7

Designing Authentic Experiences for Computing

Throughout this report, the committee has emphasized that learning is an active process that is social, embedded in a particular context, and enhanced by intentional support provided by knowledgeable individuals, be they peers, mentors, or teachers. These contexts can exist in formal or out-of-school-time settings, which have different affordances and constraints associated with them. Moreover, learning takes place across space and time, suggesting a need for partnerships, brokering, and connections made across settings. However, the evidence on whether and how authentic experiences develop interest and competencies for computing is still emerging. Based on the evidence to date, the committee offers broad guidance to program designers.

This chapter is written to serve as a guide to readers who wish to design authentic experiences for computing that attract and support diverse learners. The committee identifies important questions to ask and issues to address during the design process. As a starting point, this chapter begins with a discussion of why design matters; that is, why having a clear and intentioned set of goals and emphasis on authenticity is critical in the design of experiences. The chapter then offers a number of considerations for design that may be important for facilitating the development of interests and competencies in computing.

WHY DESIGN MATTERS

Stakeholders have a vested interest in science, technology, engineering, and mathematics (STEM) and computing for a wide variety of reasons

that may or may not be explicit. However, it is important for design, in any context, to begin with a sense of “why” and “for what purpose” one is designing. That is, designers need to have a clear and intentioned set of goals in the beginning when setting up and designing the program or experience (Laporte and Zaman, 2016; Li et al., 2019; Plass, Homer, and Kinzer, 2014). Having an explicit understanding of the purpose and clearly articulated goals for design allows for better alignment between intentions and actions.

Brennan (in press) synthesized the research to uncover the why for computing and identified three broad categories of goals: general education (i.e., technological literacy, learning and skill development); affective (i.e., identity development, supporting creative agency); and economic/societal (i.e., civic engagement, economic opportunities, and workforce development). The first is essential for equitable participation in society; the second is important for laying the foundation for equitable access to computing occupations; and the third is important for our economic and social well-being in the long term. It is worth noting that these categories can overlap and that the why of a program or experience can have multiple goals; however, many programs appear to have vague or unspecified goals.

When considering these various programmatic goals, it is important to consider how authenticity is being prioritized, as its use has been inconsistent across learning and research (Strobel et al., 2013). The two forms of authentic experiences identified by the committee—professional authenticity and personal authenticity—can play a big role in shaping the intention of design. It is critical to integrate disciplinary content with the practices and contexts of that discipline (i.e., cultivating professionally authentic experiences), and it is equally critical to connect this disciplinary content with a learner’s environment and prior knowledge (i.e., cultivating personally authentic experiences). That said, providing experiences that are both professionally and personally authentic is difficult, as there is often a tension between professional and personal authenticity that the design of learning experiences must address. If the goal of the program or experience is meant to align with the practices of the discipline (i.e., to provide a professional authentic experience), then it is worth recognizing the ways in which these practices may be at odds with the cultural and experiential background of the learners involved (see Chapter 2).

Overall, answering why will vary from context to context. However, once answered, the why informs what it is that learners are expected to know or to be able to do. In the remainder of this chapter, we discuss design considerations that may support the creation of authentic experiences that serve to develop interests and competencies in computing.

DESIGN CONSIDERATIONS

As suggested above, the first step in design is to have a clear set of goals and expectations for the learning experience. From there, a number of different features, or characteristics of design, are important to consider. The committee approached the work through the lens of diversity, equity, and inclusion. Unfortunately, as illustrated in Chapter 2, STEM educational and professional environments have historically been profoundly inequitable and unjust spaces (Bobb, 2016; Lewis, Shah, and Falkner, 2019; Ryoo et al., 2019). Design has the potential to exacerbate those inequities and injustices, or to redress them, advancing a vision of learning and participation that is diverse, equitable, inclusive (DEI), and promotes belonging. Throughout the chapter, the committee calls attention to elements of design that serve to promote participation of learners traditionally underrepresented based on gender, race, ethnicity, or perceived ability.

The committee offers a set of seven design considerations, which include (1) Learners; (2) Community; (3) Activities; (4) Environment; (5) Duration; (6) Tools; and (7) Iteration. For each of the design considerations, there are questions to keep in mind that can have an impact on design. Table 7-1 lists some of these possible questions, which are not intended to be all-inclusive but only serve as a starting point.

Before delving into each of the different design considerations, there are a few important points to highlight. These design considerations serve as a guide and are not intended to be interpreted as a set of “boxes to check.” Although the committee presents examples to illustrate how a program may have approached a particular issue, these examples are illustrative, not exhaustive, and may not reflect the realities for all environments. It is crucial to consider the local context and infrastructure in place when designing a program or experience. Additionally, the design considerations are nonlinear and interdependent (National Research Council [NRC], 2009). Decisions made for one aspect of design can have implications for one (or more) of the others. For example, if the program is designed to enhance interest and identity for a particular population of learners, this not only applies to the “learners,” but also affects many of the other design considerations (e.g., the social aspects of design [community], whether the activities are meaningful for the learner [activities], and whether the physical space is conducive to support the activity [environment]).

