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SciGirls Code: Computational Participation and Computer Science with Middle School Girls

SciGirls Code is a project comprised of 16 STEM outreach programs that provided 160+ middle school girls with computational thinking (CT) and coding skills between September 2017June 2018. The research study investigates the ways in which these learning experiences impact girls’ development of CT; interest and attitudes toward computer science; and their understandings of how participation in creation with technology impacts themselves and the world around them. Utilizing a qualitative multi-site case study design, the study found that a connected learning approach boosted the development of girls’ CT skills, positively impacted attitudes towards computing pathways/careers, and increased understandings of computational participation. In addition, the educational experiences happening throughout the SciGirls Code program exemplifies the 4E learning model. Implications include how technology can be leveraged towards creating an inherently collaborative setting, acknowledging social, emotional, cultural, technological, and cognitive intersections in learning. Major issue addressed and potential significance Women remain significantly underrepresented in the STEM workforce within the United States, particularly computer science. Women constitute only 25% of the computing workforce despite it being the STEM area with the most demand (Pew Research Center, 2018). Notably, the number of women in computing occupations has actually declined over the past 25 years (Pew Research Center, 2018). While NCWIT (2017) reports that 1.1 million computing job openings are expected by 2024, men constitute 81% of the computer/information sciences degrees conferred in the 2015-2016 academic year. Although more bachelor’s degrees are conferred to women, computer/information sciences degrees make up only 1% of degrees conferred to women (NCES, 2017). The issues that contribute to the computer science pipeline deficits are complex, and they begin early. For example, in 2018 girls represented only 28% of AP Computer Science (CS) test-takers (www.code.org). While this represents a slight increase from 2017 (26%), it demonstrates a continued, dramatic discrepancy between genders. Girls in IT: The Facts (Ashcraft, Eger, & Friend, 2012), a summary of research regarding factors that contribute to the gender gap in computer science education, suggests these ongoing issues: 1) curriculum that is irrelevant; 2) pedagogies that discourage collaboration; 3) lack of opportunities to take risks and make mistakes; and 4) heavy reliance on lecturing instead of hands-on, project-based learning. Starting early with interventions that introduce girls to computer science in elementary and middle school can help increase interest in CS; cultivating early interest is paramount because interest in STEM fields in high school, rather than achievement in these areas, is more closely associated with pursuit of careers in computer science (Corbett & Hill, 2015). SciGirls Code is a project that aims to address the gender equity issue in the field of computer science by targeting middle school girls (Blikstein, 2018), which is the age when girls begin losing interest in STEM areas (Microsoft & KRC Research, 2018). SciGirls Code worked with 16 STEM outreach programs to provide 160+ middle school girls with computational thinking (CT) and coding skills within informal education spaces. The project theorized that a connected learning approach, which is based on sociocultural learning theory (Cole, 1998; Vygotsky, 1978), with the active support of trained educators and role models, would boost the development of middle school girls’ CT skills, attitudes towards computing pathways/careers, and understandings of how participation in technology creation impacts themselves and the world around them. Theoretical approaches Connected learning and computational participation The connected learning model advocates that “the most resilient, adaptive, and effective learning involves individual interest as well as social support to overcome adversity and provide recognition” (Ito et al., 2013, p.4). With an emphasis in meaningful practices and supportive connections with others, this model identifies three CSCL 2019 Proceedings 616 © ISLS contexts for learning: peer-supported, interest-powered, and academically-oriented. We applied connected learning in this project in order to understand how girls expanded their interest within production-focused CS activities and how they empowered their own learning within a gender-equitable, peer-supported environment. Connected learning, in combination with computational participation, anchors our project and its research agenda. Computational participation (CP) is explained as “connecting through making, which leads to deeper, richer, and healthier connections among online youth” (Kafai & Burke, 2014, p. 132). With sharing and collaboration at its core, CP is described as “solving problems with others, designing intuitive systems with and for others, and learning about the cultural and social nature of human behavior through the concepts, practices, and perspectives of computer science” (Kafai & Burke, 2014, p. 128). CP, therefore, represents a shift from the previous “individualistic view of computing” to a view that focuses on “sociological and cultural dimensions” (Fields, Kafai, & Giang, 2017, p.2). Kafai and Burke (2014) suggest that computer programming “represents a crucial beginning step”, “a form of expressing oneself”, and “a community practice” to approach CP (p. 128). Computational thinking Rooted in computer science, computational thinking (CT) is viewed as “a universally applicable attitude and skill” (Wing, 2006, p.33) that involves analytical thinking (Bers, 2018) and the process of problem-solving (ISTE, 2016). Bers (2018) argues, based on Papert’s (1980, 1999) earlier ideas of learning through making and “hard fun,” that CT is not only “involved problem solving, but also a notion of expression” (p.60). Operationally, this study’s research methods are grounded in a CT framework (Brennan & Resnick, 2012), which encompasses three dimensions: 1) concepts (e.g., sequence, loops), 2) practices (e.g., debugging, remixing, and 3) perspectives (e.g., expressing, connecting). We documented and assessed girls’ knowledge of computational concepts and abilities to employ them using computational practices.