trust in citizen science research: a case study of the groundwater education through water...

TRUST IN CITIZEN SCIENCE RESEARCH: A CASE STUDY OF THE GROUNDWATEREDUCATION THROUGH WATER EVALUATION & TESTING PROGRAM1

Teresa Thornton and Jessica Leahy2

ABSTRACT: Data collected by citizen scientists, including K-12 students, have been validated by the scientificcommunity through quality assurance ⁄ quality control tests and publication of results in peer-reviewed journalarticles. However, if citizen science data are to be used by local communities, research is needed to determinewhich factors contribute to local community member trust in citizen science data, and how to increase the bene-fits and use of citizen science programs. This article describes the Groundwater Education Through Water Eval-uation & Testing (GET WET!) program that employs middle and high school students, state and localgovernment employees, environmental nongovernmental organization leaders, business representatives, collegefaculty and students, and other volunteers as citizen scientists to create a database of groundwater quality foruse as a baseline for local water resources management. Data were gathered through semi-structured interviewspre- and post-involvement from 40 participants in this citizen science program conducted in five states in thenortheastern United States. Results indicate that factors of trust are largely based on interpersonal trust andfamiliarity. We conclude with recommendations and future research that may improve local community memberwillingness to trust citizen science data generated by students.

(KEY TERMS: trust; citizen science; k-12 students; drinking water.)

Thornton, Teresa and Jessica Leahy, 2012. Trust in Citizen Science Research: A Case Study of the GroundwaterEducation Through Water Evaluation & Testing Program. Journal of the American Water Resources Association(JAWRA) 1-9. DOI: 10.1111 ⁄ j.1752-1688.2012.00670.x

INTRODUCTION

Citizen scientists can be beneficial to local commu-nities that need large quantities of data in a shortperiod of time to use in decision making about waterresources management. For citizen science data to beuseful, however, it must be trusted as a valid andreliable source of data. Peer-reviewed journal articleshave validated that citizen science programs can gen-erate acceptable data (Parris, 1999; Peckenham et al.,

2009, 2012). Publications have also validated citizenscience data, including those generated by students,by comparing their results to those of professionals(Rock and Lauten, 1996; Lawless and Rock, 1998;Galloway et al., 2006; Peckenham et al., 2009). How-ever, applied social science research regarding trustin citizen science has not been thoroughly investi-gated.

Using citizen scientists to test private well waterand assess groundwater quality provides an excellentresearch opportunity. In New England, there are

1Paper No. JAWRA-11-0077-P of the Journal of the American Water Resources Association (JAWRA). Received July 12, 2011; acceptedApril 3, 2012. ª 2012 American Water Resources Association. Discussions are open until six months from print publication.

2Respectively, Graduate Research Assistant (Thornton) and Associate Professor (Leahy), School of Forest Resources, University of Maine,241 Nutting Hall, Orono, Maine 04469 (E-Mail ⁄ Leahy: [email protected]).

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more than 2.3 million homes that rely on privatewells as their drinking water source. Testing privatewell water is encouraged in New England by the U.S.Environmental Protection Agency. Rhode Island andConnecticut are the only two states in New Englandwhere private well testing is required upon the legaltransfer of property. Otherwise, the New Englandregion has no other private well water regulations orenforcement of suggested testing guidelines (USEPA,2008). This leaves little incentive for homeowners totest their wells and has resulted in areas of unknowndrinking water quality with potentially deadly con-taminants. Strategies for educating homeowners totest their private drinking water supply has led to aneed for community-based programs, such as citizenscience, to establish baselines of groundwater qualityand land use effects on water resources (Carr, 2004).

In this study, we investigate trust through a casestudy approach with the Groundwater EducationThrough Water Evaluation & Testing (GET WET!)citizen science program. GET WET! brings togetherstudents in grades 5-12 with community memberswho volunteer in the classroom assisting with datacollection and analysis. Nearly all the communitymember volunteers have some interest in the waterquality test results and include: state and local gov-ernment employees, environmental nongovernmentalorganization leaders, business representatives, collegefaculty and students, and other volunteers. Student-generated citizen science results are mapped,graphed, statistically analyzed, and presented to thecommunity. Results are also used as a baseline forlong-term monitoring.

