Authors:
Maici Duarte Leite
1
;
Diego Marczal
2
and
Andrey Ricardo Pimentel
1
Affiliations:
1
Federal University of Paraná and UFPR, Brazil
;
2
Federal University of Paraná, UFPR, Federal Technology University of Paraná and UTFPR, Brazil
Keyword(s):
Multiple External Representations, Remediation of Math Errors, Learning Object.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Computer-Supported Education
;
e-Learning
;
e-Learning and e-Teaching
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Intelligent Agents
;
Internet Technology
;
Problem Solving
;
Software Agents and Internet Computing
;
Strategic Decision Support Systems
;
Tools, Techniques and Methodologies for System Development
;
Web Information Systems and Technologies
Abstract:
The proposition of error remediation is a widely used feature in Intelligent Tutoring Systems, but the use of Multiple External Representations to assist it, is a research subject. This paper presents (or discuss) the use of Multiple External Representations contribution in error remediation in Learning Objects. To perform this study, we present an architectural model, a conceptual framework for mathematical error classification and Multiple External Representations, using a cognitive remediation for errors. Following is presented the application of contextual remediation of error based on Multiple External Representations in a Learning Object. And finally, we present the performance of students during the application of an experiment consisting of the following steps: pre-test, test and post-test.