gender differences

Academic self-concept in science

LAIDReference. Jansen, M., Schroeders, U., & Lüdtke, O. (2014). Academic self-concept in science: Multidimensionality, relations to achievement measures, and gender differences. Learning and individual differences, 30, 11–21. 10.1016/j.lindif.2013.12.003

Abstract. Students‘ academic self-concept is a good predictor of academic achievement and a desirable educational outcome per se. In this study, we take a closer look at the nature of the academic self-concept in the natural sciences by examining its dimensional structure, its relation to achievement, and gender differences. We analyzed data from self-concept measures, grades and standardized achievement tests of 6036 German 10th graders across three science subjects – biology, chemistry, and physics – using structural equation modeling. Results indicate that (a) a 3-dimensional, subject-specific measurement model of the self-concept in science is preferable to a 1-dimensional model, (b) the relations between the self-concept and achievement are substantial and subject-specific when grades are used as achievement indicators, and (c) female students possess a lower self-concept in chemistry and physics even after controlling for achievement measures. Therefore, we recommend conceptualizing the self-concept in science as a multidimensional, subject-specific construct both in educational research and in science classes.

Computer usage questionnaire: Structure, correlates, and gender differences

Computers in Human BehaviorReference. Schroeders, U., & Wilhelm, O. (2011). Computer usage questionnaire: Structure, correlates, and gender differences. Computers in Human Behavior, 27, 899–904. doi: 10.1016/j.chb.2010.11.015

Abstract.Computer usage, computer experience, computer familiarity, and computer anxiety are often discussed as constructs potentially compromising computer-based ability assessment. After presenting and discussing these constructs and associated measures we introduce a brief new questionnaire assessing computer usage. The self-report measure consists of 18 questions asking for the frequency of different computer activities and software usage. Participants were N = 976 high school students who completed the questionnaire and several covariates. Based on theoretical considerations and data driven adjustments a model with a general computer usage factor and three nested content factors (Office, Internet, and Games) is established for a subsample (n = 379) and cross-validated with the remaining sample (n = 597). Weak measurement invariance across gender groups could be established using multi-group confirmatory factor analysis. Differential relations between the questionnaire factors and self-report scales of computer usage, self-concept, and evaluation are reported separately for females and males. It is concluded that computer usage is distinct from other behavior oriented measurement approaches and that it shows a diverging, gender-specific pattern of relations with fluid and crystallized intelligence.