Our goal was to explore trust relevant to commu-nity member volunteers’ confidence in the citizen sci-ence data so that ways of increasing the perceivedvalidity and reliability in the citizen science datacould be identified. Our specific research objectiveswere to: (1) explain factors that influence participanttrust in citizen science data generated by students;(2) describe community member volunteer percep-tions of community trust in citizen science data; and(3) identify community member volunteer perceptionsof a citizen science data collection effort.

Gaining trust has proven valuable in many naturalresource management contexts (Leach and Pelkey,2001; Davenport et al., 2007; Leahy and Anderson,2008). The role of trust is of particular interest towater resources managers, scientists, and communitymembers who want to improve their connections toeach other for the purposes of protecting, enhancing,and managing the environment (Gulati, 1995). Inves-tigating the role of trust will enable citizen scienceprogram leaders and others to understand whatdimensions of trust create positive assessments ofcitizen science data. This will allow future citizen

science program leaders, water resources managers,scientists, and community members to form success-ful groups in other locales or within collaborativegroups to work toward environmental managementactions. This research is also intended to furthertrust theory by focusing on trust in citizen sciencedata generated by students.

LITERATURE REVIEW

Within existing research, trust as a theoreticalconstruct has been difficult to define. Many social sci-ence disciplines define trust differently based on theaccepted approaches and concepts within their disci-plines (Bigley and Pearce, 1998; Rousseau et al.,1998; Kramer, 1999; Liljeblad, 2005). Trust consid-ered from a social-psychological perspective attributespositive characteristics to a person, an organization,or a group where the expectation of perceived risk isbased on the level of vulnerability a person has inany situation (Bigley and Pearce, 1998; Kramer,1999; Slovic, 1999; Dirks and Ferrin, 2001). Byextrapolation, trust can also be given to inanimateobjects, such as citizen science data. The implicationfor citizen science is that once trust is formed, thendata can be used by local communities to managetheir natural systems sustainably.

Interpersonal trust, or the trust between individu-als, has been described as an important factor intrust studies involving organizations and groups.This type of trust has been the primary focus of qual-itative studies involving resource-dependent commu-nities and federal land management agencies (Leachand Pelkey, 2001; Davenport et al., 2007; Leahy andAnderson, 2008) as well as the primary factor in thestudy of environmental alliances (Gulati, 1995).Davenport et al. (2007) performed a qualitative casestudy on trust and found that turnover of naturalresources agency staff decreased ‘‘face time’’ betweenthe community and the agency staff. They found thatrelationships formed through time spent togethercreated a trust that could sustain a successful collab-oration through potential discords in ideas. Theydetermined it was interpersonal trust that bondedlocal community members to agency staff. This wasalso determined in a comprehensive review of suc-cessful partnerships (Leach and Pelkey, 2001). Theseauthors found 16 different studies on successfulwatershed partnerships and concluded, ‘‘good inter-personal relationships and mutual trust are impor-tant’’ (Leach and Pelkey, 2001, p. 8).

Public trust in science is generally thought to bedeclining (Irwin, 1995). Forming collaborations

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between scientists and the public has been oneresponse to bolstering trust in science. Lewenstein(2003) also talked of the layperson-scientist informa-tion gap and says, ‘‘that activities designed toenhance trust among participants … are more impor-tant than specific educational or informationalapproaches’’ (p. 5). However, Lidskog (1996) felt thancollaboration was only effective if scientists are wilingto value laymen expertise. According to Lidskog(1996) and Ferretti (2007), familiarity with a govern-ing body, industry, or organization does affect trustof scientific data. Sztompka (2007) said that ulti-mately, ‘‘trust in science may be reduced to the trustin the actions of scholars, researchers, organizers ofscience, together making up the scientific community’’(p. 213). Glaeser et al. (2000) support the idea thatthe collaborative, face-to-face nature of citizen scienceprograms could foster interpersonal trust. If a com-munity member trusts the person sharing the scien-tific information, the applied social science researchsuggests they will also trust the data (Lidskog, 1996;Haerlin and Parr, 1999; Millstone and van Zwanen-berg, 2000; Friedman, 2002). It is possible thatthrough the use of citizen science programs, especiallythose that encourage significant social interactions,interpersonal trust in the ability of citizen scientists tocollect reliable and valid data could develop. Thisstudy will determine if interpersonal transactions,such as those in our case study citizen science pro-gram, will enable the citizen science data generated bystudents to be trusted.

