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Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors (2021)

Chapter: 3 How Learning Happens in Authentic Experiences for Computing

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Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
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Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
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Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
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Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
×
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Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
×
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Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
×
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Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
×
Page 35
Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
×
Page 36
Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
×
Page 37
Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
×
Page 38
Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
×
Page 39
Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
×
Page 40
Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
×
Page 41
Suggested Citation:"3 How Learning Happens in Authentic Experiences for Computing." National Academies of Sciences, Engineering, and Medicine. 2021. Cultivating Interest and Competencies in Computing: Authentic Experiences and Design Factors. Washington, DC: The National Academies Press. doi: 10.17226/25912.
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Page 42

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

3 How Learning Happens in Authentic Experiences for Computing Many types of experiences in a young person’s life contribute to whether they later exhibit interest or competence in computing. These experiences can be formal or informal and can involve exposure to individuals who will help shape the relationship that a young person will later have to computing. Messages will also be communicated in both explicit and tacit ways to a young person, which they internalize about how well suited they are for a future in computing. Larger systemic factors, such as the availability of educational programs, technologies, courses, and skilled educators, also play a role. Prior consensus reports established the groundwork for the ways these influences apply to science and to STEM education broadly (e.g., see National Research Council [NRC], 1999, 2009; National Academies of Sciences, Engineering, and Medicine [NASEM], 2018b). In this chapter, the committee presents a learning and development framework for understanding the many influences on a young person’s choice to pursue computing, and the factors that place them in a position to be receptive to these influences, whether it is through advanced study, active participation in computing practices, or career. The chapter begins with a discussion of this framework, which articulates the underlying learning and development processes that are revealed in existing theories and conceptual models. Following this, the committee further elaborates on the framework, looking at both “internal” and “external” factors. The committee begins by describing the “internal” psychological and individual influences relevant to authentic experiences; in particular, interest (which can be both an outcome and an individual mediator) and competencies for computing. The committee then delves into “external” social and cultural influences, calling attention to sociocultural and situated learning theory. This is followed by a discussion of the ways in which culture and personal relevance influence professional identity. The chapter concludes with the committee’s articulation of the ways learning happens over time and across settings (i.e., an ecosystems approach), which it believes holds promise for the development of interest and competencies for computing. Although this discussion is primarily theoretical and conceptual in nature, examples are used to illustrate how some of these relationships have been studied in research on computational identity, interests, and competencies. FRAMEWORK FOR LEARNING AND DEVELOPMENT IN CONTEXT The committee’s investigation focused on how engagement in authentic experiences embedded in meaningful social and cultural contexts is linked with specific affective, behavioral, and cognitive outcomes. For example, how might the computing experience be tied to a young person’s sense of self and agency in a way that nurtures computing interests and competencies and, eventually, participation in the world of computing as a professional? The four learner examples described in Chapter 2 illustrate the interwoven nature of influences that expose learners to computing and support the development of computing interests and competency. These include recreational pursuits that learners engage in with peers such as playing and tinkering with video games, activities supported in informal learning institutions like libraries and afterschool groups, as well as formal learning experiences in school. All four learners had “authentic” experiences in that they were embedded in valued social and cultural contexts, were personally meaningful and interest-driven, and included tools, skills and practices that computing professionals engage in. Raven (Box 2-2) learned how to create artistic objects and gifts for her Prepublication Copy, Uncorrected Proofs 3-1

