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Suggested Citation:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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:"6 Computing Experiences in Schools." 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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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.

Chapter 6 Computing Experiences in Schools Schools are potentially powerful settings for infusing authentic learning experiences in computing. Learners are required to attend school which means schools are a setting that reach a broad swath of students. The compulsory nature of schooling, however, can also make it difficult to create opportunities that balance both professional and personal authenticity. In this chapter, the committee considers computing education in schools in the United States. We begin with an overview of how computing fits into the landscape of the K–12 curriculum and identify concerns about equity and access. We then consider each level of schooling—elementary, middle, and high school—separately, discussing both the current status of computing education at each level and exploring how authentic experiences could be supported. As teachers are the lynchpin for successful computing education, the final sections of the chapter discuss teachers’ learning needs for supporting learning in computing. In describing current trends in education for computing, the committee drew on the 2018 National Survey of Science and Mathematics Education (NSSME+). This survey is one of the few nationally representative, longitudinal surveys of science and mathematics education in the country. For the 2018 data collection, computer science was added as one of the subjects that representatives of school systems and teachers were asked about (Banilower et al., 2018).1 OVERVIEW OF COMPUTING IN THE K–12 CURRICULUM The last decade has seen expansion of access to instruction in computing in schools. The report State of the States Landscape Report: State-level Policies Supporting Equitable K–12 Computer Science Education (Stanton et al., 2017) tracks progress toward ten policy priorities that are seen as central to broadening participation in computer science (CS) education. According to this report, in 2017 seven states had publicly accessible K–12 standards for CS content. Eight additional states were engaged in the standards development process. Nine states have dedicated state-level funding to K–12 CS education in fiscal year 2016–2017. At least four states had also allocated funding to CS for fiscal year 2018–2019. Four states required all public high school to offer at least one CS course. Twenty-three states and DC required that CS be allowed to fulfill a core graduation credit. A more recent analysis (2019) of state policy in CS education suggest an increase in attention to computer science. This analysis reports that 19 states require all high schools to offer CS, and 4 states require CS of all levels to be taught in all public schools. This report also highlights that 34 states have adopted CS learning standards, with another 5 states actively developing learning standards (Code.org, ECEP, and CSTA, 2019). At all grade levels, instruction in computing can be offered both through stand-alone courses and by integrating computing experiences into courses in other subjects. Teachers’ reports suggest that integrating computing into mathematics and science classes is rare (see Table 6-1). At all grade levels, 70 percent or more of mathematics and science teachers report never integrating coding into their courses. While coding is just one aspect of computing, these results to do not provide strong evidence for the presence of computing in science and mathematics classes. 1 For more information on the sampling methods and sample sizes, see Appendices A and B of the Horizon report. The final sample for computer science teachers consisted of 289 teachers. Prepublication Copy, Uncorrected Proofs 6-1

There are disparities in access to learning experiences in computing. Results of the NSSME+ reveal differences in learning opportunities by grade, rates of poverty at a school, and school size (Banilower et al., 2018). Specifically:  26 percent of elementary schools offer instruction in computer programming,  38 percent of middle schools offer instruction in computer programming,  53 percent of high schools offer one or more courses in computer science;  High poverty high schools (26%) were less likely to offer instruction in computer science than low-poverty schools (46%) (by quartiles);  Large high schools (43%) were more likely to offer instruction in computer science than smaller schools (23%); Recent shifts in state approaches to computing education might increase the number of schools that are offering computing education for all learners as part of the core educational curriculum (see Box 6-1). Knowing whether instruction and courses are available does not provide information about the nature of the students’ learning experiences. Course names and descriptions do not always reflect the content of school coursework in computing or the skills of the professional discipline (Margolis et al., 2008). Further, there is variation in the pedagogical preparation of classroom teachers to teach computing and to connect learners to computing in engaging, culturally relevant, and personally meaningful ways. This makes it difficult to know the extent to which students’ learning experiences in computing reflect professional and personal authenticity as described by the committee. The conditions of school facilities, as well as whether learners have access to technical resources at home, also impact CS learning and instruction independently of the particular course or learning experience. One major obstacle in supporting teaching and learning in CS concerns the technology, including devices and connectivity, needed to support learners learning CS. Though 94 percent of school districts meet a minimum speed of Internet access, 6.5 million students, primarily in rural schools, are without access (Mathewson, 2017). Data from the Federal Communications Commission (2015) shows that rural areas are less likely to be wired for broadband service and tend to have slower connectivity compared to other areas of the country. Given that computing education often depends on digital devices, disruptions in access to using the Internet or other technology tools and supports has a profound impact on the instruction for learners. In fact, high school CS teachers reports that lack of reliable access to the Internet (19% of teachers), lack of support to maintain technology (34% of teachers), and lack of functioning computing devices (27% of teachers) have a negative impact on their instruction (Banilower et al., 2018). Further, teachers also report that security measures, such as school restrictions on the Internet, also inhibit their instruction of CS (37% of teachers). Given the remote learning challenges that were starkly exposed by the COVID-19 pandemic, having access to devices and steady Internet, in any learning setting, is essential for student learning. In addition to instruction and courses that are part of the curriculum, schools offer a range of activities during the school day and after-school to engage students in computing. Results of the NSSME+ offer a window into the kinds of activities available and how their availability varies by grade level (see Table 6-2). These activities are another setting for providing access to authentic learning experiences in computing. They also offer opportunities to foster connections between students’ computer learning experiences in and out of school. Prepublication Copy, Uncorrected Proofs 6-2