As stated above, learning takes places across space and time. Fundamental to design is considering the ways in which partnerships and connections across settings can be established. For example, Chapter 5 noted that museums can play a role in developing curriculum materials and providing professional development opportunities. It may be advantageous to create a partnership so that the relevant expertise can be leveraged and resources

TABLE 7-1 Potential Questions RE: Designing Authentic Experiences for Computing

shared, so that capacity within the ecosystem can be developed (Allen, Lewis-Warner, and Noam, 2020; Traill, Traphagen, and Devaney, 2015; Vance et al., 2016). The STEM Learning Ecosystems Community of Practice framework includes “cultivating dynamic, diverse partnerships; experimenting with creative means of partnering across sectors; and increasing the quantity and quality of active, inquiry-based formal and informal STEM learning opportunities for all, including young people historically underrepresented in STEM” (Allen, Lewis-Warner, and Noam, 2020, p. 31).

Finally, important for this report, these types of experiences can be designed across a range of settings to include in-school and out-of-school activities (e.g., clubs, libraries, museums, other youth-oriented organizations, and households) (NRC, 2009). Although there are a number of differences across the various settings (highlighted in the preceding chapters), the design considerations are intended to have broad applicability. What follows is the evidence for each design consideration and example programs that are suggestive of showing promise.

Learners

As is true for almost all designed experiences, it is important to consider the individuals who will participate in (or engage with) the experience. Researchers have been examining how having a deeper understanding of the learners involved, beyond simple numbers or basic demographics, can enable the development of a more robust, personally meaningful authentic experience (Calabrese Barton and Tan, 2019; Cornelius-White, 2007; Eccles and Wigfield, 2002; Farrington et al., 2012; Guzdial, 2015; Immordino-Yang and Damasio, 2007; Pintrich, 2003; Roorda et al., 2011; Weinberg, Basile, and Albright, 2011). In particular, as called out in Table 7-1, it is worth considering both “who are the learners” and “how are learners’ prior experiences acknowledged and incorporated into the design.”

Who Are the Learners?

There are a number of basic and key demographics that can have differential impacts on the design of authentic experiences for computing. These demographics include (but may not be limited to) age/grade, gender, sexual orientation, race, ethnicity, income, language ability, prior knowledge, learning ability and disability status, and geographical location. Such categories may be fluid at any given time, may change over time, and may overlap or inform one another (Ashcraft, Eger, Scott, 2017; Rodriguez and Lehman, 2018; Thomas et al., 2018). Each of these categories (and the way they may intersect with and interact upon one another) can have implications for the ways in which an experience can be structured.

A first step may be determining whether the materials are suitable or developmentally appropriate, which is crucial, given the progression of learning that takes place across age or grade levels. Previous research shows that learners as young as age 4 can learn simple programming concepts (Bers, 2007; 2012); however, most tools target learners ages 7–8 and older (Flannery et al., 2013). Younger learners may have trouble with the technical aspects of reading (that may be associated with strict syntax of text-based computer languages) as well as may lack the dexterity needed to use a mouse or touchpad to move elements around on the screen (Bers, 2018). ScratchJr and KIBO (a tangible robotics kit) have been developed for learners in early childhood spaces. These programs are built on the premise that these young learners can learn and apply programming concepts and problem-solving (Bers, 2018; Flannery et al., 2013; Portelance, Strawhacker, and Bers, 2016).

The strict syntactic demands of programming languages may be an obstacle to English Learners (ELs); linguistic scaffolding and culturally responsive pedagogies (discussed in the next section) can be supportive and effective (Jacob et al., 2018). The use of everyday language, as opposed to content-specific vocabulary, may help ELs learn and master disciplinary concepts as well as develop English proficiency (Jacob et al., 2018; National Academies of Sciences, Engineering, and Medicine [NASEM], 2018c). Inquiry-based practices have also been suggested to be promising when working with ELs in STEM (Estrella et al., 2018). Jacob et al. (2020) found that a more structured inquiry approach—use of modeling techniques, simulating algorithmic processes, physically enacting computational concepts, and incrementally increasing levels of complexity (p. 7)—led to the development of interest and competencies (more sophisticated computational artifacts) for computing.

For learners who may vary in their learning ability and needs, including those with physical disabilities, explicit focus on the principles of Universal Design for Learning is needed (Israel, 2019; Israel et al., 2015a,b;

King-Sears et al., 2014; Ok et al., 2017; Ralabate, 2016; Van Merriënboer and Sweller, 2005). Moreover, computing can be used to facilitate learning. Peppler and Warschauer (2011) details a case example of “Brandy,” a 9-year-old girl with cognitive disabilities and little reading or writing ability, and her use of Scratch. During the 2.5-year observation period, Brandy not only developed literacy skills, but also immersed herself in computer programming and created a number of Scratch projects. These findings point to the potential of using digital media, especially in early literacy development, as a way to create more opportunities. Integrating computing into the curriculum, while having affordances, requires teachers to consider their instructional practices. Box 7-1 illustrates the perspectives and strategies classroom teachers used when creating classroom environments that integrate computational thinking into elementary instruction.

Another dimension is the intersection between the perception of computing and the learners’ ongoing self-fashioning of identity—as an individual, in relation to various groups, and in terms of various abstract categories. With respect to perception, learners may have different ideas for what counts as a programming language, which in turn affects their perceived confidence to use those tools (Lewis et al., 2014). Alternatively, girls and more novice programmers may be drawn to using other tools, like Storytelling Alice, which is a program that enables users to program

animated stories. The storytelling component has been theorized to be more appealing to girls, while the visual programming aspects have been theorized to be more appealing to novices, because of the lack of syntax errors (Kelleher and Pausch, 2007). Thus, this program has been suggested as a means to reach middle school learners, particularly girls. For some learners, their perceptions of computing may call into question the authenticity of the tool—if they perceive themselves as “good at programming” but do not perceive the tool as professionally authentic, then they might perceive the tool as being less personally authentic. However, for others, a more personally authentic tool may serve as an entry point into developing interest and competency.