sister. Nathan (Box 2-1) figured out how to set up a Minecraft server with friends. Antonio (Box 2-4) programmed light sabers and robots for fun in his makerspace community. Hermione (Box 2-3) engaged in hackathons and now wants to use computer science to tell stories with data. These influences and outcomes are intertwined, and their relationship is multidirectional as well as multidimensional, taking place across multiple settings and over significant spans of time. These profiled experiences also illustrate the multifaceted and unplanned nature of how learners are exposed to and develop computing interests and skills, and the dynamic and complex way in which learners build a long-term interest in computing. The relationship between experiences of tinkering, making, and programming and long-term interest, skills, participation, and persistence in computing is influenced by a wide range of experiences at home, school, online, and in the local community as well as by individual factors such as identity. Given this complexity, the committee took a first step in building an organizing framework: identifying learning and development dynamics based on existing theories and conceptual models. This learning and development framework rests on the committee’s interpretation of “authentic STEM experiences” as reflective of professional communities of practice (professionally authentic) and personally meaningful contexts (personally authentic). The committee recognizes the importance of the culture and practices of computing as an important reference point for STEM authenticity, and participation and belonging in these professional communities of practice as a key outcome. Thus, the framework takes into account experiences beyond those in formal education to consider out-of-school time learning environments as well as sites of play with peers, and community engagement where learners find personally meaningful ways of engaging with computing. The committee also emphasizes the bidirectional relationship of affective, cognitive, and behavioral outcomes with authentic learning contexts, which can also serve as key mediators that influence how learners identify with cultures and practices of computing and develop interests and a sense of belonging. Authentic experiences, conceptualized in this way, are vehicles for learners to develop interests and identification with computing practices. As described in Chapter 2, the culture of science and technology has been historically dominated by White men.1 This suggests, that many professionally authentic STEM, including computing, environments have strong gender and cultural associations. Therefore, what feels authentic to those who reflect the dominant culture of computing may feel exclusionary to women and other minoritized groups such as Black, Latinx, and Indigenous learners as well as those with differences in perceived ability. Moreover, these groups experience barriers (i.e., racism, sexism, stereotypes, implicit bias, and lack of representation in communities of practice) at every level of social and cultural influence. These barriers, described in Chapter 2, can in turn influence identity and self-efficacy in relation to STEM, broadly, and computing, in particular. This chapter describes findings from theoretical and empirical research that has examined strategies for overcoming these systemic challenges. What follows is a discussion of what is known with respect to developing interest that promotes the motivation to develop competencies in computing. INTEREST AND COMPETENCIES IN COMPUTING In STEM, researchers have traced learners’ motivation to learn and learning outcomes to three factors: 1) their personal interest in—or fascination with—the topic; 2) their perception of 1 It is important to acknowledge that Asian is an incredibly broad category with different histories of immigration and exclusion from US society and economies. Prepublication Copy, Uncorrected Proofs 3-2

the value and use of the topic; and 3) their development of competence while engaging in the practices and community of the discipline (Bathgate and Schunn, 2017) as discussed more fully below. Key to understanding how authentic experiences may influence interest and competencies in computing is understanding how learners develop interest and the mechanisms that promote interest and motivation to learn. That is because these outcomes can also be individual mediators. In this section, the committee reviews theory and research on how interests develop over time and the mechanisms that foster and mediate interest and competencies. Because the literature specific to computing is limited, this section also draws on literature from STEM disciplines more broadly. The Relationship Between Interests and Competencies Interest is a key influence on learning and the development of competencies. When learners are interested in a topic, they have greater attention spans, are intrinsically motivated to learn, and see greater achievement (Hidi and Renniger, 2006; Nye et al., 2012). As interest develops, individuals are more likely to re-engage with content, which can lead to deeper interest and knowledge (Mehta and Fine, 2019). Understanding how interest develops provides insight into the types of experiences and interventions that can foster interest and competencies in computing. Hidi and Renninger (2006) postulate that interest develops sequentially through four stages, beginning with externally supported situational interest and deepening to more intrinsic and stable interest. The first phase is triggered situational interest, defined as “a psychological state of interest that results from short-term changes in affective and cognitive processing” (p. 114). For example, interest may be sparked by unexpected or novel information, or personal relevance of the topic to the individual. Novelty, challenge, choice, active participation, and group work have been noted as key factors in triggering learners’ initial situational interest (Renninger and Hidi, 2011). Situational interest is often fostered by community-specific opportunities in professionally authentic computing communities. The second phase, maintained situational interest, “involves focused attention and persistence over an extended episode in time” (p. 114). Once interest is sparked, it can be supported or sustained by repeated engagement that is initiated by the individual or promoted by outside factors, resulting in deeper interest. This can lead to the third phase, emerging individual interest, where learners may actively seek out and choose to re-engage with the content or tasks of interest. As their interest deepens, learners gain more knowledge about and value for the topic or task. Finally, emerging individual interest may lead to the fourth phase, a well-developed individual interest that is characterized by continued engagement with content over time. At this phase, learners may show more persistence and ability to continually participate and engage with a topic and more self-regulated behavior. This can lead them to become more central practitioners in the computing community, even though the form and nature of their participation can vary (Azevedo, 2011). Although this model appreciates that engagement stems from interactions between individuals and their environment, it does not properly account for the diversity of people’s environment or how history, a sense of future, or interactional goals might supersede their interest development (Azevedo, 2013; Pinkard et al., 2017)—contexts and learning environments will be discussed in more detail below. Researchers have found that activities that trigger initial interest can be different from those that maintain it over a longer period of time. For example, Mitchell (1993) found that Prepublication Copy, Uncorrected Proofs 3-3