COMPUTING IN ELEMENTARY AND MIDDLE SCHOOL In both elementary and middle school, learning experiences in computing can be offered through both stand-alone classes and integration of computing in classes in other subjects. That said, as indicated in the previous section, integrating computing into mathematics and science appears to be relatively rare. However, there are projects at both elementary and middle that show the promise of integration. Elementary School As noted in the previous section, only 26 percent of elementary schools report offering instruction in computing (Banilower et al., 2018), suggesting that most learners in the United States do not encounter computing education in United States elementary schools. In fact, widespread efforts to provide computing experiences in the elementary grades are relatively recent. As a result, there is limited research on students’ learning experiences in computing in K– 5 classrooms. But the research and reports that do include elementary school teachers shed important light on the features and availability of computing education for younger children in schools. A school-wide study of computing education at a high-poverty elementary school shows the potential of an integrated approach. The school committed to integrating computational thinking into instruction school-wide. Seven teachers and two administrators were chosen as focal cases for the study; four were classroom teachers and three taught special subjects (art, technology, library/media). All four participating elementary classroom teachers in the study chose to integrate computing lessons into science and mathematics curriculum (Israel et al., 2015a). The teachers suggested that the primary reason they successfully integrated computing education in their classrooms was because integration did not require additional instructional time already designated for other subjects. In contrast, the instructional specialists focused more on discrete computing skills, using CS unplugged activities, Code.org resources, and Scratch tutorials. Adopting an interdisciplinary approach to teaching computing can encourage teachers to draw upon their existing content knowledge to make connections to computing-related concepts and skills. In fact, teachers are eager to know more about effective ways to integrate computing into other K–5 subjects (Roberts, Prottsman, and Gray, 2018). While teachers might be able to begin imagining these interdisciplinary connections, however, a qualitative study of teachers from one school district reveals teachers’ concerns about integrating computing into their teaching due to limited class time and having difficulty in identify instances in which connections could be made between computing and science and computing and mathematics (Rich, Yadav, and Schwartz, 2019). Another potential obstacle is the perceived mismatch between the accepted best practices across disciplines. Even with these impediments, elementary teachers point to benefits they appreciate for their learners as a result of teaching CS, including their learners’ interest in computing, capacity in problem-solving, improvements in learners’ attitudes and confidence, and an increased resilience to stick with problems, even after missteps or iterative failures (Rich et al., 2019). Similarly, a study probing elementary computing education paired together preservice teachers and undergraduate CS learners to collaborate with elementary classroom teachers to design and Prepublication Copy, Uncorrected Proofs 6-3

deliver ten hours of instruction, over ten weeks, in two districts chosen due to their “suburban and rural settings with participants from culturally diverse and economically disadvantaged backgrounds” (Tran, 2018, p. 8). The research revealed learning gains in specific CS concepts related to algorithm, loops, and debugging, as well as increased interest in computing, and positive dispositions around perseverance. Middle School As noted above, only 38 percent of middle schools offer instruction in computing. Over 80 percent of middle school mathematics and science teachers report never integrating coding into their classes (see Table 7.1; Banilower et al, 2018). There are promising examples, however, for integrating computing into other subjects (Basu et al., 2016; Grover, 2011; Sengupta et al., 2013; Weintrop et al., 2016). Bootstrap, a curriculum that supports learners in programming a video game of their own design, integrates programming concepts into algebra, physics, and data science instruction (Schanzer et al., 2015). With the focus on algebra, Bootstrap has been used at both the middle school and high school levels. This curriculum has goals in terms of increasing learners’ interest and knowledge about CS, but also has goals that facilitate the improvement of problem-solving around algebra word problems (Schanzer et al., 2015, Schanzer, Fisler, and Krishnamurthi, 2018). Schanzer et al. (2015) reported that learners exhibited some evidence of transfer of learning when provided with the opportunity to take Bootstrap as compared to a control group (that had not taken Bootstrap). Similarly, Project GUTS approaches computing education through the integration of week-long curricular units on agent-based modeling in middle school science classrooms (Lee et al., 2011). Both of these middle-school oriented computing curriculum offer PD to support teacher integration of these learning resources; however a limitation of this work is the degree to which transfer of learning can occur between computing and other content areas (Schanzer et al., 2015). There are potentially some organizational advantages to integrating computing into other courses instead of creating a stand-alone course. For example, an integrated approach does not require making space in the schedule or hiring additional staff. Indeed, one study of Utah’s middle school teachers noted that teachers have difficulty “fitting” CS into their teaching schedules and into the selection of learners’ elective choices (Rich and Hu, 2019). However, these teachers also noted they felt under-prepared and under-supported to teach computing. Computing in Elementary and Middle School Summary In sum, less than half of schools across the country are providing robust opportunities to learn computing at the elementary and middle school levels. Integrating computing into other courses, such as mathematics and science, seems like a promising approach. However, teachers need opportunities to develop the knowledge and skill to support this integration. Further, little is known about the nature of the learning experiences themselves in elementary and middle school. This makes it difficult to assess whether they incorporate features that the committee might consider to be either professionally or personally authentic. It does appear, however, that there may be missed opportunities to incorporate authentic experiences for computing at the elementary and middle school levels. Prepublication Copy, Uncorrected Proofs 6-4

