A secondary data analysis of SEAMs responses for programming and non-programming modules by gender

Osunde, Joseph and Dil, Anton (2018). A secondary data analysis of SEAMs responses for programming and non-programming modules by gender. In: The 7th eSTEeM Annual Conference 2018, 25-26 Apr 2018, Milton Keynes.


Gender disparity in computer science higher education has been tackled in a number of ways to include structural adjustments to teaching support and teaching contents. Most recently, studies have focused on the use of VLEs to influence gender disparities in university-level computer science courses. Open and distance learning institutions provide printed and online materials mostly as VLEs in the place of lectures in conjunction with computer-based activities, forums, television and radio programmes and student support provision such as face to face tutor sessions, tutor centres etc.
The empirical evidence suggests that learning environments that convey gender stereotypes significantly impact on the representation of women in these environments as it impacts on the interest and anticipated success in computer science.
The Open University delivers its courses online and blended instruction to include videos, forums, face to face sessions with tutors and tutor centres. A review of related literature about online and blended instruction validated the usefulness and effectiveness of each learning delivery format in relation to learning outcomes and learner satisfaction.
The enrolment statistics at The Open University indicates that more males than female are enrolled in the school of computing and communications and fewer women progress on to programming modules. In addition, the current data also suggests that there are no significant differences in the performance by gender for programming modules. However, are there differences in the virtual learner satisfaction by gender? Is there a correlation between virtual learner module satisfaction, teaching, assessment and learning and module content for programming and non-programming modules for both genders?
A secondary qualitative data analysis of The Open University student experience on a module survey (SEAMs) data between 2013 and 2016 of programming (M256 & M250) and non-programming modules (T227 & T215) are investigated in this study. A multi-variant review of Module Content and Teaching, Assessment & Learning were compared against Module Satisfaction by gender. The initial findings suggest that the module satisfaction rates are better for non-programing modules in comparison to programing modules for both genders. Furthermore, in most instances of the qualitative analysis, there was a correlation between all three multi-variant factors e.g. a positive linear relationship between module content and teaching, assessment & learning often indicated that the virtual learners were more satisfied with the module. Finally, the initial analysis also indicated that male virtual learners are more satisfied with the programming modules in comparison to the females. Future studies would further investigate the differences in the Module Content and Teaching, Assessment & Learning that could have resulted in the differences in the satisfaction rates by gender in modules.

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