group work and interaction with puzzles and computers in mathematics classes triggered initial situational interest, while personal relevance of the content and active participation fostered and maintained longer lasting interest. As reviewed in How People Learn II: Learners, Contexts, and Cultures, choice can also increase interest, engagement, and persistence (NASEM, 2018b). Finally, it is important to note that interest has a reciprocal relationship to other factors, such as goals, self-efficacy, self-regulation, knowledge, and value (Renninger and Hidi, 2011). For example, competence can lead to a sense of accomplishment, and in turn, fuel interest (Allison and Cossette, 2007). On the other side of the coin, lack of knowledge may lead to lower self-efficacy, dampening interest (Schmidt, 2014). Below the committee summarizes the theory and research behind these mechanisms. Mechanisms That Promote Interest and Competency Researchers have identified several factors that are characteristic of authentic experiences that can promote and mediate the development and deepening of interest. This includes the internal disposition of identity (discussed in this section) and the external influences (inputs) of role models, programs and practices and communities of practice (described in the next section). Most scholars describe three components of identity: a sense of belonging to a group, a sense of achievement within the norms of the group, and particular behaviors associated with belonging to a group (Carlone and Johnson, 2007; Cheryan, Master, and Meltzoff, 2015; Erikson, 1968; Lave and Wenger, 2002; Tajfel and Turner, 1986). Put more simply, identity in a community, such as computing, is about whether you see yourself and are recognized by others as someone who understands and uses the practices of that community (as set up in Chapter 2 and described in more detail later). Researchers have argued that it is through social processes and shared experiences that people gain a sense of identity (Boaler, William, and Zevenbergen, 2000; Lave and Wenger, 1991). Studies have linked the presence of a STEM identity with interest and persistence in STEM education and careers. For example, science identity has been found to predict learners’ interest in science, persistence in a science discipline, intention to pursue a scientific career, and decision to pursue graduate work in science (Merolla and Serpe, 2013; Merolla et al., 2012). Studies exploring the disproportionality of women and of Black, Latinx, and Indigenous individuals in STEM fields have also pointed to identity as a key factor. For example, Jones, Ruff, and Paretti (2013) found in a study of women that a strong STEM identity was related to greater persistence in the field. Stets et al. (2017) found that learners at HBCUs with a strong STEM identity were more likely to enter into a science occupation following graduation. Kim, Sinatra, and Seyranian (2018) argue that an under-acknowledged factor in STEM identity development for females is their social environment—their caregivers, friends, peers, and teachers. Specifically, in their review of the literature, they found support for the idea that women receive many signals from their environment that they do not belong in STEM. This environment impedes women’s motivation to pursue and persist in STEM coursework, ultimately reducing the likelihood that they will pursue STEM careers. Further, Kim et al. notes that STEM identity is also influenced by other social identities including one’s race, ethnicity, age, socio-economic status, and gender, to name a few. As introduced in Chapter 2, Rodriguez and Lehman (2017) recognized a need for an enhanced, intersectional computing identity theory that could allow for deeper understanding of how learners come to understand themselves as computer scientists. This theoretical framing Prepublication Copy, Uncorrected Proofs 3-4

could unpack why women and underrepresented learners continue to have difficulty identifying as computer scientists even when efforts are designed to be more inclusive. Thomas et al. (2018) interviewed 11 Black women in an effort to characterize the factors that influenced their continued participation in computing. The researchers noted that personal and professional goals, effective mentors, and familial inspiration were called out as factors that helped the women overcome adversity, which included experiences of discrimination, unrealistic expectations (either too high or too low), isolation, sexism, and racism. Taken together, the broader theoretical and empirical literature on the development of interest and competencies in STEM suggest links between interest, identity, and continued persistence in STEM fields. For communities often underrepresented in STEM, such as women, racial and ethnic minorities, and those with disabilities, research is still ongoing. This is in part because an important aspect of the research is consideration of the individual nested within a broader context of social and cultural influences. What follows is a discussion of these “external” factors and the implications within the committee’s learning and development framework. SOCIAL AND CULTURAL INFLUENCES ON AUTHENTIC LEARNING To elucidate the kinds of contexts that support authentic experiences, the committee drew from two different conceptual and theoretical literatures. The first is sociocultural and situated learning theory, which has developed a conceptual model for understanding how professional communities of practice support learning and belonging. The second body of research centers on how culture and personal relevance influence professional identity, including the role of place- based and problem-/project-based learning in shaping what young people view as personally relevant and authentic. Situated Learning and Communities of Practice Many longstanding approaches to instruction presume that learners will transfer what they are learning in one context to other future contexts. However, this idealization of the transfer process has been challenged in empirical studies (e.g., Gick and Holyoak, 1980). Although some conditions can better facilitate transfer (NRC, 1999), knowledge and understanding are largely rooted in particular contexts. For instance, grocery shoppers were effective at figuring out best-buy calculations at the supermarket but performed poorly when given similar problems in a paper-and pencil mathematics classroom-like task (Lave, 1988). Studies like these have led to the recognition that learning is situated in specific settings, with specific tools, and around specific practices (Brown, Collins, and Duguid, 1989). Consequently, learning is now viewed as a process of enculturation within a community of practice. Through documentation of learning via apprenticeship in a variety of settings, Lave and Wenger (1991) established a theory of situated learning in which novices develop competencies through a process of legitimate peripheral participation. That is, novices begin by observing, taking on some peripheral tasks, and increasingly assume greater responsibility over time within the community such that they become more central participants in the community. For instance, Antonio’s participation in his local library makerspace began with his peripheral participation, but over the years and with continued visitation, led to him becoming one of the youth mentors in that space. Raven progressed from being a newcomer at an afterschool Prepublication Copy, Uncorrected Proofs 3-5