Furthermore, learners’ motivations for engaging with computing and their perceptions of computing have been shown to intersect with learner’s race/ethnicity. For example, DiSalvo and Bruckman (2010) examined the relationship between gaming practices and race and gender. This study was based upon the findings that (1) young Black and Hispanic men play video games more hours per day than White men and (2) gaming practices in computer science majors consisted of a desire to make games, understand the underlying mathematics, or hack/modify games. To understand the gaming practices in Black men, DiSalvo and Bruckman surveyed 13 learners. They found that although they play video games frequently, their motivation for playing was primarily social—to connect with family and friends and to practice for future social situations. This finding suggests that it may be important to build social components into design.

How Are Learners’ Background and Experience(s) Acknowledged?

As described above, learners vary with respect to their demographics and by extension with respect to their backgrounds and experiences. One dimension in which learners may differ is their experience with computing (e.g., whether learners prefer to engage in video game playing,¹ taking classes, watching videos online to learn more about specific computing concepts). Chapter 2 provides illustrative examples of learners and how their particular experiences shaped their interest and skills with respect to computing. This variability can even extend to whether or not the learner has caregivers or other siblings that are interested in computing; when learners have familial experiences, this can create a sense of confidence or belonging with the content (Margolis and Fisher, 2002). Knowing how

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¹ Playing video games have been suggested to “inspire and wonder,” and self-reports with computer scientists have indicated that video game playing sparked their interest in computing (DiSalvo and Bruckman, 2010, p. 56).

much and what type of exposure learners have when engaging in computing activities is key to ensuring appropriate design.

Moreover, all learners are shaped by the communities that they grow up in, which have their own cultural practices that have developed historically and are shaped in ongoing ways to achieve the goals and values of the communities (Moll, 2015; Nasir et al., 2006). Each community has particular ways of conceptualizing, representing, evaluating, and engaging with the world (Gutiérrez and Rogoff, 2003; NASEM, 2018b). A number of efforts, such as culturally-relevant and culturally-sustaining pedagogies, have been used to increase representation and combat cultural and systemic barriers to participation (see Chapter 2 for discussion). However, it is important to recognize that potential implicit biases may be built into the design of experiences; evaluating activities to determine whether they promote stereotypical representations is essential.

In the past two decades, a growing number of schools and other youth-serving organizations have either been founded (or, if pre-existing institutions, refocused) to create and deploy culturally-responsive, inclusive programming for particular minoritized communities within STEM and computer science. For instance, long-time national groups such as Girls Inc., The Hispanic Heritage Foundation, and the Girl Scouts of America have invested heavily in STEM and computing for their constituencies, sometimes partnering with other groups such as FIRST^® Robotics. The lack of culturally-relevant curricula, educator/mentor professional development, and program delivery models likewise spurred the launch of numerous new programs: Techbridge Girls (established 2000); Technovation Girls (2006); CompuGIRLS (2007); Black Girls Code (2011); RePublic Charter Schools, in Nashville, Tennessee and Jackson, Mississippi (2011); Girls Who Code (2012); All Star Code (2013); Bulldog Bytes at Mississippi State University (2013); America on Tech (2014); The Knowledge House (2014); Digital Pioneers Academy in Washington, DC (2018), to name just a few. Box 7-2 provides a discussion of how CompuGirls navigates the intertwined social processes. Acknowledging the cultural backgrounds and experiences of learners by taking the time to ask about and understand their conceptualizations of STEM and computing is essential, as this can allow for diversity in perspectives and broaden the range of personally meaningful experiences for design (Calabrese Barton et al., 2013; Krivet and Krajcik, 2008).

Designing an optimally effective STEM and/or computing curriculum thus entails gaining an understanding of the individual and collective identities in question, an iterative process whereby the learning goals, lesson plans, activities, etc. may in turn influence the learner’s sense of identity (Carlone and Johnson, 2007; Holmegaard, Madsen, and Ulriksen, 2014; Polman and Miller, 2010; Sfard and Prusak, 2005).

Community

Learning is a social process, supported in formal and informal ways by the people that a learner encounters over the course of various learning experiences. As introduced in Chapter 3, a growing body of literature suggests that learning is a matter of participation, engagement, and membership in a community of practice (Nasir and Cook, 2009; Wenger, 1998). Given these social processes at work, designers of authentic experiences for computing must understand not only who the actors are within an environment, but also the dynamics that influence the ways in which learning occurs (or does not occur) with others within a community. What follows is a discussion centered on how people in a community of learners support a learner: the role of facilitators/educators in supporting learning and the role of others within a community in supporting learning.

Facilitators/Educators and Their Roles

Social supports for learning as provided by facilitators are ubiquitous, occur in a variety of settings, and are present in all cultures (NRC, 2009). There are a number of different possible facilitators, including educators (e.g., teachers, librarians, museum professionals), mentors, caregivers, experts (e.g., scientists or engineers), hobbyists, other professionals (i.e., in industry or other settings), peers, and even oneself. Further, an experience can be primarily guided by the learner, there can be one facilitator/educator, or there can be many playing different roles within the environment. Regardless of how the facilitation is situated, key ingredients for effective learning are the availability of appropriate support to help learners engage in an activity in a meaningful way, the gradual withdrawal of these supports as the learners’ competence increases, and instruction and guidance in the use of tools that support learning (NRC, 2000).

