GENDER DIFFERENCES IN COMPUTER SCIENCE EDUCATION PRE-SERVICE TEACHERS’ PERFORMANCE IN GENERATIVE ARTIFICIAL INTELLIGENCE-ASSISTED LESSON PLANNING IN UNIVERSITIES IN NORTH-EAST NIGERIA

Abstract

The study examined gender differences in Computer Science Education pre-service teachers’ performance in Generative Artificial Intelligence (GAI)-assisted lesson planning in universities in North-East Nigeria. One research objective, one research question and one null hypothesis guided the study. Quasi-experimental research design, specifically the pretest-posttest non-equivalent control group design, was adopted for the study. The population of the study comprised 65 Year Three Computer Science Education pre-service teachers in the selected universities in the North-East. A sample of 63 participants was used for the study, comprising 41 pre-service teachers in the experimental group and 22 in the control group. The experimental group comprised 25 male and 16 female pre-service teachers, while the control group comprised 16 male and 6 female pre-service teachers. The Lesson Planning Performance Test (LPPT) was used for data collection. Experts in relevant fields validated the instrument. Its reliability was established through pilot testing involving Computer Science Education pre-service teachers from two non-participating universities. The reliability coefficient of LPPT was found to be 0.82. The experimental group was exposed to GAI-supported lesson planning, while the control group was taught using the conventional lesson-planning approach. Data collected were analysed using mean and standard deviation for answering the research question, while Analysis of Covariance (ANCOVA) was used to test the null hypothesis at 0.05 level of significance. The findings revealed that female pre-service teachers in the GAI experimental group recorded a slightly higher posttest performance mean score of 80.27 than their male counterparts, who recorded a mean score of 79.21, resulting in a mean difference of 1.06 in favour of the female pre-service teachers. However, the ANCOVA result showed that there was no statistically significant difference between the posttest performance mean scores of male and female pre-service teachers exposed to GAI-assisted lesson planning, in which F(1, 27) = 0.325, p > .05. The study concluded that gender did not significantly influence the performance of Computer Science Education pre-service teachers in GAI-assisted lesson planning. It was recommended among others, that teacher educators should provide equitable opportunities for male and female pre-service teachers to participate in GAI-assisted lesson-planning activities and ensure equal access to digital devices, reliable internet connectivity, training, and technical support.