Kindle notes

To understand whether, how, or when learning occurs, good outcome measures are necessary, yet efforts to define outcomes for science learning in informal settings have often been controversial. At times, researchers and practitioners have adopted the same tools and measures of achievement used in school settings. In some instances, public and private funding for informal education has even required such academic achievement measures. Yet traditional academic achievement outcomes are limited. Although they may facilitate coordination between informal environments and schools, they fail to reflect the defining characteristics of informal environments in three ways. Many academic achievement outcomes (1) do not encompass the range of capabilities that informal settings can promote; (2) violate critical assumptions about these settings, such as their focus on leisure-based or voluntary experiences and nonstandardized curriculum; and (3) are not designed for the breadth of participants, many of whom are not K-12 students. The challenge of developing clear and reasonable goals for learning science in informal environments is compounded by the real or perceived encroachment of a school agenda on such settings. This has led some to eschew formalized outcomes altogether and to embrace learner-defined outcomes instead. The committee’s view is that it is unproductive to blindly adopt either purely academic goals or purely subjective learning goals. Instead, the committee prefers a third course that combines a variety of specialized science learning goals used in research and practice. (loc: 197-208)

Strands of Science Learning We propose a “strands of science learning” framework that articulates science-specific capabilities supported by informal environments. It builds on the framework developed for K-8 science learning in Taking Science to School (National Research Council, 2007). That four-strand framework Learning Science in Informal Environments aligns tightly with our Strands 2 through 5. We have added two additional strands—Strands 1 and 6—which are of special value in informal learning environments. The six strands illustrate how schools and informal environments can pursue complementary goals and serve as a conceptual tool for organizing and assessing science learning. The six interrelated aspects of science learning covered by the strands reflect the field’s commitment to participation—in fact, they describe what participants do cognitively, socially, developmentally, and emotionally in these settings. Learners in informal environments: Strand 1: Experience excitement, interest, and motivation to learn about phenomena in the natural and physical world. Strand 2: Come to generate, understand, remember, and use concepts, explanations, arguments, models, and facts related to science. Strand 3: Manipulate, test, explore, predict, question, observe, and make sense of the natural and physical world. Strand 4: Reflect on science as a way of knowing; on processes, concepts, and institutions of science; and on their own process of learning about phenomena. Strand 5: Participate in scientific activities and learning practices with others, using scientific language and tools. Strand 6: Think about themselves as science learners and develop an identity as someone who knows about, uses, and sometimes contributes to science. (loc: 208-20)

• prompt and support participants to interpret their learning experiences in light of relevant prior knowledge, experiences, and interests (loc: 255-56)

Experiences in informal environments for science learning are typically characterized as learner-motivated, guided by learner interests, voluntary, personal, ongoing, contextually relevant, collaborative, nonlinear, and openended (Griffin, 1998; Falk and Dierking, 2000). (loc: 274-76)

• Visitors to whyville.net, a large social networking site on the Internet targeted at teenagers, find their chat sessions interrupted by the unexpected appearance of the word “Achoo!” Over a few days, the virus spreads through the community. Using resources from the Centers for Disease Control and Prevention made available on the site, visitors learn to identify how the virus spreads and how to prevent further infection (Neulight, Kafai, Kao, Foley, and Galas, 2007). (loc: 285-88)

The early roots of America’s education system developed in the late 18th century when informal learning institutions, such as libraries, churches, and museums, were seen as the main institutions concerned with public education. They were viewed as places that encouraged exploration, dialogue, and conversation among the public (Conn, 1998). The American Lyceum movement, which began in the 1820s, supported the growing movement of public education in the United States (Ray, 2005). Lyceums, modeled after the early Greek halls of learning, brought the public together with experts in science and philosophy for lectures, debates, and scientific experiments. In the late 1800s, the Chautauqua movement, a successor to the Lyceum movement, grew out of the social and geographic isolation of America’s farming and ranching communities. Chautauquas, a type of educational family summer camp, brought notable lecturers and entertainers of the day to rural communities, where there was a strong hunger for both entertainment and education. These movements were driven by the notion that in a democratic nation, an educated populace is needed to inform public policy. They provided a conduit for bringing the science knowledge and practices of the day to an American public with limited access to information. At the same time, people often developed an intuitive sense of the natural world and scientific principles through activities like farming, gardening, and Introduction brewing alcohol—processes that were closely connected to daily life in an agrarian society. Beginning in the mid-19th century the world’s fairs or expositions brought people from around the world together to learn about developments in commerce, technology, science, and cultural affairs. World’s fairs have been the site for initial broad dissemination of scientific and technological developments, especially during the period of industrialization, when developments like telephone communication were unveiled to vast publics. Recently, individuals’ personal recollections of these events have been used as the basis for exploring what people attend to, learn, and recall from learning experiences in informal settings (e.g., Anderson, 2003; Anderson, Storksdieck, and Spock, 2007; Anderson and Shimizu, 2007). (loc: 334-49)

