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Fig 1.

Overview of the introduced second-order adaptive network architecture.

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Fig 1 Expand

Table 1.

Types of states in the introduced three level network architecture.

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Table 1 Expand

Table 2.

Types of connections in the introduced adaptive network architecture.

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Table 2 Expand

Fig 2.

Connectivity for part of the second-order adaptive network model.

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Fig 2 Expand

Fig 3.

Connectivity for the complete adaptive network model.

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Fig 3 Expand

Table 3.

Explanation of the base level states for the mental model within the network model.

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Table 3 Expand

Table 4.

Explanation of the first-order self-model states for the mental model learning in the network model.

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Table 4 Expand

Table 5.

Explanation of the first-order self-model states for the instructor’s Information States in the network model.

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Table 5 Expand

Table 6.

Explanation of the second-order self-model states for control of the mental model learning in the network model.

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Table 6 Expand

Fig 4.

Dynamics of the base states X1-X14 showing internal simulation of the mental model.

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Fig 4 Expand

Fig 5.

Base states X6 (Clutch-on) and X7 (Gearbox-neutral) with impact from OS-states X20, X21 and LW-state X45, RW-state X46 and learner IW-state X44 and instructor IS-state X85 with control by CIW-state X102.

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Fig 6.

All control CIW-states showing impact from the corresponding observational learning LW-states.

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Fig 7.

All control CIW-states showing their impact on the corresponding instructional learning IW-states.

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Table 7.

Equilibrium analysis results for the IW-states.

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Table 7 Expand

Table 8.

Equilibrium analysis results for the RW-states.

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Table 8 Expand