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Sosyal Bilimler Ogrencilerinde Matematik Kaygisi: Uzaktan Egitim ve Kampus Ogrencileri Uzerine Bir Uygulama

Author

Listed:
  • Muruvvet Pamuk

    () (Istanbul University)

  • Seda Karakas

    () (Istanbul University)

Abstract

Undergraduate students who are enrolled in social sciences programs, often have a negative perspective on mathematics courses. However, understanding these negative perspectives of students is necessary to help instructors in order to create a more positive attitude in such courses. The purpose of this study is to investigate the mathematics anxiety of the university students enrolled in on-campus and online education programs at the Faculty of Economics during 2010-2011 Academic Year. The sample used consists of the responses of 233 on-campus and 285 online students to “Mathematics Anxiety Rating Scale-Short Version (MARS-SV)”. Five anxiety factors for on-campus students and three anxiety factors for online students were identified by using factor analysis technique. Additionally, it was investigated whether mathematics anxiety variables differ according to the education type and gender.

Suggested Citation

  • Muruvvet Pamuk & Seda Karakas, 2011. "Sosyal Bilimler Ogrencilerinde Matematik Kaygisi: Uzaktan Egitim ve Kampus Ogrencileri Uzerine Bir Uygulama," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 14(1), pages 19-37, May.
  • Handle: RePEc:ist:ancoec:v:14:y:2011:i:1:p:19-37
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    File URL: http://eidergisi.istanbul.edu.tr/sayi14/iueis14m2.pdf
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    More about this item

    Keywords

    Mathematics Anxiety; Mathematics Anxiety Rating Scale-Short Version (MARS-SV); Factor Analysis;

    JEL classification:

    • A22 - General Economics and Teaching - - Economic Education and Teaching of Economics - - - Undergraduate
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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