COMPUTING IN HIGH SCHOOL High schools have a long history of including computing education in the curriculum, mainly as stand-alone computing or computer science courses. Recent years have seen a shift from computing-related courses being offered only in advanced, enrichment spaces towards computing being offered as a core part of a well-rounded school curriculum for all learners. Making space for computer science within an already-crowded secondary school curriculum has been variable across U.S. public schools (Banilower et al., 2018; Nager and Atkinson, 2016). State and district policies diverge in their requirements and awarding of academic credit towards graduation for learners who complete high school computer science courses. According to survey responses from NSSME+, in 3/4 of high schools, even when CS courses are offered, they are considered “elective” in that they are not required for graduation and only a small percentage allow CS to count towards graduation requirements in other subjects (Banilower et al., 2018). Only 1 percent of schools require 2–4 years of coursework in computer science for graduation, 17 percent of schools require 1 year of coursework, and 8 percent of schools require a semester of coursework (Banilower et al., 2018). Further, some schools apply academic coursework in computer science towards other disciplinary graduation requirements. The NSSME+ study notes that computer science counts towards a mathematics graduation requirement in 15 percent of schools, as a science graduation requirement in 12 percent of schools, and as a foreign language requirement in 7 percent of schools. High schools offer a variety of courses in computing or computer science (see Table 6-3). These include courses for which students may receive college credit (AP, IB and dual enrollment) as well as those that do not qualify for college credit. As noted in the overview section of the chapter, the availability of learning opportunities in computing are not proportionately distributed across high schools. Instead, these opportunities are more prevalent in schools enrolling learners from high-income communities as well as schools in which the majority are White, especially for advanced high school courses (Banilower et al, 2018). Advanced Placement Courses in Computer Science In general, AP courses, including CS courses, are offered by the College Board to provide advanced learning opportunities at the secondary school level. Learners who score particular grades on an end of course exam might have the opportunity to earn college credit, depending on the college they go on to attend. For computer science there are two courses offered: Computer Science A (CSA) and Computer Science Principles (CSP). Nager and Atkinson (2016) have shown that there is a lack of women and minorities not only taking these courses, but also going on to take the exam. Though these advanced courses are important in many computing education high school pathways, the distribution of AP courses across school sites is uneven, privileging large, suburban and urban, and more affluent schools. Specifically, studies have demonstrated the following inequities in course availability (Banilower et al., 2018; Scott et al., 2019):  Large schools are more likely to have AP computer science than small schools;  Rural schools are less likely than suburban or urban schools to offer AP computer science; and  High-poverty schools are less likely than low-poverty schools to offer AP Prepublication Copy, Uncorrected Proofs 6-5

computer science. Computer Science A CSA, first introduced in 1984, aims to give learners a comparable experience to a first semester undergraduate computer science course. The course focuses on object-oriented programming and data structures, with Java as the primary emphasis and designated programming language of the course (College Board, 2014). Though the AP CSA course has been offered for decades, until recently the number of test-takers was relatively low compared to other AP mathematics and science courses, with only 15,000 learners taking the test a decade ago (College Board, 2008). Since then, participation in the AP CSA exam has surged with a student participation growth rate of between 9 percent and 26 percent each year through 2017. In 2017, 60,519 learners completed the AP CSA exam (College Board, 2017), with 5,040 schools across the United States offering the exam. Within the AP program, of all the AP course offerings across STEM areas, CSA has historically sustained the lowest rates of participation for minoritized populations (Sax et al., 2020). Of test-takers in 2017, girls represent 24 percent of participants; Native Americans constitute 0.2 percent of participants, African Americans make up 4 percent of participants, Latinx learners make up 12 percent of participants, and Native Hawaiians and Pacific Islanders make up just 0.1 percent of participants (Sax et al., 2020). Lim and Lewis (2020) recently proposed three metrics for evaluating the impact of state-level initiatives aimed to broaden participation in computing at the high school level. Enrollment in CSA in high school has been shown to better predict interest and persistence in technology and computing for college women (Weston, Dubow, and Kaminsky, 2019), compared to technology internships or participation in other computing-related activities before college. In fact, a large sample of surveyed college freshman revealed that 28 percent of learners who take AP CSA planned on majoring in computer science (Sax et al., 2020). Computer Science Principles In a concerted effort to broaden participation in computing, the College Board and the National Science Foundation joined together in 2008 to design, develop, and implement Computer Science Principles (CSP), described as a more accessible, college-level computer science course (Cuny, 2015; Sax et al., 2020). CSP aims to be equivalent to a non-CS majors introduction to computing course. After eight years of development and piloting, the course was launched in 2016 (Kamenetz, 2017). In 2017, the first year of the course, over 44,000 students at 2,625 schools took the exam (College Board, 2017). In 2018, 70,000 students at 4,022 schools took the exam (College Board, 2018). The focus of the course is on appreciating the big ideas of computer science. The CSP course includes seven core computing concepts (creativity, abstraction, data and information, algorithms, programming, the Internet, and global impact) and six computational practices (connecting computing, creating computational artifacts, abstracting, analyzing problems and artifacts, communicating, and collaborating) (College Board, 2020). In an effort to focus more on the principles and interdisciplinary nature of computer science, the course and exam are programming-language agnostic (Nager and Atkinson, 2016), allowing for instructors to select Prepublication Copy, Uncorrected Proofs 6-6