2005 – Informalscience (http://www.informalscience.org) is launched to share evaluation and research on informal science learning environments. (loc: 390-91)

Following this report, a separate book is planned for publication by the National Academies Press. Based on the conclusions and recommendations of this report, the book that follows will interpret the research base for a practitioner audience. More information on that book is available at http://www7.nationalacademies.org/bose/LSIEP_Homepage. html. (loc: 462-64)

Consequently, there are relevant literatures that this study does not consider or only touches on. They include adult workforce learning, the classroom as a site for informal learning, and media-based health interventions (e.g., in public health campaigns and international development). (loc: 499-501)

Informal learning institutions typically operate without the authority to compel participation, (loc: 509-10)

For all these pursuits, the range of learning outcomes far exceeds the typical academic emphasis on conceptual knowledge. Across informal settings, learners may develop awareness, interest, motivation, social competencies, and practices. They may develop incremental knowledge, habits of mind, and identities that set them on a trajectory to learn more. (loc: 577-80)

The idea of lifelong, life-wide, and life-deep learning has been influential in efforts to develop a broad notion of learning, incorporating how people learn over the life course, across social settings, and in relation to prevailing cultural influences (Banks et al., 2007). (loc: 584-86)

Lifelong learning is a familiar notion. It refers to the acquisition of fundamental competencies and attitudes and a facility with effectively using information over the life course, recognizing that developmental needs and interests vary at different life stages. Generally, learners prefer to seek out information and acquire ways of doing things because they are motivated to do so by their interests, needs, curiosity, pleasure, and sense that they have talents that align with certain kinds of tasks and challenges. Life-wide learning refers to the learning that takes place as people routinely circulate across a range of social settings and activities—classrooms, after-school programs, informal educational institutions, online venues, homes, and other community locales. Learning derives, in both opportunistic and patterned ways, from this breadth of human experience and the related supports and occasions for learning that are available to an individual or group. Learners need to learn how to navigate the different underlying assumptions and goals associated with education and development across the settings and pursuits they encounter. Life-deep learning refers to beliefs, ideologies, and values associated with living life and participating in the cultural workings of both communities and the broader society. Such learning reflects the moral, ethical, religious, and social values that guide what people believe, how they act, and how they judge themselves and others. This focus on life-deep learning emphasizes how learning is never a culture-free endeavor. (loc: 586-97)

Identifying common ground between learners’ practices and practices in the domains of interest may be a productive route to experiences that move learners toward deeper understanding and capability in the domain. For example, individuals learn to reason in science by crafting and using forms of notation or inscription that help represent the natural world. Crafting these forms of inscription can be viewed as being situated within a particular (and even peculiar) form of practice—creating representations and models—into which students need to be initiated. (loc: 645-48)

Our proposal is consonant with other calls for using an ecological perspective for accounts of human development and learning that can accommodate a range of disciplinary perspectives as well as the diversity of life experiences in a global society (Barron, 2006; Lee, 2008). It builds on a tradition of scholarship on the ecological nature of human development. This tradition has long recognized and taken into account the compound set of influences on learning and development originating from a person’s experiences across myriad institutional contexts and social niches (family, school, playground, peers, neighbors, media, etc.) (Bronfenbrenner, 1977). (loc: 659-63)

