Year: 2004
Type: article
Abstract: Intellectual expertise means knowledge and ability that a person has that allows them to solve complex problems.It is important to understand how people become experts so that we can improve educational strategies, and help learners achieve their full academic potential.Unfortunately, the process of acquiring intellectual expertise is not well understood.Artificial neural networks (ANNs) have already been successful in modeling other types of human learning.This paper shows that they can also be trained as a model of expert human learning, and address many of the difficulties found in trying to study expertise in humans.The results confirm three hypotheses: (1) An artificial neural network can be used as a model to investigate how people learn under different training scenarios;(2) Different methods for delivering the training material result in different final performance; (3) The best performance is achieved by incrementally increasing the complexity of the material.These results provide educators with computational evidence that structured, integrated delivery methods are better for learners than oversimplification and isolation of learning tasks.
Institution: The University of Texas at Austin
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W1952765317