the programming language they deem most appropriate for student success in their own classrooms. Also unique to CSP, in comparison to other AP courses, is a through-course, teacher-supervised, task-based performance assessment (the Create Performance Task: Application to Ideas) that is a portion of a learner’s final AP score. While preliminary evidence suggests that students who enroll in CSP are more diverse with respect to gender, race, and ethnicity (although no differences were observed for some groups) than CSA learners, students who took CSP are less inclined to indicate their intent to pursue CS majors and careers than students who complete CSA (Howard and Havard, 2019, Sax et. al, 2020). Even in the specifically-designed-to-broaden-participation AP CSP course, the course has not attracted a heterogenous and representative population of learners that reflects the demographics of learners in public schools. Amongst the inaugural group of CSP exam-takers in 2017, girls comprised 30 percent of test-takers, and only 28 percent of learners were Black, Latinx or Indigenous (College Board, 2017). Equity in AP Computer Science Courses Both CSA and CSP are taken predominantly by men and the number of enrollees is lower in contrast to other AP courses in mathematics and science. In 2019, CSP test takers consisted of 32 percent women with CSA test takers consisting of 24 percent women. In contrast, AP Biology was 62.6 percent women and AP Calculus AB was 49 percent women. Table 6-4 presents the number of exam-takers in the CS AP exams as compared to other STEM exams, such as Biology and Calculus AB. Overall, the percentage of Black and Latinx learners completing the AP CSA exam was lower, with fairly comparable percentages observed for AP CSP as compared to AP Biology and AP Calculus AB. This reinforces the known patterns of underrepresentation by race and ethnicity in STEM fields (see Chapter 2). The Exploring Computer Science Course The Exploring Computer Science (ECS) course, developed in 2008 with National Science Foundation support, provides a foundational approach to introducing computer science to learners with no assumption of prior knowledge or experience in computing. The introductory ECS courses’ primary goal is to introduce computer science at a level that is highly accessible for all high school learners. The goal is to promote equity by engaging a broad range of learners in an inclusive approach to CS to build foundational knowledge about computer science. Currently offered in schools across 34 states and Puerto Rico, ECS enrolls about 55,000 learners each year.2 The ECS course originated in Los Angeles and demographic data from Los Angeles suggests that the ethnic and racial representation matches that of Los Angeles learners more generally, and 43 percent of ECS learners in Los Angeles are girls.3 These numbers, along with evidence in growth of student efficacy, increased interest in computing, and sense of belonging gains, suggest that this course may successfully engage girls and Black and Latinx learners in CS (Dettori et. al., 2016; Goode and Margolis, 2011). The course includes a complete year-long curriculum that includes the following possible instructional units: human computer interaction, problem solving, web design, programming, 2 For more information, see http://www.exploringcs.org/about/about-ecs. 3 Additional data and information can be found here: https://www.exploringcs.org/for-researchers- policymakers/reports/ecs-enrollment-data. Prepublication Copy, Uncorrected Proofs 6-7

data and analysis, robotics, electronic textiles, and artificial intelligence. Importantly, the ECS courses also includes a two-year PD program for teachers that focuses on inquiry-based teaching and anti-racist instruction (Goode, Chapman, and Margolis, 2012; Goode, Johnson, and Sundstrom, 2020), as well as a validated and open-ended assessment tool to gauge student learning. Learners who took ECS as their introductory computing course, as compared to more traditional programming-centric computing courses, were twice as likely to go on and take more advanced coursework (McGee et al., 2018). Learners who completed ECS before taking the AP CSA course also out-scored their peers by 1/3 point on the 5-point AP CS A exam (McGee et al., 2019). The inclusion of e-textiles as part of the ECS curriculum has been a recent (2018) and novel addition as a supplemental unit (Unit 6: Electronic Textiles), done in an effort to incorporate makerspaces in schools, and in particular, to offer tactile approaches to learning that combine computing, circuitry, and crafting. A study that accompanied the introduction of e- textiles unit in 17 ECS classrooms in Los Angeles detailed how teachers adjusted their pedagogical practices to support creativity, connection, and culturally responsive student learning. The study mapped out how rich and equitable teaching practices in computing and making can move learners from initial engagement into more complex projects that deepened their learning experiences. As the study concludes, this approach in placing e-textiles in a project-based computing curriculum with extensive PD for teachers “addresses a piece of the puzzle that has been missing in connecting informal and formal implementations of making activities” (Fields et al., 2018; p. 16). ECS seem to be a potential context for incorporating authentic experiences in computing that focus more on personal authenticity. The ECS course is designed around project-based learning, engaging learners in learning activities that apply conceptual knowledge, and allows learners to craft original computational creations. The course is aligned with foundational K–12 computing standards; its goal is to reach the general student population through inclusive, equity- based instruction that counters the dominant practices in professionally authentic technology settings. Career and Technical Education Courses Career Technical Education (CTE) courses provide a direct connection with careers and pathways to industry. These high school courses, funded in part by federal Perkins funding, vary greatly between states and schools, yet often have an applied focus to computing curriculum. Examples of these types of courses include professional certification on specific technical competencies that transfer directly to professional work settings such as Networking, Software Engineering, or Cybersecurity. The applied courses in these programs are geared towards learners already interested in technical careers and seek to closely mirror existing workplace tools, knowledge, and skills. The typical course composition of STEM-related CTE courses suggest they are not gender-inclusive (Lufkin et al., 2007), with girls composing 32 percent of learners nationally in the IT concentration of CTE pathways in (Perkins Data Explorer, 2020). It is worth acknowledging that there was a history of placing learners into a CTE track (Goode, Flapan, and Margolis, 2018); however, both ECS and CSP are also taught as CTE courses.4 4 For more information, see: https://ecepalliance.org/sites/default/files/RethinkingPerkins_Paper.pdf. Prepublication Copy, Uncorrected Proofs 6-8