• The Contextual Model of Learning (Falk and Dierking, 2000) is a general framework for understanding informal or free-choice learning (see also Falk and Storksdieck, 2005, for an application and quantitative validation of the model). The model focuses on 12 key personal, sociocultural, and physical dimensions of learning. The model stresses visitor agenda, personal motivation, the sociocultural nature of learning, the importance of physical context, and long-term outcomes. • The Multiple Identities Framework, grounded in situated cognition, explores factors associated with deciding what kind of person one wants to be or fears becoming and engaging in activities that make one part of the communities associated with a particular identity. It has been used to examine women negotiating the worlds of science and engineering, as well as race and gender in workplace settings (Tate and Linn, 2005; Packard, 2003). • Third Spaces is a theoretical construct that lends itself to nonschool learning (e.g., Gutiérrez, 2008; Eisenhart and Edwards, 2004). Third spaces are outside the two typical spheres of existence: home and work or home and school for children. For telecommuters, for example, a coffee shop where they spend the work day could be construed as a third space. Third spaces are places where participants’ everyday and technical (or scientific) language and experiences intersect and can be the site for fascinating accounts of informal learning. • Situated/Enacted Identity (Falk, 2006; Rounds, 2006) focuses on audience expectation and audience agenda in terms of true, underlying interests that are intimately linked to the audience’s enacted identity during a visit or free-choice learning experience. This framework is based on a large body of literature that considers the entry narrative of the visitor as a key factor in understanding motivation and learning from an informal learning experience. • Family learning, though not a theoretical framework per se, has been an important way of reframing informal learning experiences, changing the focus from any single individual in a learning group, such as the child, to the entire Theoretical Perspectives family (Bell, Bricker, Lee, Reeve, and Zimmerman, 2006; Ellenbogen, Luke, and Dierking, 2004; Astor-Jack, Whaley, Dierking, Perry, and Garibay, 2007; Ash, 2003; Crowley and Galco, 2001; Ellenbogen, 2002, 2003; Borun et al., 1998). In this context, learning is defined as “a joint collaborative effort within an intergenerational group of children and significant adults.” Outcomes include learning science concepts, attitudes, and behaviors and also learning about one another and the members of the group, as well as shaping and reinforcing individual and group identity. Family learning approaches are grounded in sociocultural theories and are currently transforming the way some museums and science centers are reorienting their missions, educational strategies, and experiences. Other perspectives have been used to inform evaluation studies of learning in informal environments. • Community of Practice (see Lave and Wenger, 1991) is a framework used to guide development and assessment of community-based efforts and professional development projects. This framework offers insight into participants’ trajectories from science novices (peripheral members of the science community) to more active and core members, engaging in authentic science and sometimes even participating in apprentice-like activities with scientists, engineers, and technicians. • Positive Youth Development and Possible Selves frameworks have been used primarily in assessing youth programs (Koke and Dierking, 2007; Luke, Stein, Kessler, and Dierking, 2007). They are grounded in sociocultural theory and address the broader developmental needs of youth, in contrast to traditional deficit-based models that focus solely on youth problems, such as substance abuse, conduct disorders, delinquent and antisocial behavior, academic failure, and teenage pregnancy. Positive Youth Development describes six characteristics of positively developing young people that successful youth programs foster: cognitive and behavioral competence, confidence, positive social connections, character, caring (or compassion) and contribution, to self, family, community, and ultimately, civil society. Possible Selves (Stake and Mares, 2005) proposes that individuals’ perceptions of their current and imagined future opportunities serve as a motivator and organizer for their current task-related thoughts, attitudes, and behaviors, thus “linking current specific plans and actions to future desired goals.” Learning Science in Informal Environments cultures. Using each as a lens to examine learning environments enables us to tease out various factors at play in the learning process and better identify potential leverage points for improving learning. People-Centered Lens This lens sheds light on the intrapsychological phenomena that are relevant to the purposes and outcomes of science learning in informal environments including: the development of interests and motives, knowledge, affective responses, and identity. Some of the relevant principles for the people-centered frame are encapsulated in How People Learn (National Research Council, 1999). These principles include the influence of prior knowledge on learning, how experts differ from novices, and the importance of metacognition. Other principles highlight the learning benefits of having experiences that provide one with a positive affect and that help identify personal interests, motives, and identities that can be pursued. (loc: 668-706)

Accordingly, efforts to teach should not merely be about abstractions derived in knowledge systems like science, but should also focus on helping learners become aware of and express their own ideas, giving them new information and models that can build on or challenge their intuitive ideas. (loc: 711-13)