computing group to eventually serving as a mentor both in the group and in an elementary school when she was in college. This turn toward recognizing the situated nature of knowing and learning has contributed to interest in learning experiences that are authentic relative to professional communities of practice. Learner practices in designed learning experiences that are comparable to practices of professionals are central to authentic learning experiences in STEM broadly and computing more specifically (Chinn and Malhotra, 2002; Crawford, 2012; Kapon, Laherto, and Levrini, 2018). Importantly, these authentic approximations of professional practice can serve to enculturate learners to professional communities of practice. Rather than presenting various decontextualized scientific principles in a classroom lecture, a more authentic approach positions learners as novice scientists and has them engage in versions of learning activities that better approximate professional scientific inquiry (Edelson, 1998). In an out-of-school-time learning space, this could involve a learner doing work with robotics that includes more experimentation, tinkering, and exploration akin to what an engineer would do, rather than simply assembling a robot from a kit by following a set of written instructions (Bevan, 2017). Moreover, authentic experiences that approximate professional practice provide access to tools used in professional communities of practice, albeit sometimes designed to ensure that they are accessible for more novice users (Edelson and Reiser, 2006). This was the case for Antonio, who had the opportunity to use high-end, expensive fabrication equipment to support his developing interest in technology. Mastery of these context-specific tools is thought to lead not only to increased competence in the discipline but also to an increased sense of identity as a person with special expertise. Linking Communities of Practice to Developing Interest and Competencies Some researchers argue that by structuring learning activities and environments so that they better approximate professional practice, the distance between practices in designed learning experiences and professional practice is greatly reduced (Edelson and Reiser, 2006). This results in the need to facilitate only near transfer between the learning context and the context where those practices are used professionally. The learning that takes place in the authentic experience therefore has greater relevance and utility for future use, which makes the competencies that develop from participating in an authentic experience more directly applicable to subsequent professional practice. In considering motivation and interest, the increased relevance of the knowledge and practices to be learned relative to professional practice increases the utility value of the learning experience, which in turn increases the subjective task value and motivation to develop competencies in the STEM domain (Eccles and Wigfield, 2002, Jacobs et al., 2005; Wang and Degol, 2013; Wang and Eccles, 2013). The greater relevance drives an increase in motivation to learn and thus develop greater competence. This seemed to be the case for Raven, whose motivation grew as she saw connections with the computing skills and languages she was learning and a range of professions and industries where they could be used. Moreover, researchers posit that over time, and with greater participation in authentic versions of the practice, learner identities shift such that they see themselves and are seen by others as more established practitioners in the target community (Simpson and Bouhafa, 2020). This takes place as part of the transition a novice makes from “newcomer” to “old timer” and from “peripheral participant” to “central participant” in the community (Lave and Wenger, 1991). This appeared to be the case for Nathan and his participation in online communities. Prepublication Copy, Uncorrected Proofs 3-6

While first a consumer of existing media (programming videos), he eventually went on to become a participant in some online programming communities in high school and later an active contributor to the open source coding community in college. There, competency develops as status in the community changes. As part of this shift in learner identity, the features of the practice that engender interest by professionals are thought to be recognized and valued by participants as they become further enculturated in the community (Glaze-Crampes, 2020). Interest in the professional practice develops as an identity as a competent practitioner develops. Additionally, it is believed that participation in activities that are authentic relative to professional STEM practices promotes situational interest, which in turn promotes a deeper sense of belonging within a community of practice (Moallem, Hung, and Dabbagh, 2019). As stated above, situational interest refers to the momentary state of interest that is cued by a specific activity or feature of the setting or environment; as the learner continues to re-engage with content over time this promotes deeper and more engaged learning, which in turn contributes to competency development (Hidi and Renninger, 2006). This was the case for Nathan, who had his interest piqued by bugs encountered in game server installation and later went on to explore programming. The greater authenticity of the learning environment leads to more overlaps between the features of the learning environment and the professional practice that are found interesting, thus promoting continual re-engagement and the development of competencies. Lastly, an underlying assumption of learning through enculturation is that learning is inherently a social activity. Learners benefit from exposure to more established practitioners and to role models that facilitate the development of new competence and the assumption of new identities (Lockwood, Marshall, and Sadler, 2005; Marx and Roman, 2002). Exposure to these role models can increase interest in the discipline by providing a plausible image of a professional position in the discipline that the learner can attain (Lockwood and Kunda, 1997; Marx, Stapel, and Muller, 2005). Role models also provide mentoring, access to professional networks, and forms of informal teaching that help learners develop practice-specific competencies on a just-in-time basis (NASEM, 2019). Raven had this through her after school program, Hermione through an internship, and Antonio had access to this at his local library makerspace. Near peer mentoring, with older learners serving as mentors for younger learners, is one example of how interest in computer science can be developed (Clarke-Midura et al, 2018). Exclusion from Communities of Practice Engagement in communities of practice, activities, and programs also provides occasions for young people to encounter role models and representations of computing. Different types of exposure and influence are most effective at different developmental stages. Interventions targeted toward younger learners are often centered on exposure, and as learners grow older, they are able to develop skills through activities, and eventually they can participate in professional communities (Callahan et al., 2019). Of special interest for educators is the influence that authentic experiences can have on computing interest, competencies, and engagement with communities or practice. Although the concept of communities of practice helps to explain some of the means through which young people begin to establish active patterns of participation in computing, it also raises concerns about equity and access, and reveals social and cultural influences on authentic learning in STEM, and computing more specifically. New membership in communities Prepublication Copy, Uncorrected Proofs 3-7

of practice is largely defined by those who are already established practitioners (Wenger, 1998) and professional computing has a history of excluding individuals on the basis of gender, race, ethnicity, or perceived ability (see Chapter 2). Despite a desire to promote greater diversity in computing, barriers to participation remain; these barriers include (but are not limited to) implicit biases (Cheryan et al., 2013; Steinke, 2017), systemic barriers (Margolis et al., 2008; 2017), and other detriments to cultivating feelings of belonging (Stout and Wright, 2016). As discussed above, shared interests and affinity fostered by overlapping learning and professional practices are powerful drivers of learning, engagement, and belonging within a community, but they are also exclusionary to those with dissimilar backgrounds and identities (Ito et al., 2018). Furthermore, within established communities of practice, members of socially marginalized groups begin in more precarious positions (Van Laar et al., 2019). Some are even actively discouraged from pursuing computing, as had been the case for Raven in her introductory computer science course in college. Research on situated learning also shows that the social interactions that take place and relationships that develop in communities of practice appear to be an important driver for engagement and for continued participation (Azevedo, 2011; 2013; Lee, Fischback, and Cain, 2019). Members of minoritized and non-dominant groups are often more uncertain of the quality of their social bonds within the community, and thus more sensitive to issues of social belonging (Walton and Cohen, 2007). This means that for those members of historically excluded groups who have been able to begin participating in a community of practice, there is still an ongoing disadvantage for maintaining and eventually increasing that participation. One way to disrupt these exclusionary processes is through affinity-based mentorship in programs where marginalized learners form relationships with peers and mentors who both share their background and are part of a high-value field or career path (Ben-Eliyahu, Rhodes, and Scales, 2014; Pinkard et al., 2017; Raposa et al., 2019). For instance, research suggests that middle and high school girls' engagement with mentors can add significantly to the information girls have about future career paths and can improve self-confidence with regard to STEM (Kahle and Meece, 1994; Nightingale and Wolverton, 1993). This impact was demonstrated in Hermoine’s and Raven’s cases; however, creating counter space (or safe spaces) does not erase the need to address systemic practices such as racism, sexism, and unequal access to opportunities that create the need for affinity groups in the first place. Culture and Personal Relevance As acknowledged in How People Learn II (NASEM, 2018b), “a learning environment is structured to promote particular ways of engaging in a specific set of activities, and the features of every learning environment reflect the cultural context in which it is situated” (p. 138). Moreover, learners bring their own individual cultural meaning derived from their out-of-school experiences in homes, neighborhoods, and communities to the learning environment. A learners’ funds of knowledge2 can be used as a valuable resource as part of the learning experience (NASEM, 2018b). When STEM learning is connected to familiar and personally meaningful cultural referents, places, and social relationships, it can support a sense of relevance and authenticity. Moreover, it could also support the development of connected knowledge, so that learners could then apply their knowledge to other situations (NRC, 2012). 2 Moll and colleagues (1992) have described funds of knowledge as the valuable understandings, skills, and tools that youth maintain as part of their identity. Prepublication Copy, Uncorrected Proofs 3-8