Generally, facilitators and educators help orient learners to new learning experiences and prompt them to ask new questions and pursue new types of learning (Clegg and Kolodner, 2014; NRC, 2009, 2011b, 2012), enabling learners to more fully explore their curiosities and develop new and deepened interests. As learners become more comfortable and active in driving their own learning, facilitators/educators may also find themselves becoming learners, working together with the learners to co-create the learning experience (Clegg and Kolodner, 2014; NRC, 2009, 2011b, 2012). In this role, facilitators engage learners in conversations about their own interests, motivations, and day-to-day life experiences. Through these interactions, facilitators not only build personal rapport, but also help guide learners through the learning (Clegg and Kolodner, 2014; NRC, 2009, 2011b, 2012).

Whether in or out of school, facilitators must continuously seek specific ways to promote equity in their learning community and focus on repeatedly positioning learners in their contexts to take on engaged roles. Promoting equity involves, in part, paying attention to the culture of the environment in which learning is taking place. It also involves continuously watching out for patterns that favor one group over another (Barron et al., 2014). For example, in the Digital Youth Network, Barron et al. (2014) observed that more boys were engaging in STEM opportunities than girls. They continuously monitored for differential engagement and introduced new ways to engage girls in STEM activities. They observe that monitoring for engagement is not something that is just done once but that must be continuously observed and addressed throughout the life of a program (Barron et al., 2014). Promoting equity also requires welcoming non-traditional participation (as might be observed in video game play), specifically offering a variety of ways learners can contribute to the learning community (Gee, 2007).

Facilitation, whether in school or out of school, is a complex activity that depends centrally on a facilitator’s knowledge, skill, and judgment. Facilitators will flourish when they have opportunities to develop that knowledge, skill, and judgment—and to refine that expertise over time. Box 7-3 describes one model for supporting the evolving expertise of and community of support for PK–12 computer science teachers: the Computer Science Teachers Association.

Supporting Participants and their Role(s)

Facilitators need not be the “expert” or “adult” in the room. Other supporting participants, such as peers (including same-aged or older peers) and families, can play active roles in helping to facilitate the learning experience. A number of different programs have been developed to explicitly consider families and family learning as a central thread in their design. PowerMyLearning² and Technovation³ are two examples of programs that have family learning at the core of their approach. Engaging families can help to increase family members’ confidence in support of the learners’ learning.

At all levels, a learner’s understanding and skills can be improved when peers work together on challenging tasks, especially when the interaction is cooperative (Gauvain, 2001; Light and Littleton, 1999). These interactions may include tutoring, discussion, or joint problem-solving, with the latter offering different opportunities for learning because peers can define and structure a problem in a way that is mutually accessible (Ellis and Gauvain, 1992). Many youth-development programs that involve computing have some variant of peer facilitation (Kafai, Peppler, and Chapman, 2009; Martin, 2017; Schusler and Krasny, 2010).

Activities

This section turns from a discussion of who the learner and the other individuals involved in the learning are to focus on what the learner is doing, in what we have chosen to call Activities. That is, what are learners learning? And how are they learning? The process of learning—what learners are learning and how that learning is supported by educators, environment, tools, and community—is inextricably linked to the design of

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² For more information about PowerMyLearning’s approach and outcomes associated with families, see https://powermylearning.org.

³ Technovation is a “global tech education non-profit that inspires girls and families to be leaders and problem solvers in their lives and their community” (https://www.technovation.org/). Its family program is built around the use of AI tools as a family to solve problems of personal relevance.

an activity, as it determines how learners may engage, whether the content will stick, and what skills, competencies, and interest may develop from the activity or sequence of activities.

This section divides its discussion of learning and activities into two substantial topics—(1) content and pedagogy and (2) outcomes and assessment—and considers both topics in relation to authenticity, computing, and equity. Just as in other sections of this chapter, while the focus is on the design of activities and the ideas correlate with the guiding questions around activities, listed in Table 7-1, there is influence on and overlap with community, environment, and other design considerations.

Content and Pedagogy

The emphasis throughout this section is on what the learner will learn and do: the content of the activity—what it is that learners will be learning—is central to the design of the experience. But content does not exist in a vacuum. And thus, while it is certainly fundamentally important that the learning activity clearly addresses the subject matter or disciplinary content (or the integration of content areas, see Box 7-4), this content is inflected by other elements in the learning environment and design. One of these is the

intention that drives activity design. As discussed in the beginning sections of this chapter, articulating the why is a crucial step in designing effective programs. The why that guides design of the activity and pedagogical approach in authentic experiences for computing may apply not only to the subject matter, but also to social, educational, and affective aspects.

Activities are designed in alignment with one or multiple pedagogical frameworks or learning approaches. Even in instances when there may not be an active educator supporting the learner and activity, pedagogy is still taken into consideration.

Constructionism (Papert, 1980) is a theory of learning and an approach to learning design that encourages learning through personalizing, making, sharing, and reflecting (Brennan, 2015; Resnick, 2017). It centers learner agency and “powerful ideas”—an early commitment to advancing both personally authentic and professionally authentic (in terms of disciplinary authenticity) experiences, which have been linked to developing interest and competences (Bevan, 2017; Kafai and Burke, 2015). The history of K–12

computing education can be traced back to LOGO and this movement in constructionism. LOGO, for example, was not about computing as an end, but rather computing as a means; LOGO was designed to support learners’ explorations with mathematics, creative expression, and learning itself. In designing constructionist activities, the designer needs to consider ways that they can make the activities personally meaningful to their learners, and ways that the community plays an integral role in facilitating sharing of artifacts with peers. There is a significant amount of recent work looking at how to do this effectively with everything from e-textiles (Kafai and Fields, 2018) to physical computing (Blikstein, 2013b) to games (Kafai and Burke, 2015) and other forms of computing (Brennan, 2013; Papavlasopoulou, Giannakos, and Jaccheri, 2019).