Experts in a particular domain are people who have deep, richly interconnected ideas about the world. They are not just good thinkers or really smart. Nor are novices poor thinkers or not smart. Rather, experts have knowledge in a specific domain—be it chess, waiting tables, chemistry, or tennis—and are not generalists. Their ability to identify problems and generate solutions is closely connected to the things that they know, much more so than once believed (National Research Council, 2007). At the same time, expertise is not just a “bunch of facts”; the knowledge of experts resides in organized, differentiated constructs with which the expert works and applies fluidly. Research has documented how expertise development can begin in childhood through informal interaction with family members, media sources, and unique educational experiences (Crowley and Jacobs, 2002; Reeve and Bell, in press). One way that experts work with their knowledge is through metacognition or monitoring their own thinking. Much of this work is done in the head Theoretical Perspectives and is not naturally accessible to others, although researchers have found it useful to ask knowledgeable people to talk aloud about their thinking while they engage in tasks. Metacognition, like expertise, is domain-specific. That is, a particular metacognitive strategy that works in a particular activity (e.g., predicting outcomes, taking notes) may not work in others. However, metacognition is not exclusive to experts; it can be supported and taught. Thus, even for young children and older novices engaged in a new domain or topic of interest, metacognition can be an important means of controlling their own learning (National Research Council, 1999). Accordingly, as a means of controlling learning, metacognition may have special salience in informal settings, in which learning is self-paced and frequently not facilitated by an expert teacher or (loc: 713-26)

One example of a framework that could be considered people-centered was developed by George Hein (1998). It allows for classification of museum-based and similar learning experiences along dimensions of the thinking they support or promote for participants. Hein’s framework can be represented in a diagram depicting two orthogonal lines on a plane (see Figure 2-2). One plane represents the theory of knowledge (epistemology) embodied in an exhibit or museum. This ranges from realism (the world exists independently of human knowledge about it) to idealism (knowledge of the world exists only in minds and doesn’t imply anything about the world “out there”). The second plane represents a theory of learning, which moves from a transmission model to a constructed model. This reflects a range from behaviorist commitments (e.g., knowledge is transmitted) to the variability in cognitive perspectives with respect to the extent to which knowledge is learner-constructed. Hein’s simple diagram can be used to classify the pedagogical approach (loc: 735-42)

This turning away from studying internalized mental learning outcomes to analyzing social practice is evident in the science studies literature as well—in accounts of sophisticated scientific activities that emerge or develop as a result of particular arrangements of resources in specific places like labs or field sites (Latour and Woolgar, 1986; Rouse, 1999). In this view, the material and technological objects, including visual representations of data and technological tools, constitute the foundational resources through which people individually and collectively engage in learning activities. Hutchins summarizes the role of artifacts in distributed cognition as follows: “The properties of groups of minds in interaction with each other, or the properties of the interaction between individual minds and artifacts in the world, are frequently at the heart of intelligent human performance” (Hutchins, 1995, p. 62). The ubiquity of human interaction with artifacts in the shaping of learning and thought has been documented for many decades in ecological research focused on understanding human activity in physical settings (Gibson, 1986; Shaw, Turvey, and Mace, 1982). A group of visitors on a museum floor makes sense of exhibits through forms of talk and physical activities that are fundamentally shaped by the nature of the material and technological objects they encounter in those places (Heath, Luff, von Lehn, Hindmarsh, and Cleverly, 2002). Scientists and other professionals conduct their measurements and engage in practical “intelligent routines” in concert with the features of the specific material objects and representations with which they work (Latour, 1995; Pea, 1993; Scribner, 1984; Traweek, 1988). Archaeologists conducting fieldwork, for example, go through sophisticated sequences of interaction and gesturing around the physical objects of their inquiry to develop their theoretical inferences about past cultures and local settings (Goodwin, 1994). Children working as street vendors know how to perform sophisticated arithmetic operations in conjunction with the specific currencies and retail products (Saxe, 1988; Nunes, Schlieman, and Carraher, 8 Learning Science in Informal Environments 1993). The instrumental use of artifacts in the course of mediating everyday cognition and learning is pervasive. (loc: 762-78)

there is a shift in focus from the individual learner in isolation to culturally variable participation structures, such as apprenticeship learning and legitimate peripheral participation, the process through which individuals move from simpler tasks at the periphery of group activity to higher level and more central positions of responsibility and expertise as they learn new capabilities (Rogoff, 1990, 2003; Lave and Wenger, 1991). (loc: 853-56)

