Abstract
Women are still underrepresented in engineering courses although some German universities offer separate women’s engineering courses which include virtual STEM learning environments. To outline information about fundamental aspects relevant for virtual STEM learning, one has to reveal which similarities both genders in virtual learning show. Moreover, the question arises as to whether there are in fact differences in the virtual science learning of female and male learners. Working with virtual STEM learning environments requires strategic and arithmetic-operative competences. Even if we assume that female and male learners have similar competences levels, their correlational pattern of competences, motivational variables, and invested effort during virtual STEM learning might differ. If such gender differences in the correlations between cognitive and motivational variables and learning behavior were revealed, it would be possible to finetune study conditions for female students in a separate engineering course and shape virtual STEM learning in a more gender-appropriate manner. That might support an increase in the number of women in engineering courses. To reveal the differences and similarities between female and male learners, a field study was conducted with 56 students (female = 27, male = 29) as part of the Open MINT Labs project (the German term for Open STEM Labs, OML). The participants had to complete a virtual STEM learning environment during their regular science lessons. The data were collected with questionnaires. The results revealed that the strategic competences of both genders were positively correlated with situational interest in the virtual learning environment. This result shows the big impact strategic competences have for both genders regarding their situational interest. In contrast, the correlations between mental effort and competences differed between female and male participants. Especially female learners’ mental effort decreased if they had more strategic competences. On the other hand, female learners’ mental effort increased if they had more arithmetic-operative competences. All in all, female learners seem to be more sensitive to differences in their strategic and arithmetic-operative competences regarding their mental effort. These results imply that the implementation of separate women’s engineering courses could be an interesting approach.
Highlights
Students differ in their preferences for specific subjects and these differences seem to be partly correlated with gender (Buse and Bilimoria, 2014)
We computed the correlations between the four variables mental effort, situational interest, strategic competences, and arithmetic-operative competence
We examined the female and male learners’ differences for the variables mental effort, situational interest, strategic competences, and arithmetic-operative competences
Summary
Students differ in their preferences for specific subjects and these differences seem to be partly correlated with gender (Buse and Bilimoria, 2014). Recent research revealed that such cognitive differences changing; the data depending on different tasks characteristics (Miller and Halpern, 2014). Recent research has indicated that such an essentialist view of social categories such as gender is highly problematic as it presupposes the existence of natural, clear-cut categories with relatively time-stable properties. It has proved difficult to replicate studies on gender differences in the functional organization of brain regions related to specific cognitive skills, which implies that research findings on this issue need to be reflected very carefully (Rippon et al, 2014). Contrary to the assumption of essential differences, Hyde recently concluded from a metaanalysis of gender-specific studies that “male and females are similar on most, but not all psychological variables” Contrary to the assumption of essential differences, Hyde recently concluded from a metaanalysis of gender-specific studies that “male and females are similar on most, but not all psychological variables” (Hyde, 2005, p. 581); this resulted in the formulation of a gender similarity hypothesis
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