Study of secondary school students' multiple intelligence areas (Malatya case)


AYDEMİR H., Karali Y.

ERPA International Congress on Education (ERPA), İstanbul, Türkiye, 6 - 08 Haziran 2014, cilt.152, ss.167-172 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 152
  • Doi Numarası: 10.1016/j.sbspro.2014.09.175
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.167-172
  • Anahtar Kelimeler: intelligence, multiple intelligences theory, intelligences area, individual difference, SEX-DIFFERENCES
  • İnönü Üniversitesi Adresli: Evet

Özet

General Purpose of this research is to identify dominant intelligence areas of students according to Multiple Intelligences Theory, and to look for the elements that may have impact on distribution of students to these intelligence areas. Research universe consists of 7th grade students studying at Malatya Central District secondary schools. Sample consists of 1198 7. Grade student selected via random selection method from above mentioned schools. Research is done by using screening pattern. Cepni's (2010) CokluZekaKuramiDegerlendirmeOlcegi", which was designed by utilizing Armstrong's (2009) self-assessment scale in his "Multiple Intelligence in the Classroom" book, has been used in data collection. According to the outcomes of the research distribution of students' area of intelligence is naturalistic intelligence at a significant level. Low-Mid level of significant correlation is identified between distribution of students' areas of intelligence and gender, educational status of father and family's monthly total income. It is concluded that there is no significant correlation between intelligence areas and mother's educational status, place of birth, number of siblings and profession of parents. Outcomes of the research are analyzed by using SPSS 20.0 for Windows. Since the parameters used in research are categorical, "Chi-Squared test for single sample" is used in identifying significant deviation between observed and expected values of intelligence area categories. On the other hand, "Chi-Squared test for two variables" is used in order to identify according to which independent variables the intelligence areas differentiate. (C) 2014 The Authors. Published by Elsevier Ltd.