We are interested in a broad array of settings that can capture lifelong, life-wide, and life-deep learning. We organize our discussion of environments across three venues or configurations for learning: everyday informal environments, designed environments, and out-of-school and adult programs. (loc: 956-58)

Although what makes a learning environment informal is the subject of much debate, informal environments are generally defined as including learner choice, low consequence assessment, and structures that build on the learners’ motivations, culture, and competence. (loc: 959-61)

1 The educational research community generally makes a distinction between assessment— the set of approaches and techniques used to determine what individuals learn from a given instructional program—and evaluation—the set of approaches and techniques used to make judgments about a given instructional program, approach, or treatment, improve its effectiveness, and inform decisions about its development. Assessment targets what learners have or have not learned, whereas evaluation targets the quality of the intervention. (loc: 1108-12)

the “authentic assessment” approaches taken by some school-based researchers, employing various types of performances, portfolios, and embedded assessments (National Research Council, 2000, 2001). (loc: 1166-68)

Yet, as a body of work, assessment of learning in informal settings draws on the full breadth of educational and social scientific methods, using questionnaires, structured and semistructured interviews, focus groups, participant observation, journaling, think-aloud techniques, visual documentation, and video and audio recordings to gather data. (loc: 1169-72)

Researchers have also used self-report techniques to investigate whether prior levels of interest were related to learning about conservation (Falk and Adelman, 2003; Taylor, 1994). Falk and Adelman (2003), for example, showed significant differences in knowledge, understanding, and attitudes for subgroups of participants based on their prior levels of knowledge and attitudes. Researchers replicated this approach with successful results in a subsequent study at Disney’s Animal Kingdom (Dierking et al., 2004). (loc: 1216-19)

An important method for assessing scientific knowledge and understanding in informal environments is the analysis of participants’ conversations. Researchers interested in everyday and after-school settings study sciencerelated discourse and behavior as it occurs in the course of ordinary, ongoing activity (Bell, Bricker, Lee, Reeve, and Zimmerman, 2006; Callanan, Shrager, and Moore, 1995; Sandoval, 2005). Researchers focused on museums and other designed environments have used a variety of schemes to classify these conversations into categories that show that people are doing cognitive work and engaging in sense-making. The categories used in these classification schemes have included: identify, describe, interpret/apply (Borun, Chambers, and Cleghorn, 1996); list, personal synthesis, analysis, synthesis, explanation (Leinhardt and Knutson, 2004); perceptual, conceptual, affective, connecting, strategic (Allen, 2002); and levels of metacognition (Anderson and Nashon, Learning Science in Informal Environments 2007). Most of these categorizations have some theoretical basis, but they are also partly emergent from the data. (loc: 1292-1300)

Several types of learning outcomes assessments used in museums and other designed spaces engage participants in activities that require them to demonstrate what they learned by producing a representation or artifact. Concept maps are often used to characterize an individual’s knowledge structure before and after a learning experience. They are particularly well suited to informal environments in that they allow for personalization of both prior knowledge and knowledge-building during the activity and are less threatening than other cognitive assessments. However, they require a longer time commitment than a traditional exit interview, are time-consuming to code, are difficult to administer and standardize, and may show a bias unless a control group has been used (see Appendix B). While a variety of concept mapping strategies have been used in these settings (Anderson, Lucas, Ginns, and Dierking, 2000; Gallenstein, 2005; Van Luven and Miller, 1993), perhaps the most commonly used in museum exhibitions is Personal Meaning Mapping (Falk, Moussouri, and Coulson, 1998), in which the dimensions of knowledge assessed are extent, breadth, depth, and mastery. Personal Meaning Mapping is typically presented to learners in paper format, although Thompson and Bonney (2007) created an online version to assess the impact of a citizen science project. (loc: 1322-31)