Previous research has suggested that there may be benefits to engaging in project-based learning (Bevan, 2017; Erdogan et al., 2016; NASEM, 2018b). However, there are differences in how project-based learning is operationalized. Learners in programs such as CompuGirls (Box 7-2), DreamYard (Box 7-5), Digital Youth Divas (Box 7-5), the Clubhouse Network (Box 7-6), FIRST^®, and Providence Public Library’s Rhode Coders 2.0 (Box 4-5) are frequently engaged in learning activities and environments that mirror a project-based approach. Exploring Computer Science (ECS), a year-long introductory high school computer science course, readily integrates projects and inquiry into its curriculum units. Project Lead the Way (PLTW), which provides programs, curriculum, and professional development for classrooms across K–12, including PLTW Computer Science, centers its instruction on projects and problems. Beam Camp brings together more than 90 older elementary, middle, and high school campers to create one massive art project installed in the middle of the New Hampshire woods every summer, utilizing skills related to architecture, physical computing, ceramics, and welding, to name a few.

Throughout this report, the role of personal authenticity has been amplified. As suggested above (see Learners and Community), it is important that the facilitator of the activity takes time to understand learners’ perspectives and what knowledge, skills, and other ways of knowing they bring; that learners have agency over their own learning; and that there exist opportunities to apply and connect relevant everyday experiences (Gutiérrez and Rogoff, 2003; Nasir et al., 2006; Vossoughi, Hooper, and Escudé, 2016). Inclusive and culturally-relevant pedagogies offer insights into the approaches that can be successful in engaging learners from a wide range of diverse backgrounds and abilities (Gay, 2010; Ladson-Billings, 1995; Paris, 2012). In particular, these pedagogies speak to the importance of activities being personally authentic to the learner and bring to the surface the need for learners from marginalized and non-dominant communities to be seen as contributors and actors (Ladson-Billings, 2014).

Fostering personal authenticity also involves recognizing cultural and everyday practices as legitimate practices, whether related to mathematics, literature, or science (Nasir et al., 2006). Eglash et al. (2013) describe possible approaches of culturally responsive computing education, including ways to showcase, pay respect to, and link to the creativity, problem-solving, and computational thinking inherent (but rarely recognized in such ways) in practices such as Native American beadwork, Black cornrow hairstyles, and Latinx rhythms. By understanding and leveraging how members of diverse communities conceptualize and apply these concepts in their own ways—and by adopting pedagogical approaches to content that promote personally authentic experiences—the computing field can become more relevant and approachable for all communities and particularly those typically underrepresented (see Boxes 7-2 and 7-5).

Outcomes and Assessment

Aligned closely with the purposes and motivations of a design are the goals and outcomes we can expect from its implementation. The activity can be designed to develop skills associated with computing, or the design may emphasize the individual goals (e.g., development of interest and identity) or collective goals (e.g., equity and community health). Other constructs may also be highly relevant, and these need not be mutually exclusive. As stated above, goals of authentic experiences for computing may include outcomes that are societal, educational, and affective in nature (Brennan, in press), and all are relevant. Many of the examples shared in this report touch upon all three, often overlapping and interwoven.

That being said, it is essential to design ways in which educators and learners, or others in the learning environment and community, can obtain accurate and relevant measures of these goals. Previous reports (NRC, 2000) suggested that the design of learning environments be learner-, knowledge-, community-, and assessment-centered. Assessment offers opportunities for learners to iterate (i.e., evaluate whether they are learning intended content and skills and adjust their learning strategies as appropriate), for educators to provide feedback, and for both learners and educators to converse and share in growing and deepening understandings. Key to assessment is the need to be “congruent with one’s learning goals” (NRC, 2000, p. 140). In the design of a computing activity—and the associated design of the assessment—it is worthwhile to address questions about the claims and outcomes desired (NRC, 2001), and how might we collect evidence to support those claims.

Formative and summative assessments are commonly used across learning environments, but their use is inconsistent, and the focus is often on memorization, not understanding (NRC, 2000). When evaluating activities and learning environments that are collaborative, open-ended, occurring across different physical spaces and online platforms, and long in duration, which describe many of the pedagogies and examples used in authentic learning for computing, conventional assessment techniques can be harder to apply (Murai et al., 2019). Almost two decades ago it was recommended that more research be done into effective ways to conduct formative assessment, offering opportunities for feedback, self-assessment, and integration of technology (NRC, 2000). Today, resources, tools, and capacity for assessing learning remain widely variable.

Environment

The environment in which an authentic experience for computing takes place can facilitate or hinder many aspects of the intended design (as

described below), including equitable access, perceived authenticity, and learning outcomes. Environments may be wholly physical, wholly digital, or (as is increasingly the case) a blend or hybrid of the two—with the relationship between “space” and “place” and the connections across various environments important for the ways in which authentic and equitable interactions are designed and experienced. (The COVID-19 crisis, with its sudden, wholesale move to remote learning, has sharply foregrounded these elements). The physical environment might be a school, an after-school venue, a library, a museum, a botanical garden, a workplace, or a home. The digital environment might be a wholly online community (e.g., a learning management system used in a formal setting or an immersive game in an informal setting [of course the participant is logging on from some physical environment]) or it might be interwoven (via screen, joystick, headset, DJ mixer, robot, circuitry, e-textile, microcontroller, etc.) with the face-to-face interactions within the physical environment.

