Fostering Interest in Computing With a Social Robotics Camp for Middle School–Aged Girls

• In Event: Perceptions of the Self, Social Identities, and STEM Fields: Influences on STEM Motivation and Participation

Abstract

Computing and computational thinking (CT) are now core competencies for a wide range of
work in the US (NAS, 2018). Computing education programs have increased access, but women are still participating at a lower rate than men (Code.org, 2020). Thus, there is a need to focus on designing these programs to develop long-lasting interest (Guzdial, 2019).

Theoretical Perspective

We created MyTurn, a social robotics camp for middle-school aged girls, derived from theory
that suggests belonging, value and knowledge building are key to developing interest in computing (Michaelis & Weintrop, 2022). The program provides mentored learning to build a sense of belonging, develops a computational learning tool to scaffold student learning, and uses social robots as an application to broaden student perspectives of computing that builds value.

Method

To test the impact of MyTurn on student interest in computing, we ran a one-week camp for 5th
and 6th grade girls (n=7) and 7th and 8th grade girls (n=9). Girls worked in pairs with women mentors, who were computer science majors, to design, create and program social robot interaction scenarios (e.g. service robots at a coffee shop, or home healthcare assistant robots). We collected video of student activity, daily situational interest surveys, post-camp interviews, and pre/post-camp Likert-style surveys of individual interest, belonging in computer science, interest in a computing career, and intention to pursue future computing learning. All items used a scale of 1 (strongly disagree) to 7 (strongly agree) and scores are reported as an average of items on each scale.

Results

In interviews, students described their experience as changing stereotypical beliefs about what
computing is like. They found that the work was social, creative, and collaborative, rather than the isolated programming that they had thought. Students felt the all-women environment fostered a community in computing that was a place they belonged in. Some students described the learning tool as an essential shared space to discuss and collaboratively plan the programming and interactions for their social robot. Finally, most students hadn’t previously considered pursuing CS but were now very interested. Survey results show significant increases and medium to large effect sizes (Cohen’s d) in individual interest from pre (M = 4.11, SD = 1.17) to post (M = 5.34, SD = 1.10, t(14) = 5.12, p = 0.0002, d= 1.08); interest in a computing career from pre (M = 4.11, SD = 0.82) to post (M = 5.44, SD = 1.03, t(14)= 4.26, p = 0.0004, d = 1.43); interest in more computing opportunities from pre (M = 4.65, SD = 1.44) to post (M = 5.53, SD = 1.03, t(14) = 2.57, p = 0.02, d = 0.70); and a sense of belonging from pre (M = 4.54,SD = 1.30) to post (M = 5.30, SD = 1.09, t(14) = 2.17, p = 0.047, d = 0.63).

Significance

We believe these results demonstrate how addressing stereotypes of what computing is (i.e.
social, creative, impactful to communities) with mentored and scaffolded learning can benefit interest in computing.

Authors

• Rabia Ibtasar, University of Illinois at Chicago
  Presenting Author

• Joseph E Michaelis, University of Illinois at Chicago
  Presenting Author