When learners are participating in an extended program (e.g., docents or watchers of a TV series), it may be feasible to conduct pre- and posttests of conceptual learning, similar to those used in schools, to test their learning of formal concepts. For example, Rockman Et Al (1996) used a series of multiple-choice questions to show that children who watched Bill Nye the Science Guy made significant gains in understanding that Bernoulli’s principle explains how airplanes fly. Another means by which researchers have assessed learning over extended time frames is by asking participants to write reflections in a journal, possibly to discuss with others and to share with researchers. Leinhardt, Tittle, and Knuston (2002) used this method to showcase the deep connections and knowledge-building done by frequent museum-goers. (loc: 1348-54)

This strand of outcomes is almost always assessed by examining the participant’s learning process rather than a pre-post measure of outcome. This is because the only way to do a pre-post measurement requires that learners demonstrate what they are able to do in the “pre” condition. Pretesting requires that learners be put on the spot in a manner that is inconsistent with the leisure-oriented and learner-centered nature of most informal environments. Instead, skills are usually assessed as they are practiced, and the assumption is made that practicing a skill leads to greater expertise over time. Research focused on assessing practical and discursive inquiry skills in informal environments often rely on video and audio recordings made during activities that are later analyzed for evidence of such skills as questioning, interpreting, inferring, explaining, arguing, and applying ideas, methods, or conjectures to new situations (see Appendix B for a discussion of video- and audiotaping). For example, Humphrey and Gutwill (2005), analyzing the kinds of questions visitors asked each other and the ways they answered them, found that visitors using “active prolonged engagement” exhibits asked more questions that focused on using or understanding the exhibits than visitors using the more traditional planned discovery exhibits. Randol (2005), assessing visitors’ use of scientific inquiry skills at a range of interactive exhibits, found that the inquiry could be characterized equally well by holistic measures or small-scale behavioral indicators (such as “draws a conclusion”) as long as the sophistication of the behaviors was measured rather than their number. Meisner et al. (2007) and vom Lehn, Heath, and Hindmarsh (2001, 2002) studied short fragments of video to reveal the ways in which exhibits enable particular forms of coparticipation, modeling, and interactions with strangers. Researchers have used video analysis to investigate a large range of behaviors related to how learners make sense of the natural and physical world, including interacting appropriately with materials and showing others how to do something. Stevens and colleagues (Stevens, 2007; Stevens and Hall, 1997; Stevens and Toro-Martell, 2003) used a video annotation system on the museum floor to prompt visitors to reflect on how they and others interacted with an interactive science display, leaving a durable video trace of their activity and reflections for others to explore and discuss as they come to the display. The traces then serve as data for subsequent interactional analysis of learning. Researchers have also asked learners after participation in science learn8 Learning Science in Informal Environments ing activities to provide self-reports of their own (or each other’s) skill levels. (loc: 1365-84)

While short-term participation in well-defined programs is relatively easy to assess, long-term and cumulative progressions are much more challenging to document, due primarily to the difficulties of tracking learners across time, space, and range of activity. Nevertheless, researchers must accept this challenge, because a key assumption in the field (e.g., Crowley and Jacobs, 2002) is that effective lifelong learning is a cumulative process that incorporates a huge variety of media and settings (everyday life in the home, television, Internet, libraries, museum programs, school courses, after-school programs, etc.). Thus, longitudinal studies are particularly useful. (loc: 1450-54)

These assumptions regarding outcomes align with three high-level criteria that the evidence suggests are essential in the development of assessments appropriate for science learning in informal environments. First, the assessments must address not only cognitive outcomes, but also the range of intellectual, attitudinal, behavioral, social, and participatory capabilities that informal environments effectively promote (Jolly, Campbell, and Perlman, 2004; Hein, 1998; Schauble et al., 1995; Csikszentmihalyi and Hermanson, 1995). Second, assessments should fit with the kind of participant experiences that make these environments attractive and engaging; that is, any assessment activities undertaken in informal settings should not undermine the features that make for effective learning there (Allen, 2002; Martin, 2004). Third, the assessments used must be valid, measuring what they purport to be measuring—that is, outcomes from those science learning experiences (National Research Council, 2001). (loc: 1578-85)

