A case study of gender bias in students' handwriting in the Tamale Metropolis

Abstract

This study investigates gender bias in students' handwriting evaluation in the Tamale Metropolis in the Northern Region of Ghana. The study employed purposive, convenience, and simple random sampling for selecting students, as well as examiners. One-way ANOVA was used to examine the impact of different script levels on the identification of students’ gender based on their handwriting. The t-test was used to assess the impact of examiners’ level of experience in the identification of students’ gender based on their handwriting. Students’ gender was modelled using a binary logistic regression model. The study employed a test of proportion to estimate a cut-off for significant identification of gender by examiners. The study found that gender identification through handwriting becomes easier as students progress from basic through to tertiary education levels, with upper primary and tertiary level scripts being the least and most identified respectively. It was also revealed that only a few examiners demonstrate the ability to correctly identify students' gender based on their handwriting with a significant cut-off point of 65%. The study also found that the identification of students’ gender based on handwriting is influenced by the examiner's experience and script level. Finally, the binary logistic regression model showed that the estimated probability of accurate gender identification by examiners increases with the examiner's experience level. Further studies must use larger and more diverse handwriting samples, explore additional factors such as specific writing tasks and handwriting characteristics, and replicate the study in different contexts to enhance the generalizability of the study finding findings.