Abstract
There is a strong need for a more equal gender balance within the computing field. In 1998, Richard A. Lippa [29] uncovered a relationship between gender and preference within the People–Things spectrum, with women preferring People-oriented activities to a higher degree than men. The aim of this paper is twofold. First of all, we wish to determine if a similar relation can be established in the particular context of computing educational activities. Second of all, we wish to see if Lippa’s findings can be extrapolated to contemporary high-school students. To do that, we designed and conducted an experiment involving around 500 Danish high-school students who have been asked to choose between a People-themed version vs an isomorphic Things-themed version of four activities representative for computing education. The results show that the odds of a woman preferring a task involving People is 2.7 times higher than those of a man. The odds of a student without prior programming experience preferring a task involving People is 1.4 times higher than those of a student with programming experience. If we compare women without programming experience to men with programming experience the effect is even more pronounced; indeed, the combined effect is 3.8 (2.7 × 1.4). Our study implies a recommendation for computing educators to, whenever possible, favor educational activities involving People over Things. This makes educational activities appeal more to female students (and to students without programming experience), while not making a difference for male students (or students with programming experience). Since the experiment measured only the appeal of tasks (the users were not expected to perform them) the results we obtained can be useful for recruitment processes where the overall image and appeal of material makes a difference.
Original language | English |
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Title of host publication | Proceedings of the 17th ACM Conference on International Computing Education Research (ICER 2021) |
Publisher | Association for Computing Machinery |
Publication date | 17 Aug 2021 |
Pages | 127–144 |
ISBN (Electronic) | 9781450383264 |
DOIs | |
Publication status | Published - 17 Aug 2021 |
Keywords
- Gender Balance in Computing
- People–Things Spectrum
- Computing Education
- High-school Students
- Preference and Programming Experience