engineering Competencies

Thanachawengsakul¹,

Wannapiroon²,

Nilsook³

2019

Int. J. Emerg. Technol. Learn.

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The knowledge repository management system architecture of digital knowledge engineering using machine learning (KRMS-SWE) to promote software engineering competencies is comprised of four parts, as follows: 1) device service, 2) application service, 3) module service of the KRMS-SWE and 4) machine learning service and storage unit. The knowledge creation, storage, testing and assessing of students’ knowledge in software engineering is carried out using a knowledge verification process with machine learning and divided into six steps, as follows: pre-processing, filtration, stemming, indexing, data mining and interpretation and evaluation. The overall result regarding the suitability of the KRMS-SWE is assessed by five experts who have high levels of experience in related fields. The findings reveal that this research approach can be applied to the future development of the KRMS-SWE.

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Knowledge engineering management system on cloud technology for externship students

Cited by 4 publications

References 5 publications

Development of a Learning Ecosystem Using Digital Knowledge Engineering Through MOOCs Knowledge Repository System

Development of a Learning Ecosystem Using Digital Knowledge Engineering Through MOOCs Knowledge Repository System

Asset Supply Chain Management System-based IoT Technology for Higher Education Institutions

The Knowledge Repository Management System Architecture of Digital Knowledge Engineering using Machine Learning to Promote Software Engineering Competencies

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