In addition to the trust literature focused on natu-ral resources management and science, there is alsoa body of literature within the discipline of educationconcerning trust. Students in grades 4-12 have beenrecorded as effective researchers through the valida-tion of their results. Specifically, student scientistshave been shown to produce valid scientific results ifthe directions given to them are clear and the scien-tific goals are simple (Rock and Lauten, 1996; Beckeret al., 1998; Galloway et al., 2006). For both adultsand K-12 students, the acts of gathering data andcomprehending the context of a problem are betterunderstood than comprehending complex scientificconcepts (Roth and Lee, 2004; Brossard et al., 2005;Cohn, 2008). The past research has focused on objec-tive measures of citizen science data. The data maystill be perceived as high risk, not trusted, and notused in decision making as a result. Therefore, thisstudy of trust in citizen science data generated bystudents is an important contribution.

Trust is a function of risk perception and socialinteractions that generate familiarity. Risk percep-tion involves people’s evaluation of their vulnerability(Slovic, 1999). Risk perception operates through cul-tural and social contexts to influence how risk is

interpreted. Researchers have called for greater par-ticipation of citizens in science in order for partici-pants to better understand the risks and uncertaintyin collecting and interpreting scientific data (Beck,1994; Irwin, 1995; Lidskog, 1996; Slovic, 1999; Trum-bull et al., 1999; Silvertown, 2009). Participation in acitizen science program, where a diverse group of citi-zens collect, interpret, analyze, and report the find-ings, has the potential to reduce risk perceptionsrelated to trusting citizen science data generated bystudents.

Studies also tend to reinforce the notion that themore interactions that occur between parties, themore an individual is able to assess the motives,intentions, and risk of trusting another individual,organization, or group (Lidskog, 1996; Kramer, 1999;Millstone and van Zwanenberg, 2000). Manyresearchers have established that people evaluatetrust through familiarity, and that individual trust-ing relationships are formed through social transac-tions (Granovetter, 1973; Coleman, 1988; Gulati,1995; Bigley and Pearce, 1998; Glaeser et al., 2000;Wondolleck and Yaffee, 2000; Davenport et al., 2007).Unfamiliarity with citizen scientists can create vul-nerability, the perception of risk, and the potentialfor a lack of trust in the data resulting from thesekinds of programs. Although the willingness to trusthas been studied in collaborative groups (Leach andSabatier, 2005), a focus on citizen science programsthat generate water quality data is absent. As well, afocus on risk perception and familiarity as factorsinfluencing trust has not been fully explored.

CASE STUDY DESCRIPTION

Study sites were located in five states within NewEngland: Connecticut, Maine, New Hampshire,Rhode Island, and Vermont. The United States Geo-logic Survey offices in each state were referenced todetermine which communities had 70% or more ofhomes with private well water as the primary drink-ing water source. Middle and high schools in thoseareas where at least 60% of the student body usedprivate well water were identified and asked to par-ticipate in the GET WET! program. Teachers andcommunity member volunteers were contacted andrecruited via telephone and email.

