Next Article in Journal
Autonomy-Supportive and Controlling Teaching in the Classroom: A Video-Based Case Study
Next Article in Special Issue
Concept Map and Knowledge
Previous Article in Journal
Considerations about Flip Education in the Teaching of Advanced Mathematics
Previous Article in Special Issue
The Role and Efficacy of Creative Imagination in Concept Formation: A Study of Variables for Children in Primary School
Article

Fundamental Issues of Concept Mapping Relevant to Discipline-Based Education: A Perspective of Manufacturing Engineering

Faculty of Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami 090-8507, Japan
Educ. Sci. 2019, 9(3), 228; https://doi.org/10.3390/educsci9030228
Received: 27 July 2019 / Revised: 22 August 2019 / Accepted: 26 August 2019 / Published: 29 August 2019
(This article belongs to the Special Issue Concept Mapping and Education)
This article addresses some fundamental issues of concept mapping relevant to discipline-based education. The focus is on manufacturing knowledge representation from the viewpoints of both human and machine learning. The concept of new-generation manufacturing (Industry 4.0, smart manufacturing, and connected factory) necessitates learning factory (human learning) and human-cyber-physical systems (machine learning). Both learning factory and human-cyber-physical systems require semantic web-embedded dynamic knowledge bases, which are subjected to syntax (machine-to-machine communication), semantics (the meaning of the contents), and pragmatics (the preferences of individuals involved). This article argues that knowledge-aware concept mapping is a solution to create and analyze the semantic web-embedded dynamic knowledge bases for both human and machine learning. Accordingly, this article defines five types of knowledge, namely, analytic a priori knowledge, synthetic a priori knowledge, synthetic a posteriori knowledge, meaningful knowledge, and skeptic knowledge. These types of knowledge help find some rules and guidelines to create and analyze concept maps for the purposes human and machine learning. The presence of these types of knowledge is elucidated using a real-life manufacturing knowledge representation case. Their implications in learning manufacturing knowledge are also described. The outcomes of this article help install knowledge-aware concept maps for discipline-based education. View Full-Text
Keywords: concept map; learning; semantic web; knowledge representation; epistemology concept map; learning; semantic web; knowledge representation; epistemology
Show Figures

Figure 1

MDPI and ACS Style

Ullah, A.S. Fundamental Issues of Concept Mapping Relevant to Discipline-Based Education: A Perspective of Manufacturing Engineering. Educ. Sci. 2019, 9, 228. https://doi.org/10.3390/educsci9030228

AMA Style

Ullah AS. Fundamental Issues of Concept Mapping Relevant to Discipline-Based Education: A Perspective of Manufacturing Engineering. Education Sciences. 2019; 9(3):228. https://doi.org/10.3390/educsci9030228

Chicago/Turabian Style

Ullah, AMM S. 2019. "Fundamental Issues of Concept Mapping Relevant to Discipline-Based Education: A Perspective of Manufacturing Engineering" Educ. Sci. 9, no. 3: 228. https://doi.org/10.3390/educsci9030228

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop