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Suggested Citation:"1 Introduction." 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:"1 Introduction." 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:"1 Introduction." 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:"1 Introduction." 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 8
Suggested Citation:"1 Introduction." 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 9
Suggested Citation:"1 Introduction." 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 10
Suggested Citation:"1 Introduction." 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 11
Suggested Citation:"1 Introduction." 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 12
Suggested Citation:"1 Introduction." 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 13
Suggested Citation:"1 Introduction." 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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1 Introduction The impact of computing can be seen all around us. This impact is perhaps most visible to people in moments where they engage directly and intentionally with computing, such as using a computer to access information, using GPS to navigate while driving, and using a smartphone to connect and engage through social media. Overall, the pervasive use of computing has dramatically transformed our personal, professional, and public lives. Today’s learners will enter as adults into a world that is different from the world as it is today. Progress in computing has led to significant advances (e.g., artificial intelligence and automation) and these technologies will continue to evolve. It is even possible that programming may become less essential. A recent report by the National Academies of Sciences, Engineering, and Medicine (NASEM, 2018a) defined computing as a “term used broadly to refer to all areas of computer science, all interdisciplinary areas computer scientists work in, and all fields using computer science or computational methods and principles to advance the field. This includes both academic and occupational fields, such a bioinformatics, medical informatics, library sciences, digital archives, computational sciences, and more” (p. 17).1 Because nearly all jobs involve computing, it is important to consider the ways computing will likely continue to shape the future workforce and how learners today are educated. Realizing the profound impact of computing on the future workforce has led to debates centering on the importance of learners engaging with computing in the present. These debates have largely been positioned in two ways: workforce development and computing literacy for civic participation. When considering workforce development, it is important to envision the potential workforce needs, given advancements in technology and computing (Guzdial, 2015). A number of federal strategy documents produced over the last couple of years acknowledge the trends and needs for growing sectors of the workforce (e.g., artificial intelligence, computer science, data science). For example, the development of the computing workforce is called out in the 2019 report National Artificial Intelligence R&D Strategic Plan: 2019 Update2 and the 2018 report National Strategic Overview for Quantum Information Science.3 Throughout these reports, and others (see the 2019 report National Strategic Computing Initiative Update 20194), there is an emphasis on developing a more diverse workforce, stemming from recognition that the science, technology, engineering, and mathematics (STEM) workforce, including computing, has lacked representation among women and individuals of color. In addition to workforce development, debates about learning engagement in computing have also focused on the development of computing literacy for civic participation. The 2018 report Charting a Course for Success: America’s Strategy for STEM Education produced by the 1 This report also defined computer science as “[T]he study of computers and algorithmic processes, including the principles, their hardware and software designs, their applications, and their impact on society” (NASEM, 2018a, p. 17). 2 The full report is available at: https://www.whitehouse.gov/wp-content/uploads/2019/06/National-AI- Research-and-Development-Strategic-Plan-2019-Update-June-2019.pdf. 3 The full report is available at: https://www.whitehouse.gov/wp-content/uploads/2018/09/National- Strategic-Overview-for-Quantum-Information-Science.pdf. 4 The full report is available at: https://www.whitehouse.gov/wp-content/uploads/2019/11/National- Strategic-Computing-Initiative-Update-2019.pdf. Prepublication Copy, Uncorrected Proofs 1-1

National Science & Technology Council5 stresses that computing is a necessary critical skill for understanding our changing technological and social landscape (Lee and Soep, 2016; Vee, 2013). Computing literacy goes beyond simply knowing how to use a computer or engaging with technology, it also includes being able to use computing to make and create new products (Ito et al., 2019; Kafai, Fields, and Searle, 2019; Rushkoff, 2010). As learners continue to have computing opportunities that leverage “making with” they are able to learn and understand the complex issues and approaches that are necessary for true digital literacy (Buckingham, 2007, 2013; Guzdial et al., 2012; Marty et al., 2013). These shifts in computing have also emphasized the need to develop skills that are essential to life in the 21st century, calling attention to the need to emphasize teaching computational thinking (Blikstein, 2018; Buitrago Flórez et al., 2017; Shein, 2014; Vogel, Santo, and Ching, 2017; Wing, 2006). Wing (2006) described computational thinking as: (1) conceptualizing, not programming, (2) fundamental, not rote skill, (3) a way that humans, not computers, think, (4) complements and combines mathematical and engineering thinking, (5) ideas, not artifacts, and (6) for everyone, everywhere. Conversations continue to focus on how to define these important skills, whether as a set of practices emerging from computer science (Wing, 2006), a set of dispositions (Computer Science Teachers Association [CSTA] and International Society for Technology in Education [ISTE], 2011), or a way of thinking (National Research Council [NRC], 2011a). Although its boundaries and definitions are often contested (Tedre and Denning, 2016), there is some consensus that computational thinking is a valuable skill for learners to engage in an increasingly technological and computational world (Grover and Pea, 2013; NRC, 2011a). Computational thinking can also be valuable as a method for developing disciplinary understanding (diSessa, 2000; Papert, 1980). Computational thinking includes engaging in logical thinking and problem-solving and is observed in national standards for mathematics (i.e., Common Core State Mathematics Standards)6 and science (i.e., Next Generation Science Standards [NGSS]; NGSS Lead States, 2012).7 As such, there is a close resemblance between aspects of scientific inquiry and aspects of computational thinking, such as data collection and analysis. In engineering, for example, the computational thinking practices of defining problems through abstraction and approaching solutions systematically parallel typical applications of working with robots and testing solutions iteratively. In the past decade, computer science (CS) education has been, and continues to be, supported broadly through public policy and a growing number of public K–12 institutions. For example, the increased interest and emphasis in computing and CS education is observed nationally through broader educational initiatives like the CSforALL movement as well as through private sector support (see Box 1-1).8 It is also observed in the creation of a framework for K–12 CS education and subsequent national standards.9 These national endeavors have called for the development of interdisciplinary approaches to the integration of computing within STEM teaching and learning; building capacity within the educational system to support CS education; and examining ways to broaden access and participation of learners from who have 5 The full report is available at: https://www.whitehouse.gov/wp-content/uploads/2018/12/STEM- Education-Strategic-Plan-2018.pdf. 6 For specific information regarding the mathematics standards, see: http://www.corestandards.org/Math/. 7 For specific information regarding the science standards, see https://www.nextgenscience.org/. 8 For more information, see https://www.csforall.org/. 9 For more information on the framework, see https://k12cs.org/ and for more information on the standards, see https://www.csteachers.org/page/about-csta-s-k-12-nbsp-standards. Prepublication Copy, Uncorrected Proofs 1-2

been historically underrepresented based on gender, race, ethnicity, or perceived ability. Overall, the push has been for learners to develop the skills and competencies that are reflective of the discipline (i.e., professional authenticity). As programs in and out of school continue to develop and provide learners with opportunities to engage in computing experiences, it is essential to consider how the design of these experiences develop interest and competencies for computing. Learners’ technology experiences have been dominated by playing and tinkering with commercial games, software, and social media platforms since they first began gaining access to computers in the 1980s (Ito, 2009). Authentic, open-ended learning activities—through project- or problem-based learning and makerspaces—have been offered as an approach to support broader access to STEM learning and can catalyze interests and learning in computing (Calabrese Barton, Tan, and Greenberg, 2017; Capraro and Slough, 2013; Dischino et al., 2011; LaForce, Noble, and Blackwell, 2017; Resnick, 2017). These open-ended experiences are “authentic” in the sense that they are designed to reflect the practices of the discipline; that is, they are close approximations to the work that a STEM professional would engage in. In addition to approximating the work of the professional, there has been increasing attention to designing authentic STEM experiences so that they are connected to real-world problems learners’ care about and the challenges they face. In the past decade, making and makerspaces have emerged as a movement within and outside of learning spaces (see Box 1-2). Whether in formal or informal educational settings, many maker efforts are oriented towards STEM skills and workforce development (Blikstein, 2013b; Martin, 2015; National Science Foundation, 2017; Vossoughi and Bevan, 2014), where making is the vehicle to STEM + Computing (STEM+C) careers or to accessing new opportunities (Fancsali et al., 2019). Within learning spaces, making has been embraced by both in-school and out-of-school-time communities, in early childhood all the way to higher education (Fields and Lee, 2016; Peppler, Halverson, and Kafai, 2016). Proponents and some empirical research suggest that collaboration (Clapp et al., 2017), interest, content, and practices oriented towards STEM (Kafai, Fields, and Searle, 2014; Sheridan et al., 2014), failure, persistence, and iteration (Maltese, Simpson, and Anderson, 2018; Ryoo and Kekelis, 2018; Ryoo et al., 2015), and a number of other skills are fostered through maker learning approaches and environments (Fancsali et al., 2019). Research suggests that authentic STEM experiences may foster the development of deep conceptual understanding and skills for STEM disciplines (NRC, 2009; 2014; 2015). That is, through these types of experiences, which may be more intrinsically motivating, individuals learn how to identify a problem or need as well as how to plan, model, test, and iterate solutions, all of which makes their higher-order thinking skills tangible and visible (Bennett and Monahan, 2013). Moreover, emerging research has begun to examine the ways in which these types of activities, rooted in authenticity, have the potential to invite in learners from underrepresented communities (based on gender, race, ethnicity, or perceived ability) in STEM fields, particularly computing (Lim and Calabrese Barton, 2006; Migus, 2014). As such, it is important to understand the ways in which authentic STEM experiences can develop interests and competencies for computing. CHARGE TO THE COMMITTEE Sponsored by Google and the Grable Foundation, the Board on Science Education (BOSE) of the National Academies of Sciences, Engineering, and Medicine, in collaboration Prepublication Copy, Uncorrected Proofs 1-3

with the Computer Science and Telecommunication Board (CSTB) convened an expert committee to examine the evidence on the ways in which authentic STEM experiences develop interest and competencies for computing (see Box 1-3). The 16-member expert Committee on the Role of Authentic STEM Learning Experiences for Developing Interest and Competencies for Computing included individuals with expertise in the design and construction of learning spaces in formal and informal educational settings that are aimed at providing opportunities to engage in STEM and computing. The expertise spans the K–12 range in a number of important areas, including disciplinary knowledge in science, mathematics, and computer science; the development of curriculum; teacher professional learning and development; as well as perspectives on issues around diversity, equity, and inclusion. STUDY APPROACH The committee met six times over a 15-month period in 2019 and 2020 to gather information and explore what is known about the role of authentic experiences for the development of interest and competences for computing. During this time, the committee reviewed the published literature pertaining to its charge and had opportunities to engage with many experts. Evidence was gathered from presentations and a review of the existing literature (including peer-reviewed materials, book chapters, reports, working papers, government documents, white papers and evaluations, and editorials) and previous reports by the National Academies (see Box 1-4). The committee searched for information on a number of different outcomes for computing as well as on the different features of design and the institutional/organizational contexts that can facilitate or hinder learners’ participation in authentic experiences. When looking at particular outcomes, the committee focused on a number of cognitive, behavioral, and affective outcomes that included interest, identity/belonging, motivation, self-efficacy, knowledge and skills, engagement, and persistence and retention. In reviewing the evidence, the committee sought to assemble a set of studies that represented the extent of available evidence. A search was conducted through Scopus requesting studies from the past two decades (2000–2020) and limited to English. The review focused on literature and programs centered around three categories of outcomes: (1) affective (such as interest, identity/belonging, motivation, and self-efficacy); (2) cognitive (such as knowledge and skills); and (3) behavioral (such as engagement, persistence, and retention). Details regarding this search can be found in Appendix A. Many different types of studies were included in this review: meta-analyses and reviews, qualitative case studies, ethnographic and field studies, interview studies, and large-scale studies. The committee recognized that the literature consisted predominantly of studies that were largely descriptive in nature with few studies that could demonstrate causal effects. As appropriate, throughout the report, the evidence is qualified to articulate the type of research being reviewed and its strength. Throughout the study, members of the committee benefited from discussion and presentations by a number of individuals who participated in the fact-finding meetings. At the first meeting, the committee had an opportunity to speak with the sponsors to ask questions and get clarity on the statement of task. In particular, the committee wanted to better understand the sponsor’s stance on authenticity and what could be included in the range of authentic experiences. The committee also had the opportunity to hear more about the framing and state of Prepublication Copy, Uncorrected Proofs 1-4

evidence with respect to equitable access to authentic STEM opportunities. During the second meeting, the committee considered the ways in which robotics competitions and engineering programs were reaching their participants either through the design of the experiences or through outreach efforts to ensure that girls and learners from minoritized groups had access to these programs. Additional presentations described what is known about hobbies and their relationship to different STEM outcomes and the implications of this research for computing. During the third meeting, there was a large public workshop that focused on a number of key issues. In particular, the presenters were asked to unpack the state of evidence on (1) the role of STEM learning opportunities, (2) promising approaches and strategies in the development of interest and competencies, and (3) what these mean for the goals, design, and implementation of such experiences for computing. A recurring theme throughout the workshop was the importance of evidence that emphasized the implications for increasing access for learners from minoritized communities. At the fourth meeting, the committee discussed the draft of the report and reached consensus on a number of key issues (described in the previous section). In between meetings, the committee had in-depth conversations with several youth-serving STEM programs to understand their design and their evidence with respect to impacts on the desired learner outcomes. Additionally, members of the committee conducted structured interviews with several young adults who have pursued or are immediately pursuing computing and technology- intensive postsecondary education.10 These illustrative cases were intended to provide some longitudinal, retrospective data that could highlight aspects of the individual experiences that led the learners to persist in computing. These cases do not reflect the experiences of individuals who have opted not to persist (for a variety of reasons; see Chapter 2). At the fifth meeting, the committee reviewed the draft report to ensure that there was sufficient evidence for the claims being made. As stated above, throughout the report, the type of research reviewed, and the strength of research evidence, are clearly articulated. The majority of the committee’s final meeting was devoted to discussing the conclusions, recommendations, and research agenda to reach consensus. During these discussions, the committee was careful to qualify and temper the conclusions and subsequent recommendations, based on the type and strength of the evidence presented. REPORT ORGANIZATION This report examines the research on authentic experiences in computing for learners in grades K–12 across formal and informal settings. Chapter 2 examines the structural (e.g., racism and sexism) and cultural barriers (e.g., stereotypes and implicit bias) to participation in computing that exist at multiple levels. These barriers to participation impact the nature of the learner’s experiences and their development of a computing identity. Chapter 3 articulates the committee’s theoretical framing that describes the varied factors that influence whether and how learning is positioned to develop interest and competencies for computing whereas, Chapter 4 presents the evidence on how individual programs or individual curricula speak to the intended outcomes of interest and competencies. Chapter 3 also describes the need for adopting an 10 The committee sought IRB approval from the Institutional Review Board, and it was determined that the protocol qualified for exemption from IRB review, under category 2(i, ii) on March 5, 2020. Pseudonyms are used to protect confidentiality. Prepublication Copy, Uncorrected Proofs 1-5

ecosystems approach to understanding learner’s contexts and motivating factors and how these may lead to continued pursuits with computing. Chapters 5 and 6 describe the institutional and/or organizational contexts that provide the necessary infrastructure for learners to engage in educator-designed authentic experiences for computing. Chapter 5 focuses on authentic experiences that occur outside of school time and emphasizes the strengths and challenges with respect to ensuring equitable access to these programs. Chapter 6 describes the factors (e.g., school funding, teacher preparation, standards and certifications) that influence whether and how authentic experiences for computing are offered in formal educational contexts. Chapter 7 then provides guidance on how to design authentic experiences for computing given the evidence and organizational constraints. Chapter 8 presents the consensus conclusions and recommendations that are derived from the evidence provided in earlier chapters and articulates an agenda for future research. Prepublication Copy, Uncorrected Proofs 1-6

BOX 1-1 The Role of the Private Sector The current movement for computing and learning has been catalyzed and supported by unique public, nonprofit, and private partnerships. Many in-school initiatives for K–12 STEM+C have been funded and implemented by corporations (e.g., AT&T Aspire, Tata TCS goIT, Google Code Next, Cisco Networking Academy, and Microsoft TEALS). Code.org has developed a number of activities to expand access to computing opportunities in school (e.g., providing computer science curriculum, teacher professional development, and the Hour of Code campaign). The private sector has been a key driver of tools and programs that support STEM experiences and help develop computing interests and competencies. This involvement includes (1) corporate funding and support for computer science and maker-oriented educational programs and institutions, (2) computing learning programs and tools developed by the educational technology industry, (3) technology learning experiences fostered through recreational engagement commercial games and technology platforms, (4) corporate-developed training and curriculum, and (5) corporate support for employee volunteer opportunities. The private sector has also been a longstanding supporter of out-of-school STEM learning and making programs. Intel was a key sponsor of the Computer Clubhouse Network. Other companies have also sponsored technology centers and makerspaces such as the Best Buy Teen Tech Centers. The maker movement and the Maker Faire was, until recently, championed by the for-profit company Maker Media, which also helped launch nonprofit educational efforts such as Maker Ed.11 Many of the early maker education efforts were seeded, and continue to be sponsored, by corporations such as Cognizant, Google, Infosys, and Chevron, among many others. Family and community foundations, as well as federal agencies, have also played critical roles, but corporate funds supported the momentum of these initiatives, developed in in-school and out-of-school-time spaces alike. Smaller local businesses are often also critical to a maker program’s fundraising and community building. While large corporations have supported public sector and nonprofit computing programs such as Code.org, other companies have developed businesses centered on afterschool and summer programs for STEM learning. Summer camp providers like ID Tech, Galileo and Rolling Robots offer programs that can cost over $1,000 a week to learn robotics, coding, and digital creation. A number of for-profit afterschool centers offer programming and computing experiences for youth, although their membership dues are often prohibitive for large portions of the youth population. A smaller number of startups have sought to establish online STEM learning programs and platforms, such as DIY.org and Apex Learning. 11 See https://www.edsurge.com/news/2019-06-09-a-call-to-remake-the-maker-faire. Prepublication Copy, Uncorrected Proofs 1-7

BOX 1-2 Making and Makerspaces Made visible by MAKE: Magazine and Maker Faires that centered on adult hobbyists and DIYers, the broader maker community has since diversified and expanded, with continued efforts and needs to address equity and cultural relevancy (Calabrese Barton and Tan, 2018; Buechley, 2013; Vossoughi, Hooper, and Escudé, 2016). Within learning communities, there exists a duality to making. Whether or not a dedicated physical space is available, making is recognized as a learning approach (Honey and Kanter, 2013; Petrich, Wilkinson, and Bevan, 2013; Resnick and Rosenbaum, 2013; Vossoughi and Bevan, 2014). Making can and often does happen in physical settings, such as a makerspace, often taking on the contexts of the overarching organizations in which they exist. Although “makerspace” is a commonly used term, not all spaces use that name (FabLabs, creativity studios, and Tinkering Studio), and not all maker learning takes place in dedicated physical spaces well-equipped with technology and supplies. In fact, whether in school or afterschool spaces, museum floors, or library environments, activities and materials may be distributed across multiple areas via cart-based systems, classroom corners with tools, or pop-up programming (Peppler, Halverson, and Kafai, 2016). Dedicated makerspaces may allow for consistent interactions with the physical environment and with a community of peers, families, mentors, and/or facilitators (Brahms, 2014). And making occurs at home as individuals, families, and communities have long fixed and made things out of necessity (Calabrese Barton and Tan, 2018; Danticat, 2013; Vossoughi and Bevan, 2014). Depending on how maker learning programs or makerspaces are designed, what purposes or values are upheld, what settings and contexts they exist within, and what activities are emphasized, making can be authentic to a learner’s personal and individual interests, as well as authentic to a community’s collective identity (Blikstein, 2013a; Martinez and Stager, 2013). Learners decide which activities and projects to pursue, based on their passions or curiosities (Wardrip and Brahms, 2016), and much of the teaching and learning is hands-on, open-ended, and learner-centered, scaffolded by educators and facilitators but also driven by self-exploration and inquiry (Clapp et al., 2017; Halverson and Sheridan, 2014). Specific to computing, maker learning programs frequently include digital and analog opportunities that range from e-textiles and paper circuitry to physical computing to digital fabrication to multimedia production, where learners are exposed to and develop computing skills with microcontrollers (LilyPad Arduino, Raspberry Pi, micro:bit), programming languages (block-based programming, Java, Python, HTML and CSS, Processing), 3D design (CAD for CNC machines), and more (Berland, 2016; Blikstein, 2013a,b; Kafai, Fields, and Searle, 2014; Lee and Recker, 2018; Martin, 2015). Prepublication Copy, Uncorrected Proofs 1-8

BOX 1-3 Statement of Task An ad hoc committee will explore authentic STEM learning experiences that develop interest and foundational knowledge and competencies for computing. The committee will examine 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. The committee will consider a range of pedagogical approaches and learning experiences aimed at cultivating the interest and foundational knowledge and competencies necessary for pursuing careers in computing, with particular attention to engaging participants in authentic, open-ended experiences such as problem or project-based approaches and making/makerspaces. The committee will give particular attention to approaches and experiences that promote the success of children and youth from groups that are typically underrepresented in computing fields. In cases where the evidence base with respect to interest and competencies in computing is not robust, the committee will draw on evidence from research on learning and teaching in science, engineering, and mathematics. Prepublication Copy, Uncorrected Proofs 1-9

BOX 1-4 Previous Relevant Reports by the National Academies of Sciences, Engineering, and Medicine Over the last 10 years, there has been a lot of interest in understanding the role of STEM and computing experiences in both higher education and K–12 across a variety of settings (formal and informal). In 2018(a), Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments examined the potential impacts to the increased demand for computing in higher education, drivers of the current enrollment surge, and the relationship between the surge and current and potential gains in the diversity in the field. In the K–12 education space, there has been a series of reports that have tackled related issues from a number of different perspectives. The first of these was a pair of reports, Learning Science in Informal Environments: People, Places, and Pursuits (NRC, 2009) and Surrounded by Science: Learning Science in Informal Environments (NRC, 2010a), that assessed the evidence on science learning across settings, learner age groups, and over varied spans of time and then provides case studies, illustrative examples, and probing questions for practitioners. The next pair of reports centered on computational thinking. In particular, the first, Report of a Workshop on the Scope and Nature of Computational Thinking (NRC, 2010b), focused on presenting the range of perspectives with respect to the definition and applicability of computational thinking whereas the second, Report of a Workshop on the Pedagogical Aspects of Computational Thinking (NRC, 2011a) focused on illuminating different pedagogical approaches to computational thinking. In an effort to better understand the ways in which individuals’ science learning can be accomplished through interaction with digital simulations and games, Learning Science Through Games and Simulations (NRC, 2011b) provides a review of the available research on the potential of digital games and simulations to contribute to learning science in schools, in informal out-of-school settings, and everyday life. The final report sought to draw upon a wide range of research traditions to illustrate that interest in STEM and deep STEM learning develop across time and settings. Identifying and Supporting Productive STEM Programs in Out-of- School Settings (NRC, 2015) provided guidance on how to evaluate and sustain programs. Prepublication Copy, Uncorrected Proofs 1-10

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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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