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|Title: ||A Soft Computing Approach to Quality Evaluation of General Chemistry Learning in Higher Education|
|Authors: ||Figueiredo, Margarida|
|Editors: ||Caporuscio, M.|
De la Prieta, F.
Di Mascio, T.
Rodríguez, J. G.
|Keywords: ||General Chemistry|
Knowledge Representation and Reasoning
Artificial Neural Networks
|Issue Date: ||2016|
|Publisher: ||Springer International Publishing|
|Citation: ||Figueiredo, M., Neves, J. & Vicente, H., A Soft Computing Approach to Quality Evaluation of General Chemistry Learning in Higher Education. In M. Caporuscio, F. De la Prieta, T. Di Mascio, R. Gennari, J. G. Rodríguez & P. Vittorini, Eds., Methodologies and Intelligent Systems for Technology Enhanced Learning, Advances in Intelligent and Soft Computing, Vol. 478, pp. 81–89, Springer International Publishing, Cham, Switzerland, 2016.|
|Abstract: ||In contemporary societies higher education must shape individuals able to solve problems in a workable and simpler manner and, therefore, a multidisciplinary view of the problems, with insights in disciplines like psychology, mathematics or computer science becomes mandatory. Undeniably, the great challenge for teachers is to provide a comprehensive training in General Chemistry with high standards of quality, and aiming not only at the promotion of the student’s academic success, but also at the understanding of the competences/skills required to their future doings. Thus, this work will be focused on the development of an intelligent system to assess the Quality-of-General-Chemistry-Learning, based on factors related with subject, teachers and students.|
|Appears in Collections:||CIEP - Publicações - Capítulos de Livros|
QUI - Publicações - Capítulos de Livros
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