Design for environment(s) means attention to how control (of access, of resources, of standards) and agency are manifested: who creates the blueprints, who decides whether there shall be gates and locks (and, if so, who controls the keys?), who in effect owns the space and holds title to the place? Design for environment(s) also includes the intent for duration: is the environment meant to be fixed, sustained and continuous (e.g., a 10th-grade computer science classroom, a wet lab) or to be flexible, ephemeral and/or sporadic (e.g., a pop-up locale hosting a hackathon, a game jam, a robotics competition, a stitchfest or similar DIY maker event)? Is the environment intended as a stand-alone or as a connected part of a systemic whole? Is the environment purpose-built, or is it a space repurposed/retro-fitted to meet new design intentions?

Physical Spaces

Researchers from many disciplines⁴ have examined the ways in which the configuration and conceptualization of physical spaces work to invite, hinder, or facilitate interaction (Lupton, 2014; Nussbaumer, 2018). Substantial, if inconclusive, research exists specifically for the impact of the physical environment on formal K–12 and postsecondary education (Barrett et al., 2015; Cleveland and Fisher, 2014; Davies et al., 2013; O’Neil, 2010; Rands and Gensemer-Topf, 2017; Strong-Wilson and Ellis, 2007). Higgins et al. (2005) summarize that “[i]t is extremely difficult to come to firm conclusions about the impact of learning environments because of the multi-faceted nature of environments and the subsequent

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⁴ These disciplines include architecture, engineering, design, ergonomics, psychology, ethnography, and learning sciences.

diverse and disconnected nature of the research literature” (p. 6). The lack of definitive findings is even more pronounced with respect to informal environments, both because informal environments are much more varied and because there is far less research done on them compared to the formal environments. Having said that, the maker movement and various informal STEM and computer science initiatives have propelled much experimentation (Bennett and Monahan, 2013; Brahms and Werner, 2013; Dooley and Witthoft, 2012; Martinez and Stager, 2019; NRC, 2015; Peppler, Halverson, and Kafai, 2016; Stornaiulo and Nichols, 2018).

Effective designs of physical spaces also consider the needs and goals of the learning community members. Lighting, color schemes, acoustics, airflow, temperature, furniture and device design and configuration, hallway orientation, and the location and nature of common areas and storage space can foster planned collaboration and spontaneous informal learning among learners in the program or experience (Amedeo and Dyck, 2003; Yang, Becerik-Gerber, and Mino, 2013).

In recent decades, researchers have focused particularly on space/place-related issues relating to STEM and to computer science (Dasgupta, Magana, and Vieira, 2019; Denson et al., 2015) and even more recently on issues of access, inclusion, and equity (Beers and Summers, 2018; Holeton, 2020; Israel, 2019; Ladner and Israel, 2016; Mader and Lynch, 2020; Santo, Vogel, and Ching, 2019; Wilson and Randall, 2010). The equitable distribution of space and amenities, the age of facilities, equitable access to physical space and place (including consideration of regulations, such as the Americans with Disabilities Act, and popularized guidelines, such as Universal Design for Learning), and equitable access to required hardware and software, including physical network connectivity, bandwidth, download speeds and data storage capacities, all need to be considered. Adaptations to the environment may be needed if a learner has a physical disability so that they can continue to meaningfully engage with the content. For example, if the learner uses a wheelchair, then it may be necessary to adjust not only the table height, but also white boards around the room used for collaborative engagement (Center for Applied Special Technology, 2020).

Schools or Campus-Style Learning Environments

Inspired by heightened interest in STEM and computer science, and deliberately designing for equity, some schools and youth development programs have created holistic, large-scale, sometimes campus-style learning environments. These spaces are often co-created/funded by a consortium of public-sector, corporate, and non-profit actors, typically situated within the community being served and simultaneously adapting some

tech workplace practices to suit community-determined norms.⁵ Some examples include High Tech High in San Diego (launched 2000); The School of the Future in Philadelphia (2006); Digital Harbor Foundation in Baltimore (2011); Pathways In Technology Early College High School in Brooklyn (2011); Harlem Children’s Zone Promise Academy Charter School (2012); Digital NEST in Watsonville and Salinas, California (2014); The Knowledge House in the Bronx (2014); and the Brooklyn STEAM Center (2019). Some of these models were designed for replication and have begun to be replicated. Relatively little research is yet available on the efficacy of these various models in terms of their environmental design features.

Online Communities

Learners may engage with computing through gaming and online communities, which are individuals who come together and share “feelings of camaraderie, empathy and support” around a common interest (Preece and Maloney-Krichmar, 2005). It is important to distinguish between voluntary or open-call online communities (e.g., individuals playing Fortnite or creating and commenting on TikTok videos) and mandated or circumscribed communities (e.g., an online math class required to pass the ninth grade). Design considerations may differ for the two scenarios, and research on how best to design online environments for involuntary participants is not yet available—though a surge in such research is expected on remote learning triggered by the COVID-19 crisis.

