Open AccessMultivariable Analysis Methods On Identifying Factors and Groups of Students in the Environment of the Discovery Learning/Constructivistic Approach Using Cognitive Tools
Author(s) -
Konstantinos Korres
Publication year - 2019
Publication title -
european journal of engineering research and science
Language(s) - English
Resource type - Journals
ISSN - 2506-8016
DOI - 10.24018/ejers.2019.0.cie.1289
Subject(s) - multivariable calculus , cognition , mathematics education , computer science , statistical analysis , machine learning , artificial intelligence , psychology , mathematics , statistics , engineering , control engineering , neuroscience
This paper studies the environment of the discovery learning/constructivistic approach using cognitive tools regarding students’ performance in tests involving different kinds of learning and in the final formal examinations and students’ attitudes towards the approach in Mathematics’ higher education. In particular the paper aims in identifying factors regarding students’ scores and attitudes affected by the approach and groups of students with similar characteristics based on these factors. Data was obtained by a study realized at the Department of Statistics and Insurance Sciences of the University of Piraeus, concerning the application of the discovery learning/constructivistic approach using Mathematica on the course Calculus (Functions of multiple variables). Multivariable analysis methods are used in the data analysis, in particular factor analysis in identifying factors and cluster analysis in identifying groups of students with similar characteristics, in combination with inferential statistics’ methods. The statistical package SPSS was used for the data analysis.