Give or keep A transactive memory approach to understanding knowledge hoarding on the organisational digital knowledge repository

2020 ◽  
Vol 11 (1) ◽  
pp. 41
Author(s):  
Chunke Su
Keyword(s):  
Transactive Memory ◽  
Knowledge Repository ◽  
Knowledge Hoarding ◽  
Digital Knowledge

scholarly journals The Development of a MOOCs Knowledge Repository System Using a Digital Knowledge Engineering Process to Enhance Digital Entrepreneurs’ Competencies

2021 ◽  
Vol 11 (6) ◽  
pp. 85-101
Author(s):  
Nattaphol Thanachawengsakul ◽  
Panita Wannapiroon
Keyword(s):  
Human Performance ◽  
Knowledge Engineering ◽  
Small And Medium Enterprises ◽  
Competency Assessment ◽  
Engineering Process ◽  
Significance Level ◽  
Knowledge Repository ◽  
Digital Knowledge ◽  
Dependent Sample ◽  
Medium Enterprises

The objectives of this research were as follows: the development of a MOOCs knowledge repository system using a digital knowledge engineering process, and a competency assessment of digital entrepreneurs engaging in a MOOCs knowledge repository system using a digital knowledge engineering process. A total of 30 people were selected as a sampling group (purposive sampling) for this study, these included Small and Medium Enterprises (SMEs) in Bangkok with expertise in Human Performance Technology (HPT), as well as the MOOCs knowledge repository system. The mean, standard deviation, percentage, and a dependent sample t-test were used in the procedure for data analysis. The research findings suggested that: (1) the overall result concerning the development of a MOOCs knowledge repository system using a digital knowledge engineering process was at the highest level (Mean = 4.89, S.D. = 0.31), and (2) the overall result regarding the competencies of digital entrepreneurs after engaging in a MOOCs knowledge repository system using a digital knowledge engineering process passed the 80% rating, according to criteria. Moreover, learners who had undertaken activities through a MOOCs knowledge repository system using a digital knowledge engineering process improved their learning outcomes with a significance level of .05 based on the research hypothesis.

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

2019 ◽  
Vol 14 (12) ◽  
pp. 42 ◽  
Author(s):  
Nattaphol Thanachawengsakul ◽  
Panita Wannapiroon ◽  
Prachyanun Nilsook
Keyword(s):  
Machine Learning ◽  
Software Engineering ◽  
System Architecture ◽  
Management System ◽  
Knowledge Engineering ◽  
Research Approach ◽  
Storage Unit ◽  
Knowledge Repository ◽  
Application Service ◽  
Digital Knowledge

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.

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

2021 ◽  
Vol 11 (1) ◽  
pp. 35
Author(s):  
Nattaphol Thanachawengsakul ◽  
Panita Wannapiroon
Keyword(s):  
Learning Outcomes ◽  
Learning Process ◽  
Knowledge Engineering ◽  
Learning Activities ◽  
Instructional Tools ◽  
Knowledge Repository ◽  
Learning Ecosystem ◽  
Digital Knowledge ◽  
Further Development

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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