High School Experiences Summary Although computing education has had a longer history within high schools as compared to elementary and middle school spaces, primarily as stand-alone courses, computer science is typically considered as an elective and not a requirement towards graduation. Moreover, despite efforts to design AP CS courses to address known inequities in learner participation, underrepresentation of women and learners of color persist. The Exploring Computer Science course was designed to introduce learners to computing with no assumption of prior knowledge or experience in computing. This course has shown some promise in promoting equity as findings suggest that learners who complete this course are more likely to go on and take more advanced coursework. EQUITY AND ACCESS IN COMPUTING IN SCHOOLS While there have been ongoing efforts to expand learning opportunities for computing in schools, there are still disparities in access and participation. There are multiple factors contributing to these trends. In secondary schools, classroom teachers are the primary instructors of stand-alone CS classes. The characteristics of high school CS teachers are similar to those of high school science and mathematics teachers in some areas and markedly different in others (Banilower et al., 2018). Similar to science and mathematics teachers, nearly all high school CS teachers characterize themselves as White (94%), and most are older than 40. In contrast with most K–12 teachers, the majority of CS teachers (60%) are men. The dramatically low numbers of Black, Indigenous, and Latinx teachers represent a missed opportunity in terms of providing learners exposure to role models and pedagogies informed by minoritized perspectives and experiences in computing. In particular, women teachers of color bring important commitments to computing education in terms of serving learners from minoritized communities, connecting to community knowledge, and serving as a role model to their learners (Johnson et al., 2020). In addition to the problem of lack of diversity among teachers, structural inequalities and bias also play a role. In Stuck in the Shallow End: Education, Race, and Computing, Margolis et al. (2008; 2017) detail an ethnographic study examining student access and participation in computing learning across three demographically diverse high schools: an overcrowded urban high school, a math and science magnet school, and a well-funded school in an affluent neighborhood. The study revealed that systemic racism—which impacted access learners had to course offerings, qualified teachers, and school resources, accompanied by educator belief systems about which learners belong in computing classrooms—perpetuated race and gender differences in participation that were reproduced across each of the school sites. Research in this area highlights the importance of examining equity in school settings in terms of access to computing courses, necessary resources, and qualified teachers; as well as examining equity in terms of the quality of learning environments for learners that are characterized by inclusion, encouragement, effective pedagogy, and culturally relevant and responsive curriculum. Belief systems amongst educators play an important part in ensuring, or constricting, opportunities for learners. Educators’ biased beliefs about who belongs in CS and who might be interested in studying CS often are enacted in ways that reinforce and reify those ideas by guiding White and Asian boys towards—and Black and Latinx learners and girls away from— Prepublication Copy, Uncorrected Proofs 6-9

classroom learning experiences (Goode, Estrella, and Margolis, 2006; Margolis et al., 2017). One response, in this case aimed specifically at school counselors, comes out of the National Center for Women in Technology, which has developed a Counselors for Computing (C4C) program that provides an immersive PD and set of resources for school counselors to encourage counselors to understand and advocate for increased CS learning opportunities for learners at their schools (Hug and Krauss, 2016). Inside high school CS classrooms, multiple features have been identified that signal and support an inclusive learning ecosystem for learners. As first noted in Chapter 2, classroom learning spaces that support collaboration and avoid “geeky” stereotypical signifiers, such as posters or exclusionary discourse patterns, are important for creating a positive learning atmosphere for girls (Goode, Estrella, and Margolis, 2006; Master, Cheryan, and Meltzoff, 2016). When teachers connect computing curriculum to the lived experiences and values of learners (a tenet of culturally responsive teaching), there is strong student engagement, particularly amongst learners from minoritized groups (Madkins et al., 2019; Ryoo et al., 2013; 2019). Further, though there is only nascent research, scholars point to the visual nature of programming languages, and also to the tactile nature of creating electronic-textiles, in supporting the computing learning for English language learners in CS classrooms (Jacob et al., 2018); however, relying upon either the visual and/or tactile nature of these activities can be inaccessible to some learners (either because of impairments and in some cases, cost). In their study of learners learning computing in a bilingual middle school classroom, Vogel et al. (2019) note that the development of learners’ computational literacies are entwined with learners’ repertoire of other linguistic and discourse literacies. Their findings suggest that educators should not treat CS education as a fixed learning progression of concepts alongside “remediation” or “differentiation” for emergent bilinguals. Rather, they encourage educators to build upon the varied literacies learners bring to the classroom with potential computational literacies, for both bilingual and monolingual learners (Vogel et al., 2019). Professional and personal authenticity in learning experiences for computing provide other lenses for understanding the problems of equity in computing. In particular, authenticity has traditionally been considered to be discipline-driven, with experiences designed to reflect the practices of the discipline. As illustrated in Chapter 2, some learners may have stereotypes about the culture of CS—including the kind of people, the work involved, and the values of the field— and the emphasis on the professional practices may steer learners from underrepresented groups from engaging in authentic computing experiences (Cheryan, Master, and Meltzoff, 2015). However, curriculum that leverages learners’ interests, identities, and backgrounds (personal authenticity) may encourage increased participation of women, learners of colors, and those with differences in perceived ability (Eglash et al., 2006; Goode, Johnson, and Sundstrom, 2020; Israel et al., 2015a; Ryoo et al., 2020). PREPARING TEACHERS FOR K–12 COMPUTING CLASSROOMS The previous section helped to identify spaces in K–12 education where authentic learning experiences in computing could be situated. However, a key piece of doing this successfully is providing teachers with opportunities to develop the necessary knowledge and skills. In fact, the expertise of teachers is a key limiting factor in expanding computing in K–12 more generally, regardless of whether the learning opportunities are authentic in the way the Prepublication Copy, Uncorrected Proofs 6-10