To a significant extent, the ability to answer these questions depends on how well the research community is able to describe the nature of participants’ experience in particular types of informal learning environments, with an eye to eventually understanding what is consistent and systematic across these environments. An in-depth understanding of key features of the environments (e.g., what are the physical and social resources? What are the norms of behavior?), ways in which learning is framed or organized (e.g., what activities are presumed to lead to learning? How is learning supported? What does it mean to be knowledgeable in this setting?), and the capacities being built (e.g., what skills, knowledge, or concepts are learners engaging with?) can lead to critical insights regarding the particular contributions of informal experiences to science learning, therefore highlighting the outcomes one would most expect and want to see. (loc: 1595-1601)

Indeed, one conclusion from the literature is that adult learners tend not to be generalists in their learning of science; rather, they tend to become experts in one particular domain of interest (Sachatello-Sawyer, 2006). (loc: 2019-20)

Epstein (1996) documented the process by which AIDS activists, initially relatively naïve about technical aspects of AIDS research, became sufficiently expert in the science of AIDS to contribute meaningfully to research policy, research funding, and research design. Epstein’s work is part of a qualitative, case studyoriented sociological tradition that highlights ways in which nonexperts can learn technical information when relevant to their needs and indeed may contribute to the production of knowledge in ways that are unavailable to traditional scientific experts. This focus on lay knowledge comes largely from British explorations of the public understanding of science in the 1980s and 1990s (Irwin and Wynne, 1996; Layton, 1993). (loc: 2091-96)

Based on a number of studies, they propose a four-phase model of interest development: (1) triggered situational interest, typically sparked by such environmental features as incongruous/surprising information or personal relevance; (2) maintained situational interest, sustained through the meaningfulness of tasks and personal involvement; (3) emerging individual interest; and (4) well-developed individual interest, in which the individual chooses to engage in an extended pursuit using systematic approaches to questioning and seeking answers. (loc: 2646-49)

More recently, research on motivation for learning has emphasized a broader set of constructs in “goal-orientation theory,” which includes needs, values, and situated meaning-making processes (reviewed by Kaplan and Maehr, 2007). However, this theory has yet to be applied to informal environments. (loc: 2720-22)

Meaning-making (i.e., interpreting experiences to give them personal significance) has become so central to descriptions of learning in informal environments that it is sometimes regarded as the essential learning behavior (e.g., Silverman, 1995; Hein, 1998; Ansbacher, 1999; Rounds, 1999). (loc: 2857-59)

What these programs have in common is an organizational goal to achieve curricular ends—a goal that distinguishes them from everyday learning activities and learning in designed environments. Science learning programs (loc: 3493-95)

are typically led by a professional educator or facilitator, and, rather than being episodic and self-organized, they tend to extend for a period of weeks or months and serve a prescribed population of learners. Ideally, the programs are informal in design—they are learner driven, identifying and building on the interests and motivations of the participant, and use assessment in constructive, formative ways to give learners useful, valued information. Yet as programs that retain much of the structure identified with schools—a curriculum that unfolds over time, facilitators or teachers, a consistent group of participants—and yet that occur in nonschool hours, they have a natural tension. Nowhere is this tension more evident than in discussions of after Learning Science in Informal Environments school programs in which establishing learning goals, outcome measures, and accountability processes can be especially contentious (see Box 6-1). (loc: 3495-3501)

Out-of-school-time programs have existed for some time, first appearing at the end of the 19th century.1Throughout the years, they have changed and adapted to serve different purposes, needs, and concerns, including providing a safe environment, academic enrichment, socialization, acculturation, problem remediation, and play (Halpern, 2002). (loc: 3508-11)

A project funded by the National Science Foundation (NSF) designed to enhance the ability of citizen science projects to achieve success had identified, by November 2007, more than 50 published scientific articles based on citizen science data, along with other articles assessing the data quality, educational processes, and impact of citizen science projects (http://www.citizenscience.org). (loc: 3812-14)

The number and scale of citizen science programs is increasing (Cohen, 1997; http://pathfinderscience.net/; http://www.citizenscience.org). The effects of these projects on participants’ knowledge and attitudes toward science have rarely been documented (Brossard, Lewenstein, and Bonney, 2005), although efforts to increase assessment are actively in progress (http://www.citizenscience.org). (loc: 3822-24)

culture is “the constellations of practices historically developed and dynamically shaped by communities in order to accomplish the purposes they value” (Nasir et al., 2006). (loc: 4202-4)