The first step in GET WET! is a full day of trainingfor teachers and community member volunteerswhich includes: sampling and laboratory procedures,and training in computer applications such as GoogleEarth, Excel, and PowerPoint. Teachers were pro-vided a book containing geologic explanations of

TRUST IN CITIZEN SCIENCE RESEARCH: A CASE STUDY OF THE GROUNDWATER EDUCATION THROUGH WATER EVALUATION & TESTING PROGRAM


groundwater and how it is formed in their particulararea. The book also included hands-on activities, listsof vocabulary words, and lessons that apply to theparameters of each test performed in the classroomwith student well water samples. In the second stage,students were trained by GET WET! facilitators onhow to collect private well water samples. They thenused, with the support of community member volun-teers, HACH chemistry testing kits to measurenitrates, hardness, chloride, pH, conductivity, andiron. Ten percent of all samples were taken to a uni-versity lab for quality assurance and control. In thethird step, students entered the water quality infor-mation in Excel and Google Earth. In the fourth step,students prepared a PowerPoint presentation of sta-tistics and charts to graphically represent findings.Results were presented to the community membervolunteers, parents, and community leaders at apublic meeting. The final step involved uploadingthe data to a national web site created to manage acomprehensive database of all information citizenscientists generated through the GET WET! pro-gram (http://www.umaine.edu/waterresearch/outreach/getwet/index.htm).

RESEARCH METHODS

A qualitative case study approach was chosen forthis research into trust of citizen science data gener-ated by students. Qualitative research provides find-ings that are based on themes, patterns, andrelationships, and resulting case studies are context-specific. Theories, grounded in the specific situation,can be developed from the data collected (Dey, 1999).Specifically, a semi-structured interview format wasused in this study. The data collected are rich, in-depth, and unique to the individual. The interviewerattempted to collect information that shed light on theparticipants’ meanings, symbols, interpretations, andinteractions. Participatory action research, as a meth-odology, was a component of this case study because ofthe dual roles as researchers and extension specialistsheld by those involved in carrying out both theresearch and the GET WET! program (Creswell, 2007).

Qualitative semi-structured interviews were con-ducted prior to and after participation in GET WET!.Eight participants from the community member vol-unteers in each of the five study sites were selectedusing purposive sampling to identify those who inter-acted most with the citizen scientists (Creswell,2007). Data were collected using a semi-structuredinterview format with a standard set of questions forall participants (Table 1). Follow-up questions and

other probes varied depending on participantresponses, allowing participants to explain, forinstance, what factors they attach to trusting citizenscience data or the social networks they employ tomake decisions regarding water resources manage-ment. We first interviewed community member vol-unteers immediately before the implementation ofGET WET! in their community. A follow-up interviewwas conducted approximately six months followingthe public presentation of citizen science by the stu-dents. Questions in the interview guide, of both thepre- and post-GET WET! visits, were directed to thecommunity member volunteer’s perspective first andthen to the community as a whole to determine ifthey shared or did not share the same opinions.

Forty interviews were recorded and transcribed.Transcriptions were compared to digital recordings toassure accuracy of responses. NVivo software (QSRInternational, Cambridge, MA) was used to codeinterviewee responses through open coding, based onresponses, and then axial coding was used from thoseresponses in order to identify emerging themes.Codes were analyzed until no new codes appeared. Aconceptual model was created based on emergingthemes. Tabulation of responses, as a way of indicat-ing the frequency of responses or occurrence ofthemes, were not calculated following the recommen-dations of Creswell (2007). This could be appropriateif the participants were a representative sample ofthe population. However, we used a network sam-pling approach with a purposive sample. In this typeof qualitative research, if a comment was made ortheme coded then it is simply known to exist, but wedo not assert intensity or frequency.

We followed Lincoln and Guba’s (1985) comprehen-sive recommendations for assuring validity and reli-ability equivalents in qualitative research. Validitywas addressed through the triangulation of multiplesources. External validity came from the research

TABLE 1. Example Semi-Structured Interview Questions.

Pre-Citizen Science Program QuestionsWill you trust GET WET! results? Why or why not?What would change your opinion?How would your community view student-generatedscientific results?

Post-Citizen Science Program QuestionsDo you trust the results and ⁄ or information generated byGET WET!? Why or why not?

