TY - JOUR
T1 - An adaptive network model covering metacognition to control adaptation for multiple mental models
AU - Treur, Jan
PY - 2021/6
Y1 - 2021/6
N2 - Learning processes can be described by adaptive mental (or neural) network models. If metacognition is used to regulate learning, the adaptation of the mental network becomes itself adaptive as well: second-order adaptation. In this paper, a second-order adaptive mental network model is introduced for metacognitive regulation of learning processes. The focus is on the role of multiple internal mental models, in particular, the case of visualisation to support learning of numerical or symbolic skills. The second-order adaptive network model is illustrated by a case scenario for the role of visualisation to support learning multiplication at the primary school.
AB - Learning processes can be described by adaptive mental (or neural) network models. If metacognition is used to regulate learning, the adaptation of the mental network becomes itself adaptive as well: second-order adaptation. In this paper, a second-order adaptive mental network model is introduced for metacognitive regulation of learning processes. The focus is on the role of multiple internal mental models, in particular, the case of visualisation to support learning of numerical or symbolic skills. The second-order adaptive network model is illustrated by a case scenario for the role of visualisation to support learning multiplication at the primary school.
KW - Adaptive network model
KW - Control of adaptation
KW - Metacognition
KW - Rivera
UR - http://www.scopus.com/inward/record.url?scp=85099003028&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85099003028&partnerID=8YFLogxK
U2 - 10.1016/j.cogsys.2020.11.005
DO - 10.1016/j.cogsys.2020.11.005
M3 - Article
AN - SCOPUS:85099003028
SN - 1389-0417
VL - 67
SP - 18
EP - 27
JO - Cognitive Systems Research
JF - Cognitive Systems Research
ER -