Factor analysis of social context of statistics learning within an IT environment between student genders

Abstract

Some research studies showed that male students held a more positive attitude to using computers for learning than their female counterparts, albeit some reported the other way around. Apparently, the issue of gender differences on students' views is controversial. A question which arises naturally is how the nature of underlying influences for social interaction when using Information Technology in statistics learning is affected by a student gender. Students were divided into small groups to work together in a computing laboratory to accomplish statistical tasks assigned by their teacher. Data were gathered from a questionnaire through personal interviews with the students. The data were summarised, using the factor analytic technique, into factors: co-learning with one another, students' attitudes towards collaborative learning, teacher's scaffolding assistance, collaborative interaction with learning partners, the significance of the teacher's intervention, students' control of their own learning process, etc. The data were further analysed by discriminant analysis. It turns out that knowledge construction through social interaction is the key factor influencing learning of male and female students. Interestingly, female students raised more concerns about the significance of a teacher's assistance in the learning process whereas male students were more serious about expectations regarding performance.