In what ways was the program successful orunsuccessful?

In what ways was the program an asset or not an assetto your community?

How do you think your community viewed thestudent-generated results?

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design, member checking, and the ability for the gen-eralized results to apply beyond the study. Reliabilitywas improved through the clarity of organization inthe detailed records kept within the database created,the protocol used, the quality of the design, and abil-ity for replication of the results when performed byanother researcher. Analysis began with theorydevelopment through a literature review and contin-ued throughout the research project. Participantobservation was also used to collect supplementaldata. Supplemental data was included in the digitalinterview recordings then transcribed along with theinterviews. Additionally, field notes, member check-ing, and external audits were also performed toassure validity and reliability through triangulation(Creswell, 2007). Participants interviewed wereinformed they could review transcripts of their ses-sions, and supplemental phone calls to intervieweeswere made if there was a need for clarification. Inter-coder agreement was used through multiple codersanalyzing portions of interview transcripts.

RESULTS

The key themes that emerged from this researchwere interpersonal trust in students, teachers, andother community member volunteers, and familiaritywith testing kits and protocols, and water qualitydata. There was significant trust in the citizenscience data generated by students, although thisperception was not held by all. Every communitymember volunteer supported proving the validity andreliability of the citizen science data through qualityassurance ⁄ quality control measures. Local communitytrust, beyond citizen science program volunteers, wasperceived to be related to interpersonal and disposi-tional trust.

Interpersonal Trust in Students

Community member volunteers specifically men-tioned interpersonal trust as a reason they trusted citi-zen science data generated by students. Interactionsbetween the student citizen scientists and the commu-nity member volunteers increased trust in the data. Acommunity member volunteer stated, ‘‘seeing the pro-gram, and seeing how it’s done’’ created trust in thedata for him. Basically, community member volunteersgained trust in the results through the experience ofhelping students with the tests: ‘‘… the monitoringthat went on [increased trust] … those of us who wereinvolved with the children and assuring what they

were doing was revealing a pretty accurate finding[s]…’’ Two other interviewed community member volun-teers said, ‘‘The students were … sincere about theirresearch and their results, so there is no reason todoubt their integrity, in terms of that sort of informa-tion,’’ and ‘‘Before I saw what the protocols were Ireally didn’t know that kids would be credible valid col-lectors of that kind of fairly scientific data. I’m wrong.’’

There were some community member volunteerswho did express reservations about the student-gen-erated citizen science data. Those with reservationsfelt that students were not experienced enough to beconsidered equal to the professionals from the com-munity that volunteered. This was expressed by acommunity member volunteer who claimed, ‘‘Because[the students] are not trained, I think, in appropriatedata gathering.’’ One participant felt that because ofthe role of students, and their lack of experience, theyshould not be held accountable for the data collected.

Interpersonal Trust in Teachers

A community member volunteer suggested thatadults and children often do not feel comfortable work-ing together as equals, which may explain the mixedresults related to interpersonal trust between commu-nity member volunteers and student citizen scientists.Different life experiences and communication stylescontribute to the inability to develop interpersonaltrust. In this regard, teachers were key to bridgingbetween students and community member volunteers:

… Adults and kids are not used to talking andorganizing at this level … adults and studentselbow to elbow talking and interacting … adultsare not necessarily comfortable being around kidsand vice versa. That’s why educators are so incredi-ble to me; they can bring them together.Community member volunteers indicated that per-

sonal interaction and with the teachers’ abilities tohave students follow the science protocols were a rea-son they believed the students could produce validand reliable results. One community member volun-teer described, ‘‘… knowing the teachers that werepart of the project and knowing how they run theirclassrooms,’’ was critical. Another community mem-ber volunteer stated, ‘‘I have confidence in [the tea-cher] and how she runs her program with the kids.’’