Several environmental design dimensions are associated with the success of online communities. The first of these is, collectively, the purpose, rules, rhetoric, and graphic representations for the community (and who controls these), that is, the means by which the community creates the boundaries for its sense of “ambient belonging” (Cheryan et al., 2009) and the sense of “rightful presence” for its participants (Calabrese Barton and Tan, 2019). Just as in physical environments, participants may be attracted or repelled by elements of an online environment, with enormous implications for learning outcomes, authenticity, and equity (Ito et al., 2018).⁶ Flowing from and supporting the above are other elements, including whether or not the community is completely virtual or has a physical

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⁵ Their antecedents include the original Dewey-influenced Gary Plan schools launched in 1907, the “Schools of Tomorrow” movement in the 1960s, and the work of the Coalition of Essential Schools in the 1990s; they also overlap with the community schools approach more generally.

⁶ It should be recognized that widespread male harassment of women game creators and reviewers, in what became known as “GamerGate,” is a harsh and blatant example of the stakes involved (Barnes, 2018; Todd, 2015).

presence; the software environments that support the community (e.g., listservs, chat, blogs, wikis, apps and app creation, game design, authoring tools and play protocols, virtual reality design, video creation and use), including whether that environment is via traditional fixed computer or via a mobile device, or via some form of ubiquitous “Internet of Things” network; and the size and longevity of the community (Barbour, 2013; Bers, 2012; Corry and Stella, 2012; Gee, 2007; Harris-Packer and Ségol, 2015; Martinez-Garza, 2013; Pasnik, 2019; Preece and Maloney-Krichmar, 2005; Sobel, 2019; Statti and Villegas, 2020). As is true of all physical environments, the social experience in an online community is fundamental and dynamic, changing with who is present, the number of individuals present, and the nature of the interaction. And central to the continuation of such communities is knowing who the intended audience is.

Duration

How long a young person is engaged within an individual learning experience—and across an ecosystem of learning experiences—is another consideration of design. Duration includes the time in which a learner is engaged in a particular activity, as well as the frequency with which the learner engages in a particular learning experience. Both of these duration factors (i.e., total time and frequency) are important to consider in relation to the goals underlying the learning experience. For example, if the goal is to spark interest in a particular activity, a single, brief encounter may be sufficiently catalytic for a learner, inspiring them to continue with similar experiences or to identify resources to support further exploration (Barron, 2006; Chao et al., 2016). By contrast, if a program is designed to develop deep knowledge or greater fluency, more time and more frequent time within an experience and across an ecosystem of experiences may be needed (Barron, 2006).

Research suggests a relationship between time engaged in an activity and performance (Crowley et al., 2015; NRC, 2009; 2015); however, that does not mean that simply providing more time will lead to increased learning. The amount of time devoted to an activity needs to be developmentally and contextually appropriate. It is worth considering whether the appropriate frequency is a one-time event, weekly (or multiple times per week), or over a more extended time period, such as multiple classes; this will, of course, depend on the goal(s) of learning (e.g., to develop deeper expertise). Whether a learning experience is in the service of personal authenticity or professional authenticity, authenticity in learning necessitates time. Inquiry processes take time (Edelson, Gordin, and Pea, 1999; Kapur and Bielaczyc, 2012); likewise, personally-meaningful creative activities take time (Sternberg and Lubart, 1991).

But total time and frequency present challenges when designing both within and beyond the school setting. Highly structured learning environments such as K–12 classrooms typically enjoy the benefit of participants who are required to be present; classroom teachers, unlike museum educators or librarians, do not have to worry about learners opting out of a learning experience. That said, computing experiences are typically not included as part of core curricular experiences, and so finding time for them presents a challenge as K–12 classroom teachers navigate numerous demands on instructional time and manage competing interests within an already-crowded curriculum. Another challenge in the school context is the compartmentalization of the school day. Many K–12 teachers in the United States operate within fixed and relatively brief class periods. These encounters make it difficult to engage in deep work; authentic learning for computing, whether personally or professionally authentic, does not flourish in settings where thinking and creating are continually disrupted and restarted (Mehta and Fine, 2019).

Out-of-school learning experiences are not immune to duration-related challenges (see Box 7-6). Unlike the requisite participation of the school setting, out-of-school experiences typically rely on voluntary participation from learners. But the lack of expectation of commitment can result in attrition, either completely or partially, leading to discontinuity in the learning experience and undermining the time required to foster learning in authentic experiences. As discussed in Chapter 5, it is important to note, also, that there are inherent inequities in access to out-of-school learning opportunities, due to cost, accessibility of locations, or varying personal or family responsibilities.

Tools

Authentic experiences for computing often call on learners to engage in activities that involve the use of tools or manipulation of objects (physical or digital). In particular, authentic experiences that cultivate interest and competencies in computing are unsurprisingly dependent on interactions with the tools of computing. Tools are not neutral as they are designed with explicit and implicit intent (Costanza-Chock, 2020; DiGiano, Goldman, and Chorost, 2008; Svihla and Reeve, 2016); but they are both used in intended and unanticipated ways (de Certeau, 1984). This section will outline several key considerations related to tools and platforms for computing—factors that influence the design of tools with which young people are learning computing and worth considering by designers when selecting tools to support learners.

Learning how to program is a common entry point into computing. Although there are numerous programming languages and platforms ex-

plicitly designed for professional use, starting novices with professionally-authentic tools has been shown to be discouraging and alienating to young people having their first experiences with computing (Kelleher and Pausch, 2005). Several decades of design research have focused on how to design programming languages and computing environments that are developmentally appropriate and appealing to young, novice learners.

