Object's details: Gender differences in the predictive validity of student achievement indicators from lower secondary school

Description

• Title:
  Gender differences in the predictive validity of student achievement indicators from lower secondary school
• Creator:
  Świst, Karolina
   ;
  Skórska, Paulina
• Publisher:
  Educational Research Institute
• Date:
  2016
• Abstract:
  In this article, we discuss the gender differences in the predictive validity of students’ Matura results. We use the achievement indicators (school grades, grade point average and standardized exam results) from lower secondary school as predictors of success on the Matura exams. Due to a number of psychological, socio-cultural and other factors, achievement indicators may function differentially according to gender. Thus, we hypothesize that the predictive validity itself may differ for girls and boys. We analyzed two cohorts of students – the first one took the exam at the end of lower secondary school in 2011 and the Matura in 2014, the second one took its exams in 2012 and 2015. We conducted the analysis using hierarchical linear modeling and ability level estimated within the IRT paradigm. The results show the differential functioning of achievement indicators according to gender and domain tested (mathematics and literacy). Combining exam results and school grades is the best strategy to predict the Matura’s results; however, the differences in the predictive validity between girls and boys is negligible.
• Bibliographic citation:
  Edukacja. 2016, 4 (139)
• Subject and Keywords:
  educational research
   ;
  predictive validity
   ;
  gender
   ;
  hierarchical linear modeling
   ;
  grading
• Coverage:
  21st century
• Language:
  pol
• Rights: Creative Commons BY 4.0
• Resource Type:
  article
• Format:
  application/pdf
• Resource Identifier: oai:jbc-test.dlibra.psnc.pl:409146
• ISSN:
  0239-6858

Object is located in the collections:

Additional information

• Creation date: 2017-10-19
• Last modification date: 2021-10-26
• Content object's number of views: 35
• You could also download the object's description in these formats:
  RDF
   ;
  OAI-PMH