Problem-, project-, and place-based learning are a number of different strategies linked to promoting the engagement of learners as they are more learner-centered, require that learners take more responsibility for their learning, have choices, and are provided with opportunities to participate in real-world tasks that are meaningful for them (NASEM, 2018b). This suggests that experiences designed in this way are deeply motivating to students due to their personally authentic, iterative, and collaborative nature (Kolodner et al., 2003). Some of these approaches, such as place-based learning, are a subset of culturally relevant and sustaining pedagogies (see Chapter 7’s Content and Pedagogy section for more discussion of these approaches). Researchers such as Lim and Calabrese Barton (2006) have adopted equity-oriented approaches to these strategies to transform disciplinary content from abstracted knowledge to local knowledge that is related to communities’ cultural practices (Gruenewald, 2003). Place-based education engages learners in activities within and about their communities to highlight disciplinary concepts that are embedded within local systems, organizations, histories, and interactions and advance meaning making (Smith, 2002; Sobel, 2004). Siebert- Evenstone and Shaffer (2019) investigated the impact of authenticity in a simulated place-based learning environment. The environment was a simulation of a city that was local to some learners and not to others. Their study found that learning outcomes were better when learners engaged in the place-based simulation about their own local setting, suggesting that place plays a critical role in the impact of place-based education. Youth development benefits of place-based pedagogies include increased engagement in school and motivation for achievement (Athman and Monroe, 2004; Duffin, Powers, and Tremblay, 2004; Falco, 2004; Powers, 2004). Place-based pedagogies can increase workplace skills such as leadership, persistence, taking responsibility, teamwork, developing plans to reach a solution, managing time, motivating others, and dealing with unexpected challenges (Duffin, Powers, and Tremblay, 2004; Glenn, 2001); and development of an action-taking orientation and action competence (Barratt and Hacking, 2011; Mogensen and Schanck, 2010). In addition to academic and youth development benefits, a substantial body of research links place-based education with outcomes in the literature on social-emotional development. Impacts of place- based education on social-emotional development include: increases in self-esteem, increase in one’s sense of empowerment and agency, greater social interaction and social skills, increased social capital, and improved awareness of cultural diversity (Billig, 2000; Robinson and Zajicek, 2005; Schusler et al., 2009; Schusler and Krasny, 2010); increased sense of community attachment and community consciousness (Barratt and Hacking, 2011; Harrison, 2011); and increases in civic engagement, involvement, and responsibility (Duffin, Powers, and Tremblay, 2004; Flanagan and Gallay, 2014; Gallay et al., 2016; Schusler et al., 2009; Volk and Cheak, 2003). In engineering, studies of place-based pedagogies have documented the disproportionate involvement of women learners in community-based and service-learning engineering programs (Amadei and Sandekian, 2010; Coyle, Jamieson, and Oakes, 2006; Litchfield and Javernick- Will, 2014; Ruth et al., 2019). LEARNING OVER TIME AND ACROSS EXPERIENCES: AN ECOSYSTEMS APPROACH Developing both interest and competencies in computing-intensive activities, or any STEM field for that matter, can be a long-term process that may play out over years and in multiple settings. Therefore, no single short-term experience alone is likely to change a person’s Prepublication Copy, Uncorrected Proofs 3-9

life course or, at a systems level, to dramatically increase the participation of learners that have been underrepresented based on gender, race, ethnicity, or perceived ability working in computing. Recognizing this, researchers have articulated the importance of taking an ecosystems approach and examining the ways in which different kinds of experiences and supports in multiple settings over time reinforce each other to either build or undermine the development of interest, identity, and competency in a field of endeavor (Azevedo, 2018; Azevedo, diSessa, and Sherin, 2012; Barron, 2006; Bell et al., 2012; Bevan et al., 2010; Bransford et al., 2005; Crowley et al., 2015; Falk and Needham, 2011; Falk et al., 2015; Ito et al., 2013; Krishnamurthi et al., 2013; Mehus, Stevens, and Gringholm, 2010; NRC, 2015; Rahm, 2008; Traphagen and Traill, 2014). To illustrate, recall in Chapter 2 some of the descriptions of how actual youth active in computing came to their current level of interest and competence. Nathan (Box 2-1), for instance, participated in gaming communities, online programming communities, formal high school courses, and in clubs. Gaming led to initial opportunities to begin some work with backend computing, which led to discovery of online programming communities, which also contributed to participation in formal course selection and so on. It was not any single activity alone that led to his pursuit of a computer science degree. The combination of all, distributed across time and space, contributed. Similarly, Raven (Box 2-2) went from participating in an afterschool program to then pursuing summer programs related to computing and then eventually a major in computer science. The combination of those activities was additive with respect to her growth in interest and competence in computing, even sustaining her when she was discouraged from maintaining that path in college. As illustrated above, conceptualizing development of interest and competencies in computing would involve explicit recognition of the ecosystem of opportunities and supports that are available to learners. A number of initiatives (e.g., CSforALL,3 CIRCL,4 and STEM ecosystems5) have been developed to expand and explore the implementation of ecosystems. Where learners connect in the ecosystem may vary. For some learners, their interest in computing begins with enjoying and playing video games. For others, it could be an afterschool opportunity to become acquainted with new people working in computing and build relationships while building tools. And for others still, the entry might be highly engaging, personally meaningful project experiences in school that relate to computing, such as in Hermione’s experience (see Box 2-3). Barron (2006) employed this ecosystems approach in a study of “learning histories” for individual young people’s acquisition of interest and fluency in using computer technology. Barron stressed the importance of multiple contexts of fluency development related to technology that range from home, school, work, peers, community, and distributed resources such as online groups. In some of Barron’s case profiles, school experiences stimulated learners to seek technology learning experiences outside of school; in other cases, learning outside of school provided the impetus for a young person to take computing courses in school. The combination of learner initiative and broader support networks that included brokers to new opportunities contributed to the creation of technology learning opportunities. 3 For more information about the ways in which CSforALL is providing opportunities to connect formal and out-of-school time providers, see https://www.csforall.org/out-of-school-time-providers/. 4 For more information about the Center for Innovative Research in Cyberlearning, see https://circlcenter.org/. 5 For more information, see https://stemecosystems.org/. Prepublication Copy, Uncorrected Proofs 3-10

Crowley et al. (2015) used retrospective interviews to document the reported pathways taken by 69 scientists and science professionals and to track how interest was developed and involved in their eventual positions as professional scientists. Across their sample, the majority of participants (86%) reported interests being sparked during childhood. Out-of-school science experiences played a significant role in supporting interest in nearly half the participant sample (45%). School experiences were reported by 28 percent as positively related to their interest development. For those who felt their formal schooling contributed positive experiences that led to their current interest in science, enthusiastic teachers, independent study, afterschool clubs, and specific hands-on activities were noted as important. Another more recent retrospective study by Hecht, Knutson, and Crowley (2019) confirmed these patterns in a study of interest development among naturalists. Different combinations of school, family, and out-of-school learning experiences triggered and mutually supported interest development over time. These retrospective accounts are suggestive of how prior experiences shape subsequent interest and STEM identity. Studies of the Digital Youth Network compiled by Barron et al. (2014) have further illustrated how the combination of experiences and movement between school, community, home and online provided a mix of technology related engagements that led to development of technology interests and competencies. The prominence of early and ongoing experiences in family contexts in many of these longitudinal or retrospective studies, underscores the equity concerns raised throughout this report. Hermione (Box 2-3) is an interesting case in that her interest was not sparked by family, out-of-school settings, camps, etc. Her interest was sparked in school and relatively late in life and was nurtured through multiple in and out of school experiences. Moreover, it is likely that these experiences were arguably personally and professionally authentic. As such, this indicates that interest does not have to be sparked early, or through family or informal experiences. Young people from groups underrepresented in STEM and computing fields are less likely to grow up with authentic experiences that are both personally, culturally, and professionally relevant (Cheryan et al., 2016; Rodriguez and Lehman, 2018). An ecosystems approach challenges the dominant metaphor of a workforce “pipeline” that must be strengthened in order to increase participation in computing. A web of experiences over time and across settings that spark new interests and connect with existing personal interests, coupled with positive relationships with caring adults and peers working in those settings (Ito et al., 2020), has thus appeared to be the main driver of interest and participation in computing. Moreover, it is not simply the presence of a multitude of experiences and a network of caring peers and adults that will lead to long term professional participation in computing. Through a series of coordinated studies, the Connected Learning Research Network has documented that when learning is embedded in meaningful relationships, and connected to interests and home cultures, it is uniquely relevant and resilient (Ito et al, 2020). For example, Sefton-Green, Watkins, and Kirshner (2019) collaborated to investigate “the last mile” that connects education and careers. They found that success hinges on building an extensive, interconnected, and diverse network of relationships to supportive peers, mentors, and organizations that create new opportunities for youth, as observed in the case of Hermione. Following Ito et al. (2020), this ecosystems approach in research suggests the need to consider models of network and capacity building. The importance of building social capital and relationships may be particularly important for connecting personally authentic learning experiences to professionally authentic computing opportunities (Martin, Simmons, and Yu, Prepublication Copy, Uncorrected Proofs 3-11

2013; Martin, Miller, and Simmons, 2014). This ecosystems approach has important implications for equity and access to authentic learning experiences and computing fields. A growing body of research has documented personally relevant STEM learning experiences such as making and mathematics in the home culture and communities of groups underrepresented in STEM (Eglash et al., 2013; Nasir et al., 2006; Peppler, Sedas, and Dahn, 2020). These studies also note that these practices are not commonly connected or legitimated in dominant STEM educational practices. Gutiérrez and Rogoff (2003) have described the efficacy of an asset-based approach that engages “repertoires of practice” across home and school contexts as a way of addressing this disconnect. Researchers have described how girls from underrepresented groups may benefit from mutually enhancing experiences that connect STEM experiences in home and school to engage and develop STEM identities (Calabrese Barton, Tan, and Rivet, 2008; Calabrese Barton et al., 2013; Kang et al., 2019). Research on the Digital Youth Network documented how, when provided with supports that spanned school, afterschool, and online settings, Chicago learners from economically disadvantaged middle-schools developed tech interests and skills on par with tech-privileged youth growing up in Silicon Valley (Barron et al., 2014). Altogether, studies like these and those from the STEM literature more broadly suggest that an ecosystems approach for computing education experiences may be warranted (NRC, 2015). Experiences and activities that are personally authentic to youth can be a critical entry point for eventual long-term participation in computing, but the entry point alone is not enough to count on long-term computing participation. The growing body of evidence described above (Barron, 2006; Crowley et al., 2015) suggests that when young people experience validation and support for connecting personally relevant computing experiences across the settings of home, school, and community, this can reinforce their sense of belonging and interest. That is, it is important to consider the ways in which learners participate in multiple communities of computing practice over time and the various forms of authenticity emphasized in those communities. Individually, these communities may not be in direct alignment with professional communities of practice. In the aggregate, they support and lead to participation in the eventual participation in professional computing communities. SUMMARY In an attempt to understand the role that authentic experiences play in developing interest and competences for computing, the committee began with a review of the evidence on learning. The committee introduced a framework that illustrates how the influences and outcomes are intertwined and takes place across multiple settings and over significant spans of time. The chapter then characterized the relationship between interests and competencies. To understand how authentic experiences may influence interest and competencies in computing, it is important to understand how learners develop interest and the mechanisms that promote interest and motivation to learn. Moreover, the framework focuses on the underlying learning and development dynamics that are based upon existing theories and conceptual models, specifically, calling attention to sociocultural and situated learning. In particular, the committee recognized the ways that the situated nature of knowing and learning has contributed to interest in learning experiences that are authentic relative to professional communities of practice. The committee then discussed the role of culture and personal relevance, describing the evidence on problem, project-, and place- Prepublication Copy, Uncorrected Proofs 3-12

based learning. The chapter concluded by articulating the need for an ecosystems approach, notably an understanding that learning happens over time and across settings. That is, the development of expertise requires time, and no single short-term experience is likely to be enough to develop the competencies and skills needed for computing. Moreover, different kinds of experiences and supports in multiple settings over time reinforce each other and may serve to build and interest in future computing endeavors. Prepublication Copy, Uncorrected Proofs 3-13

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Computing in some form touches nearly every aspect of day to day life and is reflected in the ubiquitous use of cell phones, the expansion of automation into many industries, and the vast amounts of data that are routinely gathered about people's health, education, and buying habits. Computing is now a part of nearly every occupation, not only those in the technology industry. Given the ubiquity of computing in both personal and professional life, there are increasing calls for all learners to participate in learning experiences related to computing including more formal experiences offered in schools, opportunities in youth development programs and after-school clubs, or self-initiated hands-on experiences at home. At the same time, the lack of diversity in the computing workforce and in programs that engage learners in computing is well-documented.

It is important to consider how to increase access and design experiences for a wide range of learners. Authentic experiences in STEM - that is, experiences that reflect professional practice and also connect learners to real-world problems that they care about - are one possible approach for reaching a broader range of learners. These experiences can be designed for learners of all ages and implemented in a wide range of settings. However, the role they play in developing youths' interests, capacities, and productive learning identities for computing is unclear. There is a need to better understand the role of authentic STEM experiences in supporting the development of interests, competencies, and skills related to computing.

Cultivating Interest and Competencies in Computing examines the evidence on learning and teaching using authentic, open-ended pedagogical approaches and learning experiences for children and youth in grades K-12 in both formal and informal settings. This report gives particular attention to approaches and experiences that promote the success of children and youth from groups that are typically underrepresented in computing fields. Cultivating Interest and Competencies in Computing provides guidance for educators and facilitators, program designers, and other key stakeholders on how to support learners as they engage in authentic learning experiences.

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