One framework (du Boulay, O’Shea, and Monk, 1981) for thinking about how to make programming more accessible to novices introduces the ideas of “simplicity and visibility” as central principles for design. Simplicity means a small number of commands, and visibility means providing insights into how the machine works. Others have commented on this framework to note it still needs to be “easy to use” (Mendelsohn, Green, and Brna, 1990), which has led to the development of “easy to use” graphical programming languages, from the early days of Boxer (diSessa and Abelson, 1986) and AgentSheets (Repenning, 1991), to data flow languages like Prograph (Cox, Giles, and Pietrzykowski, 1989).

Resnick and Silverman (2005) describe the kind of intended environment as one with “low floors, high ceilings, and wide walls.” The image of low floors represents a commitment to simplicity, visibility, and ease of use—qualities that are especially important when designing tools for novices. High ceilings represent the ability to create programs that are programmatically sophisticated or complex. The image of wide walls captures the importance of being able to create many different types of things, complexity notwithstanding; a language or tool enables a learner to produce different types of programs, not just a narrow focus on one genre of creative product. Box 7-7 describes Scratch, a programming environment for novices whose designers explicitly engaged the aspirations of low floors, high ceilings, and wide walls.

Some tool designers may encounter constraints that cause them to choose to sacrifice wide walls (despite how they might support the vision); this may be true for particular genres of creations or particular disciplinary commitments. As an example of constraining genres of projects, the Scratch programming environment opted to support programming 2D worlds, while the Alice programming environment opted to support programming 3D worlds. Both Scratch and Alice have been designed to make programming accessible to learners and teachers with little to no programming experience (i.e., the “low floor”) and computationally sophisticated programs can be created (i.e., the “high ceiling”), but they have each intentionally constrained what is easy to create (i.e., a learner who is passionate about 3D virtual worlds would ideally select a tool that supports that type of work).

Computing tools need not be constrained to a computer, and there is a long history of how tangible interfaces can be used to support introduction

to computing education (Bers, 2017; Horn and Bers, 2019; Kafai, Fields, and Searle, 2014; Resnick and Rosenbaum, 2013). Tangible interfaces, such as robotics kits (e.g., Mindstorms), interactive blocks (e.g., KIBO), and e-textiles (e.g., LilyPad Arduino; see Box 7-8), offer access to computing without the traditional computer (Buechley and Eisenberg, 2008; Buechley et al., 2008). Tangible interfaces have been used to both lower the floor and widen the walls of participation. For example, instead of snapping virtual programming blocks together, young children snap together physical programming blocks with the KIBO programming environment, a developmentally easier entry point for small children. E-textiles expand the range of creative production, widening (or maybe moving) the walls of creative participation, inviting young people and women who perhaps did not see the expressiveness of code until it was paired with more traditional crafting activities. An equity-related concern regarding tangible interfaces is their cost; robotics kits and tangible programming interfaces can be hundreds of dollars; even lower-cost e-textiles become cost-prohibitive when trying to serve large numbers of learners.

The intent and expressive capacity of a tool are important factors to consider when selecting a tool to include in the broader design of a learning experience. No one tool will be ideal for all learners or for every type of learning experience, so thinking about the vast array of tools as part of a larger ecosystem of learning is key. Transfer between different

tools for novices and then later from tools for novices to tools for professionals is possible. Researchers have studied transfer between languages through additional scaffolding (Shrestha, Barik, and Parnin, 2018), including moving from visual languages to textual languages (Weintrop and Wilensky, 2015).

Iteration

As stated in the opening section of this chapter, developing a clear and intentioned set of goals is an important early step in the process of program or experience design. To create alignment among the intended goals, reflection provides opportunities for designers to evaluate the alignment of the experience so that they can iterate until alignment is achieved. Moreover, understanding why previous efforts have faltered can greatly benefit the process of creating and implementing programs. There are countless initiatives to improve STEM learning and engagement, including computing. Many of these have met with some success and contributed greatly to the field. Others provide fodder for a number of important areas for consideration when designing programs around a specific intended goal. Table 7-2 highlights some particular goals of iteration and strategies to consider as part of reflection and the continuous improvement process.

Ultimately, the design of authentic experiences for computing yields the strongest results when it is conducted as an iterative, rather than linear, process. The design of a learning experience is not about the application of relevant principles and hoping they lead to the desired outcomes. Rather it

TABLE 7-2 Program Goals and Strategies for Iteration

is about using feedback to adjust course as things unfold, making changes to better achieve the activity’s goals. While designers hope for success, there are many ways that well-intentioned initiatives can fail. But it is really only failure if we do not learn anything from that experience. If instead, designers learn from each iteration of their implementation and adjust key components of the experience, either in small or large ways, there is continuous improvement.

SUMMARY

There are a number of important considerations to the design of any authentic experience for computing. The goal of this chapter was to provide guidance with respect to the design of authentic experiences for computing based on the available evidence. To that end, the chapter identified a number of important questions to ask and issues to consider during the design process. Having a clear and intentioned set of goals and attending to authenticity is critical in the design of authentic experiences for computing. Important considerations for design include attending to the social elements of the experience, such as who the intended learners are and the prior experiences they bring as well as who supports the learners and what experiences educators and facilitators need. Central to any authentic experience for computing is the activity—or what the learner is doing—as well as the ways in which the environment and duration of the activity can sufficiently engage learners. There is also a need for intentional consideration of the content and pedagogy, and of how best to assess the intended outcomes. Additional considerations include the connections in and out of the program to other learning opportunities. Just as important to the design is evaluating the program/experience to ensure alignment with the goals; as such, reflection is key.