Interpersonal Trust in Other Community MemberVolunteers

The community member volunteers were also asource of increased trust in the citizen science datagenerated by students. Recall, the community



member volunteers were all recruited into the citizenscience program because of their interest in or usefor water quality information. As such, many wereconsidered professionals in the water resources, envi-ronmental, or natural resources management fieldsand a source of valuable credibility. ‘‘There were edu-cated adults there to help with the program.’’Another community member volunteer said, ‘‘… itwas monitored by people in the field in addition tothe parents and teachers.’’ Computer specialists thatassisted students with the GIS portion of the pro-gram, engineers, education administrators, and pro-fessors of science education believed that thegroundwater professionals and the scientists thatwere involved had an authority and a desire to seethe testing done to their rigorous satisfaction.

Familiarity with Protocols and Testing Kits

Many community member volunteers expressedtrust in the accuracy of the citizen science databecause of the simple, near fail safe chemistry testingkits. This theme was support by statements such as,‘‘There are not lots of details and the tests are verysimple and they can be repeated.’’ Another commu-nity member volunteer agreed saying, ‘‘They arepretty simple tests … it was not really anything com-plicated … pretty user friendly.’’ Some communitymember volunteers had previous experience workingwith the tests or they performed the tests with thestudents and felt they were acceptable for middle andhigh school students. They also felt the data the testkits produced were consistent and in line with whatwas expected for local groundwater chemistry:

… the HACH kits are pretty foolproof if you do itcorrectly and the data fell in place … we really didnot see anything wacky … [there was a samplewith a] really high iron content … you could tell bylooking that it was rusty brown so and so it proba-bly wasn’t a bad result at all.There were a small number of community member

volunteers that did not trust the citizen science datagenerated by students because of the protocols andtesting kits. These individuals believed the only wayto produce accurate, valid results were to have thewater tests performed in state certified labs by pro-fessional scientists with high tech equipment. Toillustrate, one community member volunteer said,

I would question how the instruments are well cal-ibrated. I would need more information on themethodology and on the tolerance and the preci-sion of the measurements … I want to see it com-pared to some other lab number to know thateverything was done correctly. It’s so hard for eventrained investigators to get the right data and to

calibrate correctly, and the further out you go fromthe core the more likely that you are going to geterrors in the measurements.

Familiarity with Water Quality Data

Some community member volunteers trusted thecitizen science data generated by students because oftheir knowledge of the scientific process, knowledge ofexpected water quality results, and the ability to easilyidentify anomalies in student results. Many commu-nity volunteers believed that the large number of stu-dents testing water in an area would generate resultscapable of showing valid and reliable patterns; moststudent results should be similar since they share asimilar geologic region. Anomalies would be attributedto a lack of validity or reliability, perhaps due tohuman error in the data collection. For instance, com-ments were made such as, ‘‘… with any experimentthere is going to be the outliers, and so as long asthings look pretty consistent, or if there are some areaswhere there are variation, there is some sort of expla-nation as to why that might be happening,’’ and ‘‘Ithink it is nice when you have that many kids toobecause it is really easy to see what the truth is andyou can see an anomaly and you can see that there ispatterns and you can see all of that stuff.’’ Finally, onecommunity member volunteer stated succinctly,‘‘There’s always error associated with scientific mea-surements ... I think with student workers there willbe a little more … it’s just a matter of saying how reli-able are these—they’re 80% reliable; they’re 90% reli-able—you just label them as such and move on. If youare just honest about the process, people can make uptheir own decisions, and that’s fine.’’

Quality Assurance ⁄ Quality Control

All participants wanted student data verified asvalid and reliable. Some, in particular, wanted profes-sional labs to test the same water the students weretesting and to compare lab results with studentresults. This step was critical to some choosing totrust the citizen science data generated by students:‘‘[The results are] backed up by the university. Imean you … are checking it, qualifying it.’’

Perception of Local Community’s Trust in CitizenScience Data

Community member volunteers were asked howthey felt others in the local community would view citi-zen science data generated by students. Familiarity

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and dispositional trust were the primary themes thatemerged in relation to the local community trust in thedata. Community member volunteers based theirresponses on previous experience dealing with theircommunities. Many responses focused on the fact thatthe citizen scientists and community member volun-teers, themselves, were well known in their communi-ties. They felt this familiarity was a reason thecommunity would trust the data. Others felt the localcommunity would rely on dispositional trust.

