Leveraging Survey and Motion Sensors Data to Promote Gender Inclusion in Makerspaces
Abstract: Over the last decade makerspaces have become more popular and prevalent in formal and informal learning environments. A finding, however, is that makerspaces are often male-dominated, and females can feel a sense of intimidation in the space. Furthermore, maker-centered learning typically adopts an open-ended structure which makes it difficult to identify students who are struggling. In this paper, we explore the use of quantitative data from survey and motion sensors to potentially assist instructors in uncovering gender differences and promoting gender inclusion. Results suggest that there are different pathways for male and female students to thrive in makerspaces. Based on survey results, male students tend to have higher self-efficacy, resulting in more self-confidence in their abilities and more positive feelings. Findings from applying network analysis on the motion sensor data show that female students persevere more consistently and use empathy to form closer ties with peers for mutual support. These findings suggest that quantitative data could help raise instructors’ awareness of gender differences and use that information to cater to the unique learning needs of each group of students. Overall, this work represents preliminary steps in instrumenting makerspaces to promote gender inclusion and support maker-centered learning.