committee has described. In this section we consider the knowledge and experience of the current cadre of computing teachers and describe professional development (PD) practices for supporting teachers of computing. Teachers’ Knowledge and Experience in Computing There are few direct measures of teachers’ knowledge of computing. Instead courses taken during preservice preparation, undergraduate degree, area of certification, and previous teaching experiences are all used as proxies for knowledge. In the NSSME+ there are also measures of teachers’ confidence in teaching computing. Elementary and Middle School Teachers In the United States, fewer than 1 in 4 elementary teachers reported having experience or just a “crash course” in computing before they began teaching computing to their learners. Not surprisingly, this lack of sufficient preparation can leave teachers apprehensive about their own knowledge and skills as they begin teaching computing to learners (Israel et al., 2015a; Rich, Yadav, and Schwarz, 2019). A study of elementary teachers demonstrated that those who participated in continuous PD around computing and engineering had statistically significant greater confidence in computing after a year than their elementary teacher colleagues who did not have access to this preparation, highlighting the importance of PD experiences (Rich et al., 2017). High School Teachers Scholarship on teacher knowledge in CS suggests that effective computing teachers are able to join together content, engaging pedagogy, knowledge of their learners’ identities and backgrounds, and understanding of the school context to engage learners in meaningful learning opportunities (Goode and Ryoo, 2019). Yet a recent large-scale survey of STEM teachers (Banilower et al., 2018) indicates that the current cadre of high school CS teachers have variable degrees of experience, knowledge, and capacity in these areas. Many CS teachers might have significant experience teaching high school but are new to teaching CS. Though nearly half of CS teachers have more than 10 years of experience teaching at the K–12 level, many are novice teachers of CS, with 35 percent of teachers having 0–2 years of experience and 28 percent of teachers having 3–5 years of experience teaching the subject (Banilower et al, 2018). In addition to being new to teaching CS, CS teachers are also teaching outside of their primary areas and/or are teaching CS in addition to other subjects (CSTA, 2015; Yadav et al., 2016). In terms of content knowledge, only 25 percent of high school computing teachers have degrees in CS. Still, most teachers have participated in CS college courses. In fact, 87 percent of high school teachers had completed at least one class in computing and two out of three teachers reported completing two or more college courses related to CS. Additionally, 35 percent all responding high school CS teachers reported prior job experience in the field of computing before they became teachers. However, the recency of the courses or job experiences before teaching is unknown. This experience with content-focused computing courses does not seem to translate to Prepublication Copy, Uncorrected Proofs 6-11

teachers’ sense of preparation in teaching CS. In fact, fewer than 50 percent of high school teachers feel confident in teaching any of the topics5 associated with high school computing courses, and compared with other STEM teachers, they generally feel less prepared to teach their subject-area content (Banilower et al, 2018). In terms of pedagogical preparation, of the 84 percent of CS teachers who hold teaching certifications, 44 percent have a CS teacher certification, 34 percent in mathematics, 28 percent in business, 10 percent in engineering, and 9 percent in science (Banilower et al., 2018). Yet, the survey also revealed that fewer than half of high school CS teachers feel prepared to encourage learners or develop capacity in a number of ways, such as encouraging learners’ interests in computing (49%), encouraging participation of all learners (45%), developing learners’ awareness of STEM careers (36%), or incorporating learners’ cultural backgrounds into CS instruction (16%). Given how few states award primary teaching endorsements in CS (see Box 6-2), the majority of preparatory learning opportunities for computing teachers occur in PD settings for in-service teachers, as will be discussed in further detail below. Professional Development in Computing for In-Service Teachers Because most teacher education programs do not offer computing methods courses (Yadav, Stephenson, and Hong, 2014), the primary place for teachers to learn about teaching computing takes place in curriculum-specific PD sessions. Research on teacher preparation for teaching computer science courses highlights the importance of sustained, long-term professional learning experiences that support the emerging content-related and pedagogical needs of teachers (Goode, Margolis, and Chapman, 2014; Menekse, 2015). This aligns with earlier research about necessary length and duration of effective professional learning programs for STEM teachers (Loucks-Horsley et al., 2009). Yet for most schools, PD opportunities for CS teachers are not plentiful, with only 19 percent of high school teachers noting that they had access to local PD opportunities in their school or district (see Table 6-5; Banilower et al., 2018). Instead, teachers took advantage of regional or national PD opportunities and online opportunities to learn about computing education. When computing teachers did participate in professional workshops, they reported that the most common emphases related to understanding and doing CS: deepening their CS content knowledge, including programming (70%); learning how to use programming activities that require a computer (64%); and deepening understanding of how CS is done (63%). Half of CS teachers’ PD has had a substantial focus on implementing the CS curricular materials to be used in their classroom. But only about a quarter of high school computing teachers have participated in professional learning that addresses meeting the needs of learners who are underrepresented based on gender, race, ethnicity, or perceived ability or incorporating learners’ cultural backgrounds into CS instruction, despite the known diversity issues in computing education (Banilower et al., 2018). Moreover, there is a lack of PD that specifically relates to computer science pedagogical content knowledge (Yadav and Berges, 2019; Yadav et al., 2016). In another professional learning structure, instructional coaches who work with teachers within the context of their own classrooms have been shown to be particularly effective in supporting the needs of novice CS teachers as they begin teaching new high school courses in schools (Dettori et al., 2018; Margolis, Ryoo, and Goode, 2017). In fact, in schools that offer CS, 5 These topics include algorithms and programming, impacts of computing, computing systems, data and analysis, and networks and the Internet. Prepublication Copy, Uncorrected Proofs 6-12

