An agent-based model for teaching–learning processes.
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Date
2020
Authors
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Publisher
Universidad de Concepción.
Abstract
This paper presents an agent-based model for describing the increase the knowledge by
accumulating the information needed to complete a learning task or objectives, based
on phenomena studied by behavioral and learning scientists. From the simulations,
the average increase rate in knowledge, the skewness and kurtosis of knowledge
distributions, and grade distributions are determined. These tools make it possible to
evaluate the efficiency of teaching strategies and the performance of learning in the
classroom. The present model significantly reproduces the phenomenology obtained in
Bordogna and Albano (2001), showing first and second-order phase transitions and the
temporal dynamics of knowledge. Furthermore, the results of our model allow us to built
a gas model analogy. Some of the study cases show characteristics of systems far from
the state of thermodynamic equilibrium. This allows us to use the known techniques
from gas models to interpret the dynamics of the simulated learning process. The
presented model does not describe the teaching–learning process in all its complexity.
We use a simple behavioral characteristic of the persons, namely, the inattentional
private experience. However, it allows us to prove learning strategies to optimize the
learning process. Also, this model is a starting point to propose new models with more
elements from neuroscience and sociophysics to study in greater depth the dynamics of
the classroom.
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Keywords
Enseñanza Aprendizaje, Sociofísica, Sistemas Multiagente, Sistemas Complejos