Human learning is a complex, multidimensional phenomenon. In everyday use and in professional research and educational contexts, the word “learning” is used to capture a multiplicity of processes and outcomes, and language is rich with related terms that are associated with learning: knowledge, know-how, competence, understanding, skill, expertise, and proficiency. Understanding the nature of different varieties of learning, the processes that support them, and the ways in which they are expressed requires considering factors at multiple levels and scales. Science learning inherits all of the complexity of learning, while at the same time possessing a distinctive character in some respects.
The next few chapters explore what is known about science learning and how it is possible to apply this knowledge to citizen science. This will set the stage for some design strategies that can maximize learning in citizen science and preface a research agenda that explores how to continue supporting learning in citizen science. In this chapter, we offer some preliminary insight into why citizen science is a useful place to pursue science learning. We do this by first explaining why citizen science provides a useful venue for supporting learning, and we then describe potential outcomes of science learning in the context of citizen science using a framework developed by an earlier National Research Council report (2009). We conclude with a few notes on who is learning in citizen science, and how to approach supporting learning for all learners.
Citizen science provides a rich and varied array of contexts in which to consider science learning. As shown in Chapter 2, the field of citizen science is characterized by many different participants in various roles. Those participants and stakeholders enter into their participation with wide ranging goals, motivations, backgrounds, and interests. Because citizen science projects offer participants the opportunity to play a role in a scientific investigation, they offer particular opportunities for learning science. As the committee considered the unique constellations of potentials, constraints, and challenges that citizen science offers for science learning, several distinct characteristics emerged as elements of citizen science that are especially fertile opportunities for learning. In particular, the committee considered the common traits and variations in citizen science projects and types of participation in citizen science identified in Chapter 2, with an eye toward how those similarities and differences are mobilized to support science learning. Based on these descriptions, the committee was able to identify elements of citizen science that can be leveraged to support science learning, which we cluster into the following three categories:
- Scientific context. As investigations of natural phenomena, citizen science projects provide an entry point for learning about the science related to the phenomena under investigation, for learning to engage in the scientific practices involved in the investigation, and for learning about the nature of science.
- Nature of participation. As detailed in Chapter 2, the committee identified a number of variations in how participants can take part in citizen science, ranging from the duration of participation to the mode of project participation (online or in person, etc.) to the kind of role a participant might assume. As participants make decisions about the nature of their participation, the kind of learning that is possible through their citizen science experience is apt to change.
- Project infrastructure. Citizen science projects are supported by technological and social infrastructures. These infrastructures can be used to support learning.
In the following section, the committee describes how these elements of citizen science can be leveraged to support science learning.
As with all scientific efforts, every citizen science project exists in a scientific context, which can be defined in terms of the phenomenon under study and the reason that it is a focus of study. For example, the scientific context for the Monarch Larva Monitoring Project is “to better understand the distribution and abundance of breeding monarchs and to use that knowledge to inform and inspire monarch conservation” (Monarch Larva Monitoring Project, 2018). There are three ways that the scientific context of a citizen science project can support science learning:
- Authentic scientific endeavor. By definition, citizen science projects are authentic scientific endeavors, meaning that they are ongoing investigations of a scientific phenomenon conducted for a purpose. Authenticity can serve as a motivator for participation, which provides an opportunity to learn. That citizen science is an authentic endeavor provides the additional opportunity to engage in scientific practices and to learn about the nature of science.
- Real-world context. Most citizen science projects are investigations of phenomena in the natural or built environment that play out at observable scales, that is, they are investigations that play out in “real-world contexts.” Taking place in a real-world context provides the opportunity to motivate learning based on relevance (Boullion and Gomez, 2001).
- Data-driven. Citizen science opportunities generally engage participants in the collection or processing of data. The focus on data in citizen science projects creates the opportunity to learn about the role of data in scientific inquiry (nature of science) and the opportunity to learn to conduct data analysis (a scientific practice).
The participation of members of the public in a scientific investigation is the essential characteristic of citizen science. As described in Chapter 2, participation in citizen science can take many forms. In considering that variation, the committee noted three specific aspects of participation that present potential opportunities for learning.
- Interest- or concern-driven participation. Participation in citizen science projects is often voluntary.1 Research has shown that most citizen science participants are motivated by interest in the topic of the project or concern about the implications of the project (Geoghegan et al., 2016). Because interest- or concern-driven participation motivates learning about the context of the project, this interest or concern can be an opportunity for learning. The committee notes that the role of interest-driven participation is potentially complicated and/or enhanced when citizen science or practices in citizen science are used in a formal learning setting. For more on citizen science and formal learning, see Box 3-1.
- Social, communal activity. Citizen science projects exist in a communal context insofar as participation is conducted in relationship to a scientific goal shared by participants and project designers. Even in projects where participants do not have direct interaction with organizers or other participants, participants are generally aware that they are participating in a project alongside others with a shared purpose. The social and communal nature of citizen science projects can be an affordance for social, communal learning.
- Longer-term participation. While participation in some citizen science projects can be brief, many projects offer the opportunity for repeated activity over an extended period of time. For example, FrogWatch USA asks participants to make weekly observations of frog calls over a 6-month period, and many participants continue for multiple years (Association of Zoos & Aquariums, 2018). A longer duration of involvement creates the opportunity to develop deeper understanding and more sophisticated skills. Additionally, it creates the opportunity for learning through repetition and reinforcement. Our analysis, however, suggests that a minority of project participants engage in an extended way, which means that most people participating in citizen science cannot take advantage of learning opportunities afforded by repeated exposure.
What makes a citizen science project possible is its infrastructure. When committee members reviewed citizen science projects for this report,
1 The committee notes that the term “voluntary,” though intended to signify that participants elect to engage of their own volition, is necessarily contingent on an individual’s or community’s access to participate in a given project. Issues of access and how they may be mitigated through intentional project design are taken up in Chapter 7 of this report.
we noted two infrastructures distinctive to citizen science that specifically support learning.
- Social infrastructure. The social infrastructure includes the people who organize the project, provide direction to participants, and are available to assist them. The social infrastructure also includes the network of participants engaged with and learning from one another, either in person or virtually. The social infrastructure for a project can provide support for learning by developing educational resources or by facilitating learning directly.
- Technology infrastructure. The technology infrastructure includes the computing and communication technologies that enable participants to learn about and fulfill their roles in the project, as well as the specialized equipment that contributes to scientific investigations such as telescopes and DNA sequencing technology. The technology infrastructure can support learning by providing access to educational resources and specialized equipment, database platforms that house, maintain, and disseminate data, or by providing the communications platform that enables participants to learn from each other and other individuals that make up the social infrastructure of the project.
As articulated above, the characteristics of citizen science outlined here create particular and special opportunities for learning. The committee discusses how these opportunities may be identified and utilized in the design of citizen science projects in Chapter 6, with an eye toward how they might be leveraged to support specific learning goals.
To understand what people learn, the committee turned to the National Research Council’s 2009 report on Learning Science in Informal Environments: People, Places, and Pursuits (hereafter referred to as LSIE). That report synthesized multiple bodies of evidence to propose a framework of six complementary strands of science learning, conceived as intertwined strands of a rope. Four of the strands had been previously developed to capture aspects of science learning in K–8 school settings (National Research Council, 2007); two additional strands (Strands 1 and 6 in Box 3-2) were added to capture some of the distinctive aspects of learning in informal environments (i.e., settings outside of school such as museums, clubs, or nature centers), which typically reflect a greater emphasis on personal interest, growth, and free-choice engagement, often over extended periods of time and across different phases of participants’ lifespans. Many settings for citizen science projects can be naturally characterized as informal or nonformal, and, as described below, the kinds of learning outcomes possible in citizen science projects align with one or more of the six strands of informal science learning.
Strand 1: Sparking Excitement and Interest. Learners experience excitement, interest, and motivation to learn about phenomena in the natural, physical, constructed, and social worlds.