about one in five high schools offer instructional coaches to high school CS teachers (Banilower et al., 2018). The dynamic nature of computing can also provide ongoing opportunities for more seasoned computing educators to augment their knowledge and learn to incorporate new technologies. Promising approaches have been demonstrated to recharge (as self-reported by teachers as a renewal in excitement through reflection) the teaching practices of experienced teachers in CS classrooms (Nakajima and Goode, 2019) as they learn to incorporate electronic textiles in their classrooms. In addition to individual professional development around content, pedagogy, and engaging diverse groups of learners, teachers also report deeply valuing their membership in sustained face-to-face and online CS teacher learning communities as a way of learning from peers and breaking the school-level isolation they experience at their schools as the sole computing teacher (Goode, Johnson, and Sundstrom, 2020; Ni, 2011; Ryoo, Goode, and Margolis, 2015). SUMMARY Formal educational experiences are important settings for engaging learners in authentic computing experiences that have the potential to influence interest and competencies for computing. But, as for any context, the conditions have to be right. Schools have the opportunity to provide experiences that may allow for sustained engagement, which is important for developing learners’ individual interests in computing. However, just as with out-of-school time settings, formal educational environments may not be able to provide experiences due to lack of resources and adequate teacher preparation, or learners may find that the options are not engaging. Moreover, the opportunities in formal educational context are inequitably distributed. Not only are there more opportunities available in high school as compared to middle and elementary schools, large schools, low-poverty schools, and suburban/urban schools are more likely to offer AP CS courses (Banilower et al., 2018). Additionally, women and learners of color continue to be underrepresented in AP CS courses. Overall, this chapter has considered how professionally and personally authentic experiences with computing have been offered in United States schools across K–12 settings. The review highlighted that although course offerings are variable and inequitably distributed across schools, there are also promising practices and approaches that support more foundational approaches to bring computing education to all learners. Prepublication Copy, Uncorrected Proofs 6-13

BOX 6-1 Moving Computer Science into the Core of Chicago Public Schools Not all policies that support and embed CS instruction into the core curriculum are at the state level. Chicago Public Schools, the third largest school district in the nation, has evolved as the leader in creating systems-level changes to realize the aspiration of providing all learners a CS education. In fact, beginning with 2020, all learners in high school are required to successfully complete an introductory CS course in order to graduate. This course requirement has reflected a decade of collaborative leadership in the district amongst teachers, district leaders, higher education, computing educational organizations, and city officials. A decade ago, computing education opportunities were scarce in most schools, and when learning opportunities were offered, they were in selective STEM schools in the district. In 2008, a group of Chicago teachers were attending a Computer Science Education conference in Oregon. They independently attended a panel discussion of the Association for Computing Machinery’s Education Policy Committee about the need to expand and broaden K–12 CS education. One of the teachers stood up and asked who he might work with to address this issue in Chicago, connecting him with other Chicago teachers in the room, the Computer Science Teachers Association community, and ultimately, higher education faculty with shared visions of expanding an equitable vision of CS for all. Members of this growing local community of educators attended the ECS PD offered for Los Angeles teachers in 2010, and deciding that it was an ideal fit for Chicago Public Schools, successfully obtained a series of grant awards from the National Science Foundation to initially offer, then scale, this course and associated PD in Chicago. The leaders of this movement note that the failures allowed for learning that systemic change requires trust and the need to develop relationships along the way. Along with this bottom-up approach led by educators and centering on curriculum and PD, creating systemic change also required the support of city and school district leadership. In announcing an initial partnership with Code.org in December of 2013, the mayor and Chicago Public Schools CEO established a five-year goal to provide CS learning pathways in high schools. Along with this goal to scale ECS courses to each high school, a robust CS education district team has been created to support and sustain these district-wide teaching and learning efforts while expanding learning pathways into K–8 classrooms. Leadership also elevated computing to a “core subject” district-wide. Galvanizing this top-down institutional and political support has been critical for realizing the wide-scale vision that was initially sparked by a group of Chicago teachers. With the majority of all learners taking CS, the school district, evaluators, and researchers are collecting additional data on the supports and impact of systemic changes in computing education that will further the district’s stated equity goals of reaching “for all” (Dettori et al., 2018). SOURCE: Committee generated based on Reed et al. (2015) and Dettori et al. (2018). Prepublication Copy, Uncorrected Proofs 6-14

BOX 6-2 Teacher Certification Few states currently offer CS teacher certification. A 2017 report from Code.org mentions only two explicitly.6 The Home4CS report Priming the Computer Science Teacher Pump7 (DeLyser et al., 2018) tells us that only 2 out of 50 states and the District of Columbia (4%) require CS certification/licensure for teachers to teach any CS course, and only 7 states (14%) require it to teach AP Computer Science. To get a sense of trends in teacher certification in the United States, the landscape reports issued by the Expanding Computing Education Pathways (ECEP) Alliance can be useful. The ECEP Alliance is funded by the National Science Foundation (NSF) to broaden computing education participation by supporting states in implementing computing education.8 ECEP encourages its member states to prepare landscape reports that describe computing education in that state. In Indiana, as in many states, CS is classified as a CTE course. A business certification allows a teacher to teach CTE classes such as CS. Indiana has a Computer Education License which requires teachers to be knowledgeable about a breadth of topics from web design and computer applications, to library media and technical repair support. The definition of computing education is vague and tends to include a large number of topics. Only Indiana University- Bloomington (IU) and Ball State University (BSU) offer preservice teacher education for computing education. In both of these programs, teachers need to achieve an elementary or secondary education certification, and then they can add-on the computer education license. These programs are fragile. Purdue University had a program until the sole faculty member supporting the program left in 2013, and the program formally closed in 2016. These programs will have to be more robust to be successful at growing computing educators systematically. In South Carolina, researchers found even less opportunity for teachers to pursue PD or certification in CS. There is no certification or program in higher education to prepare teachers in computing education in South Carolina. Part of the challenge for South Carolina in developing such programs is the lack of statewide standards in computing education; a lack of definition makes it difficult to grow teacher programs in computer science and, consequently, increase the number of CS teachers. The absence of teacher programs and the lack of clearly-defined standards have had an effect on K–12 learners. Texas has a rigorous CS education certification process; however, relatively few teachers pursue certification. The CS certification process requires teachers to be equipped with a significant number of technical skills and involves developing a proficiency with topics such as software design and programming, loops and recursion, data structures, object-oriented programming, algorithms, Big-O notation, discrete math, digital forensics, robotics, and game and mobile app development. CS teacher certification in Nevada is based on Praxis exams. In states that allow certification by examination, there may less incentive to create preservice programs. While the definition of what is computing is clear when testing by exam, preparation is the responsibility of the teacher, more typically in-service. 6 See https://code.org/files/TeacherPathwayRecommendations.pdf. 7 See https://www.computingteacher.org/. 8 For more information, see https://ecepalliance.org. Prepublication Copy, Uncorrected Proofs 6-15

