How the design and complexity of concept maps influence cognitive learning processes
Users: 2 - Average Rating: 5.00
The paper attracted me due to the interest of our consortium in using networks. Concept maps have this structure, where nodes are concepts and arcs provide the relation between them. The idea is a student (called learner) may be aided to understand the whole structure of a system b graphically ordering in 2D. Uf, I realise that I have been studying 55 years without creating a concept map. Apparently, visual ordering of concepts is not a great aid to me.
The paper basically reports experiments with students on material with the logical conclusion that if you make more mess out of the concept map, the student is getting more disoriented "significantly". The variables are to have less or more concept nodes and to place them more or less well organised, called salient. An interesting experiment, but the result des not surprise me in a Popperian sense.
The paper basically reports experiments with students on material with the logical conclusion that if you make more mess out of the concept map, the student is getting more disoriented "significantly". The variables are to have less or more concept nodes and to place them more or less well organised, called salient. An interesting experiment, but the result des not surprise me in a Popperian sense.
Type:
Scientific Paper
Area:
Data Analytics
Target Group:
Basic
DOI:
10.1007/s11423-022-10083-2
Cite as:
Krieglstein, F., Schneider, S., Beege, M. et al. How the design and complexity of concept maps influence cognitive learning processes. Education Tech Research Dev 70, 99–118 (2022)
Author of the review:
Eligius Hendrix
University of Malaga
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Andrej Košir
This paper includes useful hints for Learning indicators in terms of 1. Optimizing OptLearn algorithm 2. Evaluating OptLearn algorithms They are useful for OptLearn algorithms (versions of it) linked to Conceptual maps and also to those not related to it.Pablo Guerrero-Garcia
The added bonus of this paper is that it directly leads to two learning indicators (extrated from the graph structure and complexity, cf. more details in the Learning Indicators section of this iMath library), hence you can measure the learner cognitive state before using some (technological or not) learning tool/environment and after using it to check if there has been some improvement ;-)