The coherence and connectivity of such knowledge representations is known to be closely related to knowledge production, acquisition and processing. In this study we use network theory in making the clustering and cohesion of concept maps measurable, and show how the distribution of these properties can be interpreted through the Maximum Entropy (MaxEnt) method. This approach allows to introduce new concepts of the “energy of cognitive load” and the “entropy of knowledge organization” to describe the organization of knowledge in the concept mapsPeer reviewe
Concept learning and organization are much studied in artificial intelligence and cognitive psycholo...
The Kohonen Self-Organizing Map (SOM) is an unsupervised learning technique for summarizing high-dim...
Abstract Digital knowledge maps are rich sources of information to track students ’ learning. Howeve...
The coherence and connectivity of such knowledge representations is known to be closely related to k...
We present three new standardised network concept map (CM) measures that can provide unique informat...
Abstract Concept maps, which are network-like visualisations of the inter-linkages between concepts,...
Learning scientific knowledge is largely based on understanding what are its key concepts and how th...
A growing community of researchers applies the concept map for elicitation and representation indivi...
Many assume that the quality of students’ content knowledge can be connected to certain struct...
Concept maps are assumed to enhance learning as their inherent structure makes relations between inf...
ABSTRACT. A characteristic feature of scientific knowledge is the high degree of coherence and conne...
This study examined variation in the organization of domain‐specific knowledge by 50 Year‐12 chemist...
grantor: University of TorontoConcept maps are said to represent mental models of problems...
Conceptual change theories assume that knowledge structures grow during the learning process but als...
A growing community of researchers applies the concept map for elicitation and representation indivi...
Concept learning and organization are much studied in artificial intelligence and cognitive psycholo...
The Kohonen Self-Organizing Map (SOM) is an unsupervised learning technique for summarizing high-dim...
Abstract Digital knowledge maps are rich sources of information to track students ’ learning. Howeve...
The coherence and connectivity of such knowledge representations is known to be closely related to k...
We present three new standardised network concept map (CM) measures that can provide unique informat...
Abstract Concept maps, which are network-like visualisations of the inter-linkages between concepts,...
Learning scientific knowledge is largely based on understanding what are its key concepts and how th...
A growing community of researchers applies the concept map for elicitation and representation indivi...
Many assume that the quality of students’ content knowledge can be connected to certain struct...
Concept maps are assumed to enhance learning as their inherent structure makes relations between inf...
ABSTRACT. A characteristic feature of scientific knowledge is the high degree of coherence and conne...
This study examined variation in the organization of domain‐specific knowledge by 50 Year‐12 chemist...
grantor: University of TorontoConcept maps are said to represent mental models of problems...
Conceptual change theories assume that knowledge structures grow during the learning process but als...
A growing community of researchers applies the concept map for elicitation and representation indivi...
Concept learning and organization are much studied in artificial intelligence and cognitive psycholo...
The Kohonen Self-Organizing Map (SOM) is an unsupervised learning technique for summarizing high-dim...
Abstract Digital knowledge maps are rich sources of information to track students ’ learning. Howeve...