SOURCE: Committee generated based on reports available at https://ecepalliance.org. Prepublication Copy, Uncorrected Proofs 6-16

TABLE 6-1 Mathematics and Science Classes in Which Teachers Report Incorporating Coding into Mathematics Instruction, by Grade Range Mathematics ELEMENTARY MIDDLE HIGH Never 74 (2.0) 86 (2.1) 89 (1.0) Rarely (e.g., A few times per year) 15 (1.7) 11 (1.6) 9 (0.9) Sometimes (e.g., Once or twice a month) 7 (1.1) 3 (1.3) 2 (0.4) Often (e.g., Once or twice a week) 3 (0.8) 0 (0.3) 1 (0.2) All or almost all mathematics lessons 0 (0.3) 0 (0.1) 0 (0.1) Science Never 71 (3.4) 81 (1.9) 89 (1.2) Rarely (e.g., a few times per year) 16 (2.0) 14 (1.8) 6 (0.9) Sometimes (e.g., once or twice a month) 11 (2.8) 3 (0.8) 4 (0.8) Often (e.g., once or twice a week) 3 (0.7) 1 (0.5) 0 (0.1) All or almost all science lessons 0 ---† 0 (0.3) 0 (0.0) SOURCE: Banilower et al. (2018). Prepublication Copy, Uncorrected Proofs 6-17

TABLE 6-2 School Programs and Practices to Enhance Students’ Interest and/or Achievement in Computer Science, by Grade Range (percent of schools) Programs/practices Elementary Middle High Holds family computer science nights 15 (2.0) 8 (1.5) 5 (1.0) Offers after-school help in computer science 14 (1.8) 20 (2.1) 31 (2.8) (e.g., tutoring) Offers formal after-school programs for 21 (2.3) 21 (2.6) 15 (1.8) enrichment in computer science Offers one or more computer science clubs 22 (2.4) 25 (2.3) 29 (2.2) Participates in Hour of Code 38 (2.8) 34 (2.8) 27 (2.6) Participates in a local or regional computer 11 (1.9) 13 (2.1) 12 (1.5) science fair Has one or more teams participating in 6 (1.3) 10 (1.5) 15 (1.6) computer science competitions (e.g., USA Computer Science Olympiad) Encourages students to participate in 38 (2.9) 44 (3.3) 51 (2.6) computer science summer programs or camps offered by community colleges universities museums or computer science centers Coordinates visits to business industry and/or 14 (2.3) 22 (2.8) 30 (3.0) research sites related to computer science Coordinates meetings with adult mentors 14 (2.0) 18 (2.1) 22 (1.9) who work in computer science fields Source: Banilower et al. (2018). Prepublication Copy, Uncorrected Proofs 6-18

TABLE 6-3 High Schools Offering Computer Science and Technology Courses Course Percent of Schools Advanced Placement (AP) computer science courses 21 (1.6) International Baccalaureate (IB) computer science courses 1 (0.4) Concurrent college and high school credit/dual enrollment computer 19 (1.9) science courses Computer technology courses that do not include programming 47 (2.4) Introductory high school computer science courses that include 36 (2.4) programming but do not qualify for college credit Specialized/elective computer science courses with programming as 21 (1.7) a prerequisite that do not qualify for college credit SOURCE: Banilower et al. (2018). Prepublication Copy, Uncorrected Proofs 6-19

TABLE 6-4 Contrasting Participation in the 2019 AP CSP and CSA Exams versus AP Biology and AP Calculus AB AP CSP AP CSA AP Biology AP Calculus AB Overall 94,360 64,197 253,212 285,923 Black 6,559 (6.9%) 2,521 (3.9%) 16,484 (6.5%) 14,037 (4.9%) Latinx 18,601 (19.7%) 7,728 (12.0%) 48,512 (19.2%) 51,365 (18.0%) NOTE: It should be noted that during this reporting period, 4,930,147 exams were administered. However, it is not known how many individual learners this translates to as a learner can take multiple exams. SOURCE: College Board (2019). Data are available at: https://secure- media.collegeboard.org/digitalServices/misc/ap/national-summary-2019.xlsx. Prepublication Copy, Uncorrected Proofs 6-20

TABLE 6-5 Computer Science-Focused PD Activities Offered in the Last Three Years Type of PD activity Elementary Middle High Professional Development Workshops 35 (2.5) 28 (2.4) 19 (1.9) Teacher Study Groups 43 (3.1) 41 (3.3) 33 (2.9) One-on-One Computer Science-Focused Coaching 28 (2.4) 27 (2.3) 21 (2.3) SOURCE: Banilower et al. (2018). Prepublication Copy, Uncorrected Proofs 6-21

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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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