USING BAYESIAN NETWORKS TO UNDERSTAND RELATIONSHIPS AMONG MATH ANXIETY, GENDERS, PERSONALITY TYPES, AND STUDY HABITS AT A UNIVERSITY IN JORDAN

<p style="text-align: justify;">Mathematics is the foundation of all sciences, but most students have problems learning math. Although students’ success in life related to their success in learning, many would not take a math course unless it is their university’s core requirements....

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Bibliographic Details
Main Author: Linda Smail
Format: Article
Language:English
Published: Sriwijaya University 2016-12-01
Series:Journal on Mathematics Education
Online Access:http://ejournal.unsri.ac.id/index.php/jme/article/view/3405
Description
Summary:<p style="text-align: justify;">Mathematics is the foundation of all sciences, but most students have problems learning math. Although students’ success in life related to their success in learning, many would not take a math course unless it is their university’s core requirements. Multiple reasons exist for students’ poor performance in mathematics, but one prevalent variable worth consideration is the personality type. This work seeks to uncover relationships, if any, between students’ math anxiety and the students’ learning type in learning math and preparing for exams and tests. We use Bayesian networks to link those different variables and detect possible relationships among these variables. The data was obtained from population of 468 students during spring in 2009 at a U.S. institution in Jordan. Not many researches have been performed in the area of math study and personality types so we undertook this study to add to this area of knowledge. The study reveals that math anxiety related to gender, personality type, and study habits among this group of university students.</p> <p style="text-align: justify;"><strong>Keywords</strong>: Mathematics Anxiety, MBTI, Personality Types, Bayesian Networks</p><p style="text-align: justify;"> </p><p style="text-align: justify;"><strong>DOI</strong>: <a href="http://dx.doi.org/10.22342/jme.8.1.3405.17-34" target="_blank">http://dx.doi.org/10.22342/jme.8.1.3405.17-34</a></p>
ISSN:2087-8885
2407-0610