This strand captures the affective component of learning, including the sense of fun and curiosity that citizen science can engender,
- Strand 2: Understanding Scientific Content and Knowledge. Learners come to generate, understand, remember, and use concepts, explanations, arguments, models, and facts related to science (including both technical content and broader social, political, and cultural contexts of science).
and the way that scientists get excited by the ability to answer a question. It also encompasses the social motivations that may drive or be driven by citizen science, such as desires for cleaner environments or more diverse ecosystems. There is evidence that citizen science can produce excitement, interest, and motivation (Everett and Geoghegan, 2016; Frensley et al., 2017; Geoghegan et al., 2016; Rotman et al., 2012), thus we can conclude that this kind of learning takes place. This kind of learning is also aligned with goal- and interest-driven learning, in which a learner needs to know something to accomplish a goal or because one enjoys learning more about something one is interested in. An additional effect of this strand of learning is that when participants are motivated and excited, this engagement improves recruitment and retention, leading to higher quality scientific data (Gollan et al., 2012; Shirk et al., 2012).
This strand includes the traditional “disciplinary knowledge” associated with a citizen science project such as knowledge about project-relevant science content. This knowledge includes knowledge that learners acquire through their participation and the new or cutting-edge knowledge that professional scientists will acquire through the project, such as novel data that are collected by participants. Disciplinary knowledge may also include an enhanced understanding of the interaction of science and society, such as the political contexts, needs, and potential actions that result from a community engaging in environmental issues. This type of learning is further discussed by the National Academies of Sciences, Engineering, and Medicine report on science literacy (2016), and people across all levels of technical expertise can learn about these issues. The various participant groups within a project (nonscientists, scientists and researchers, community activists) bring different preexisting knowledge to the table, and thus both contribute and receive different content.
Strand 3: Engaging in Scientific Reasoning. Learners manipulate, test, explore, predict, question, observe, and make sense of the natural, physical, constructed, and social worlds.
This strand includes learning traditional scientific methods, which in the context of citizen science may include well-established research methods that are learned by participants, as well as cutting-edge research methods that are collectively developed through cooperative efforts of all groups, including professional scientists. As scientists learn to use the citizen science “method” for conducting their own research, they also learn how novel methods can improve data, analysis, the formulation of questions, etc.
Citizen science offers a venue where people who are not training to be scientists—whether school students or adults—gain access to learning how to think in scientifically sophisticated ways. The evidence here is mixed; many studies show that participants learn only specific methods or tools, and do not engage in the full panoply of scientific methods and reasoning (Phillips et al., in review).
Strand 4: Reflecting on Science. Learners reflect on science as a way of knowing: on processes, concepts, and institutions of science; and on their own process of learning about phenomena.
This strand captures the need for learners to improve their
understanding of the nature of the scientific enterprise. As LSIE explains, “The outcomes targeted in this strand address issues related to how scientific knowledge is constructed, and how people, including the learner herself, come to know about natural phenomena and how the learner’s ideas change” (National Research Council, 2009, p. 68). In order to achieve these outcomes, the learner needs to understand that people are responsible for making sense of theories and evidence and that, as a result, science changes as understandings of the relationships between theory and evidence evolve with the construction of new knowledge.
In the context of citizen science, this may include considering one’s own identity as a participant (whether as expert or as new researcher) and understanding the value and rewards to self from the activity. Through whatever role a person plays within a project, they may come to understand how collaboration among many different kinds of people leads to new knowledge. Participants may also reflect on the social, political, and cultural contexts of the activity. Participants may also come to recognize the broader implications, applications, and meaning of a project, both through their activities, as well as through the new knowledge generated, and ultimately wonder, “Where do I/we go from here?” This strand is particularly important for identifying learning about the social context of science, including issues of history and social power that affect learning, the multiple ways of understanding what counts as reliable knowledge, and the ways that communities learn and use learning to advance their priorities.
Strand 5: Engaging in Scientific Practices. Learners participate in scientific activities and learning practices with others, using scientific language and tools, and engaging in collective activities.
This strand captures the need for learners to participate “in normative scientific practices akin to those that take place in and govern scientific work” (National Research Council, 2009, p. 70). Mastery in this area includes recognition of the hallmarks of scientific culture and the ability to participate in its codes and mores, specifically in regard to scientific argumentation.
Within citizen science, learning outcomes from this strand may include learning specific skills associated with a project or activity, such as political or organizational skills in collective or community projects. For scientists, a few things that may be learned through practice include project leadership and management, communication skills, reporting and review of data, as well as project design and implementation.
Strand 6: Identifying as a science learner. Learners think about themselves as science learners—that is, as ones who CAN learn science—and develop an identity as someone who knows about, uses, and sometimes contributes to science.
This strand captures the change in identity that can occur when people recognize that they are capable of learning in science. This shift or change in identity is accompanied by increased feelings of self-efficacy and agency in relation to science. Taken together, the issues of identity, self-efficacy, and agency do not necessarily indicate that people develop identities as scientists, but rather they come to the understanding that they can learn and contribute to the process by which reliable scientific knowledge is produced. For some participants, an identification with science preceded their participation in citizen science, and this part of their identity may have motivated their engagement with citizen science (Phillips et al., in review).
The strands helped the committee address the challenging task of organizing potential learning outcomes for citizen science and linking them to important knowledge about how people learn science. Each strand describes and organizes a whole range of outcomes of science learning, for a variety or learners, in a variety of contexts including cultural contexts. In light of the many opportunities for learning potentially supported through citizen science, the committee was able to use the strands to better consider how participation in citizen science can maximize specific learning outcomes.
As the committee broached the subject of supporting learning in citizen science, it became clear that it was first important to introduce a few considerations about learners in citizen science: that is, who is it that is doing the learning in citizen science, and what do we need to know about the learner in order to begin to support learning outcomes. In Chapter 4, we summarize the committee’s approach to understanding learning in order to provide a theoretical foundation for the committee’s discussion of learning processes and outcomes. In advance of that discussion, we offer perspective on how our understanding of the learners themselves informs our later discussion of supporting learning in citizen science.
Many research literatures and theoretical perspectives, including developmental, social, organizational, and cultural psychology; cognitive science, neuroscience, and the learning sciences; and education, have contributed to nuanced and comprehensive frameworks for understanding and facilitating learning in individuals. Citizen science has, in large part, remained close to that research tradition and, as we will discuss in Chapters 4 and 5, much of the existing research on learning in citizen science focuses on individual learners and their learning outcomes. Given the nature of citizen science projects and activities, however, the committee also observed that “the learner” in citizen science may, in fact, be broader than individual participants. In 2016, the National Academies’ report on science literacy demonstrated a different perspective on learning by highlighting an emerging idea in the literature on learning in science: community science literacy (National Academies of Sciences, Engineering, and Medicine, 2016).
Community literacy is more than the sum of knowledge held by individuals in the community. Rather, community literacy is distributed among many individuals, but comes together through established networks of trust, behavior, relationships, power, and mechanisms of sharing. As the 2016 report documented, community (or communal) science literacy is ubiquitous: for example, it can occur in families (Borun, Chambers, and Cleghorn, 1996; Borun et al., 1997), in groups facing health crises (Epstein, 1996), or in communities addressing issues of toxic wastes or water quality (Brown, 1992; Brown and Mikkelsen, 1990; Fagin, 2013; Lee and Roth, 2003c; Ottinger, 2010a, 2010b; Ottinger and Cohen, 2011; Roth and Calabrese Barton, 2004; Roth and Lee, 2004). Community science literacy is particularly evident in the understandings of science held by marginalized communities, such as suspicion of the health care system in the African American community, based on historical and contemporary patterns evident in the Tuskegee syphilis study and in the contamination of water in Flint, Michigan (Armstrong et al., 2007; Benjamin, 2014; Dula, 1994; George, Duran, and Norris, 2014; Markowitz and Rosner, 2016; Thomas and Quinn, 1991). As described in Ann Fadiman’s book, The Spirit Catches You and You Fall Down (2012), the Hmong community demonstrates a set of beliefs about health and healthcare that conflict with the American medical system; the conflict is not between the knowledge of individuals, but between different community understandings of what constitutes and creates health. Other researchers have found community-level differences in knowledge, reasoning, and practice between fisherpeople and hunters from different cultural communities, primarily Native American and European
An important aspect of community science literacy is that it highlights an issue that the committee will discuss in Chapter 4: Learning science means more than learning the content of specific topical domains. It also covers learning the processes of science (both idealized and in practice) and the epistemological bases of science (including the implications of different epistemological stances) and the ability to act on science. Learning theorists have provided several ways of thinking about the learning process that address community learning (Bela et al., 2016), described in Box 3-3.
Given these expanding conceptions of who is learning, the committee wishes to highlight that communities also have the potential to learn in citizen science, though research in this area is nascent. We will return to these ideas later in this report in Chapter 5, where we look at examples of learning in citizen science, and in Chapter 6 of this report, where we offer some thoughts on how to design citizen science in support of community science literacy.
As noted in Chapter 1 of this report, the committee believes that in order to address this study’s statement of task, it is critical that we consider how people of all backgrounds can learn through citizen science. In order to truly address these questions, the committee feels that it is first necessary to understand who learners in citizen science are: that is, what backgrounds and experiences do they bring to their encounters with citizen science that undergird what and how they will learn. In this section, we unpack the importance of honoring the prior knowledge and experiences that learners (individual learners and community learners) bring into their participation in citizen science by treating these backgrounds as assets that support learning.
In the past decade, research that devotes scholarly attention to the learning processes of nondominant communities and learners has illuminated the tendency for educational interventions to assume that people, and especially people from historically underrepresented communities in science, have minimal relevant prior knowledge (Bang et al., 2012). This research shows that these interventions fail to provide opportunities for learners to connect new learning to prior experiences. Even the choice of what content to learn is often constrained by applying a deficit model that presumes that learners do not have the ability to chart their own learning goals. Research has demonstrated that the assumption of a “deficit” on the part of some individuals and communities is invalid and that people the world over have experiences and exposure to phenomena that can be taken up in scientific study (National Research Council, 2012).
As the committee will describe in Chapters 4 and 5, the processes of learning are always situated within the context of what learners already know and understand. It is easy to think that learners enter projects with a deficit and project activities fill that deficit. But adopting this perspective can undermine other sources of knowledge and other ways of knowing, alienate learners, and impede learning: ultimately, this perspective fails to recognize that learners enter projects with a variety of relevant prior knowledge and experience, some of it cultural, and that engaging that knowledge and experience actually empowers learners in the ways described above. Alternatively, learning environments that work to connect those experiences to the focal phenomena of new learning have demonstrated increased learning, retention, and sustained interest for learners (Moll and Gonzalez, 2004). Further, creating environments in which learners are positioned to see their own experiences and knowledge as resources has also been associated with increased persistence (Brossard, Lewenstein, and Bonney, 2009).
In our review of research on science learning specifically, the committee noted that the scholarly community is moving toward understanding science learning in ways that are attuned to learners’ prior knowledge and their many ways of knowing. This has led to a shift away from deficit models toward a more refined understanding of alternative conceptions and epistemologies and their role in supporting science learning, referred to as an asset-based approach to supporting learning. In order to support learning, asset-based approaches seek to connect and query disciplinary (science) knowledge with and against a broader store of knowledge, and leverage that knowledge in ways that advance scientific disciplines.
In thinking about learning in the context of citizen science, the committee stresses the importance of adopting an asset-based perspective in regard to participants’ prior knowledge and experience. We return to this idea in Chapter 5, where we attempt to highlight examples of how this asset-based approach is supporting specific learning outcomes in citizen science, as well as in Chapter 6, where we discuss how to design for learning in citizen science.
In summary, this chapter seeks to set the stage for our in-depth conversations about science learning in citizen science. By identifying what it is about citizen science that makes it a desirable vehicle for supporting learning, we lay a foundation for our later discussions about how citizen science can be leveraged in support of specific learning outcomes. Also, by calling out the strands of learning and their associated learning outcomes, we set the stage for what kinds of learning outcomes are possible; we discuss these processes of learning in greater depth in Chapter 4. Finally, by exploring
who is learning—whether an individual or community—and considering the knowledge and experience that learners bring with them into citizen science, we prepare for subsequent analysis and recommendations that leverage sociocultural conceptions of learning.
Armstrong, K., Ravenell, K.L., McMurphy, S., and Putt, M. (2007). Racial/ethnic differences in physician distrust in the United States. American Journal of Public Health, 97(7), 1283-1289.
Association of Zoos & Aquariums. (2018). Welcome to FrogWatch USA. Available: http://frogwatch.fieldscope.org [September 2018].
Atran, S., and Medin, D.L. (2008). The Native Mind and the Cultural Construction of Nature. Cambridge, MA: MIT Press.
Bang, M., Warren, B., Rosebery, A.S., and Medin, D. (2012). Desettling expectations in science education. Human Development, 55(5-6), 302-318.
Bela, G., Peltola, T., Young, J.C., Balázs, B., Arpin, I., Pataki, G., and Bonn, A. (2016). Learning and the transformative potential of citizen science. Conservation Biology, 30(5), 990-999. doi:10.1111/cobi.12762.
Benjamin, M.M. (2014). Water Chemistry. Long Grove, IL: Waveland Press.
Borun, M., Chambers, M., and Cleghorn, A. (1996). Families are learning in science museums. Curator: The Museum Journal, 39(2), 123-138.
Borun, M., Chambers, M.B., Dritsas, J., and Johnson, J.I. (1997). Enhancing family learning through exhibits. Curator: The Museum Journal, 40(4), 279-295.
Boullion, L., and Gomez, L. (2001). Connecting school and community partnerships as contextual scaffolds. Journal of Research in Science Teaching, 38(8), 899-917.
Brossard, D., Lewenstein, B., and Bonney, R. (2005). Scientific knowledge and attitude change: The impact of a citizen science project. International Journal of Science Education, 27(9), 1099-1121.
Brown, P. (1992). Popular epidemiology and toxic waste contamination: Lay and professional ways of knowing. Journal of Health and Social Behavior, 267-281.
Brown, P., and Mikkelsen, E.J. (1990). No Safe Place: Toxic Waste, Leukemia, and Community Action. Berkeley: University of California Press.
Dula, A. (1994). African American suspicion of the healthcare system is justified: What do we do about it? Cambridge Quarterly of Healthcare Ethics, 3(3), 347-357.
Epstein, S. (1996). Impure Science: AIDS, Activism, and the Politics of Knowledge. Berkeley: University of California Press.
Everett, G., and Geoghegan, H. (2016). Initiating and continuing participation in citizen science for natural history. BMC Ecology, 16(1), 13.
Fadiman, A. (2012). The Spirit Catches You and You Fall Down: A Hmong Child, Her American Doctors, and the Collision of Two Cultures. New York: Farrar, Straus and Giroux.
Fagin, D. (2013). Toms River: A Story of Science and Salvation. New York: Bantam Books.
Frensley, T., Crall, A., Stern, M., Jordan, R., Gray, S., Prysby, M., Newman, G., Crall, A.C. Hmelo-Silver, and Huang, J. (2017). Bridging the benefits of online and community supported citizen science: A case study on motivation and retention with conservation-oriented volunteers. Citizen Science: Theory and Practice, 2(1), 4, 1-14.
Fu, W. (2016). From distributed cognition to collective intelligence: Supporting cognitive search to facilitate online massive collaboration. In U. Cress, J. Moskaliuk, and H. Jeong (Eds.), Mass Collaboration and Education (pp. 125-140). New York: Springer.
Geoghegan, H., Dyke, A., Pateman, R., West, S., and Everett, G. (2016). Understanding motivations for citizen science. In Final report on behalf of UKEOF. University of Reading, Stockholm Environment Institute (University of York) and University of the West of England.
George, S., Duran, N., and Norris, K. (2014). A systematic review of barriers and facilitators to minority research participation among African Americans, Latinos, Asian Americans, and Pacific Islanders. American Journal of Public Health, 104(2), e16-e31.
Gollan, J., de Bruyn, L.L., Reid, N., and Wilkie, L. (2012). Can volunteers collect data that are comparable to professional scientists? A study of variables used in monitoring the outcomes of ecosystem rehabilitation. Environmental Management, 50, 969-978.
Gunawardena, C.N., Hermans, M.B., Sanchez, D., Richmond, C., Bohley, M., and Tuttle, R. (2009). A theoretical framework for building online communities of practice with social networking tools. Educational Media International, 46(1), 3-16. doi:10.1080/09523980802588626.
Hutchins, E. (1995). Cognition in the Wild. Cambridge, MA: MIT Press.
Jackson, M., and Moreland, R.L. (2009). Transactive memory in the classroom. Small Group Research, 40(5), 508-534.
Lave, J., and Wenger, E. (1991). Situated Learning: Legitimate Peripheral Participation. Cambridge, England: Cambridge University Press.
Lee, S., and Roth, W.M. (2003). Science and the “good citizen”: Community-based scientific literacy. Science, Technology, and Human Values, 28(3), 403-424.
Lewis, K., and Herndon, B. (2011). Transactive memory systems: Current issues and future research directions. Organization Science, 22(5), 1254-1265.
Markowitz, G., and Rosner, D. (2002). Deceit and Denial: The Deadly Politics of Industrial Pollution. Berkeley: University of California Press.
Medin, D.L., and Atran, S. (2004). The native mind: Biological categorization and reasoning in development and across cultures. Psychological Review, 111(4), 960.
Moll, L.C., and González, N. (2004). Engaging life: A funds-of-knowledge approach to multicultural education. Handbook of Research on Multicultural Education, 2, 699-715.
Monarch Larva Monitoring Project. (2018). About the Monarch Larva Monitoring Project. Available: https://monarchlab.org/mlmp/about-us/ [September 2018].
National Academies of Sciences, Engineering, and Medicine. (2016). Science Literacy: Concepts, Contexts, and Consequences. Washington, DC: The National Academies Press.
National Research Council. (2007). Taking Science to School. Washington, DC: The National Academies Press.
National Research Council. (2009). Learning Science in Informal Environments: People, Places, and Pursuits. Washington, DC: The National Academies Press.
National Research Council. (2012). A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas. Washington, DC: The National Academies Press.
Ottinger, G. (2010a). Constructing empowerment through interpretations of environmental surveillance data. Surveillance and Society, 8(2), 221-234.
Ottinger, G. (2010b). Buckets of resistance: Standards and the effectiveness of citizen science. Science, Technology, and Human Values, 35(2), 244-270.
Ottinger, G., and Cohen, B.R. (Eds.). (2011). Technoscience and Environmental Justice: Expert Cultures in a Grassroots Movement. Cambridge, MA: MIT Press.
Phillips, T.B., Ballard, H., Lewenstein, B.V., and Bonney, R. (In review). Examining engagement in science through citizen science: Moving beyond data collection. Science Education.
Roth, W.M., and Calabrese Barton, A. (2004). Rethinking Scientific Literacy. New York: RoutledgeFalmer.
Roth, W.M., and Lee, S. (2004). Science education as/for participation in the community. Science Education, 88(2), 263-291.
Rotman, D., Preece, J., Hammock, J., Procita, K., Hansen, D., Parr, C., Lewis, D., and Jacobs, D. (2012, February). Dynamic changes in motivation in collaborative citizen-science projects. In Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work (pp. 217-226). New York: Association for Computing Machinery.
Salomon, G. (Ed.). (1997). Distributed Cognitions: Psychological and Educational Considerations. Cambridge, England: Cambridge University Press.
Shirk, J.L., Ballard, H.L., Wilderman, C.C., Phillips, T., Wiggins, A., Jordan, R., McCallie, E., Minarchek, M., Lewenstein, B.V., Krasny, M.E., and Bonney, R. (2012). Public participation in scientific research: A framework for deliberate design. Ecology and Society, 17(2).
Tallapragada, M. (2016). Activists, Learning, and Relating to the Controversial Technology of Hydraulic Fracturing. (Doctoral dissertation.) Cornell University, Ithaca, NY.
Thomas, S.B., and Quinn, S.C. (1991). The Tuskegee Syphilis Study, 1932 to 1972: Implications for HIV education and AIDS risk education programs in the black community. American Journal of Public Health, 81(11), 1498-1505.
Wegner, D.M., Giuliano, T., and Hertel, P.T. (1985). Cognitive interdependence in close relationships. In W. J. Ickes (Ed.), Compatible and Incompatible Relationships (pp. 253-276). New York: Springer.
Weick, K.E., and Roberts, K.H. (1993). Collective mind in organizations: Heedful interrelating on flight decks. Administrative Science Quarterly, 357-381.
Yoo, Y., and Kanawattanachai, P. (2001). Developments of transactive memory systems and collective mind in virtual teams. The International Journal of Organizational Analysis, 9(2), 187-208.
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