The interviewed local community members gener-ally thought that the local community would trustthe citizen science data because they would be famil-iar with the citizen scientists. For instance, a localcommunity member said, ‘‘… especially in these smallcommunities, they know the students, and they knowthe work ethic, or they know who is careful.’’ Citizenscientists were seen as better communicators of scien-tific data. One community member volunteer com-mented, ‘‘… information is going to be shared withthe community, it’s shared in a manner that makessense to people; it’s not over their heads, it’s notbeing presented in a manner that doesn’t make senseto the average person in the community and thearea.’’

There was also a strong distrust of outsiders:You might argue that a scientist should be happierwith a fellow scientist, they would want to see top-notch training and a record of results … but Ithink things change when you talk to the public atlarge, they are not scientifically trained … I think[the public] has more faith in people they know …there’s personal buy-in, and it almost doesn’t mat-ter what they have to say because it is comingfrom a trusted source … fact that you know thepeople at the school. They’re the cashier, the peo-ple you saw on the swim team, and these are thekids that play on the football team, march in theparade. They’re your neighbors, and you see themevery day, so you know this is not some big con-spiracy hatched in Washington — it’s your next-door neighbor who delivers your paper and mowsyour lawn.A geologist from Maine discussed the perception

that local communities are skeptical of outsiders whogenerate scientific data about their area when hesaid, ‘‘I think in general there is a certain amount ofskepticism of white-coated scientists by the public ingeneral.’’

Dispositional trust was mentioned by volunteers inwhether or not the local community would trust citi-zen science data generated by students. Some inter-viewed community member volunteers felt thatcommunity members would decide to trust GETWET! or student-generated data based on their ownworldview. For example, a community member volun-

teer remarked, ‘‘I think they will view them throughwhatever lens they use to look at the world. If theysee this as an imposition, then they’re going to dis-miss it as a bunch of kids.’’

DISCUSSION AND CONCLUSION

Interpersonal trust and familiarity were the pri-mary themes that emerged from the interview data.All participants expressed that the level of interper-sonal trust that they had with others involved in thecitizen science program served as the foundation forevaluating risk and thereby trust in the citizen sci-ence data. Community member volunteers gainedtrust in citizen science data through increased inter-personal trust in students, teachers, and other com-munity member volunteers in the citizen scienceprogram. This agrees with the past trust literaturethat places social interactions as one of the tenets oftrust theory (Coleman, 1988; Irwin, 1995; Kramer,1999; Friedman, 2002). This finding also validatesKramer (1999), Lidskog (1996), and Millstone andvan Zwanenberg (2000) who identify the idea thatfrequency of interaction enable citizen science partici-pants and users of citizen science data to better eval-uate their trust of the data. Familiarity throughpersonal involvement with GET WET! enabled com-munity member volunteers to evaluate the risk oftrusting the student data they helped produce. Thetransactions that occurred between people have alsobeen recorded in literature as a means to gain inter-personal trust and familiarity between participantsin collaborations (Granovetter, 1973; Coleman, 1988;Gulati, 1995; Bigley and Pearce, 1998; Glaeser et al.,2000; Wondolleck and Yaffee, 2000; Davenport et al.,2007).

Local community members were more confident instudent-generated data because the protocols wereeasy to follow and the chemistry testing kits wereeasy to use. The kits were simple, with few steps,and students had significant supervision while per-forming the tests. This finding coincides withresearch published by Galloway et al. (2006) thatstated students were effective in data accuracy if theinstructions are clear and the goals are simple.Familiarity with the test kits, either through previ-ous experience or by participating with student test-ing, provided the community member volunteers theability to trust the results.

Community member volunteers were also inter-ested in having quality assurance ⁄ quality controltechniques in place to verify student results. Theirtrust in science came from an understanding and



belief in the processes of scientific method (Kramer,1999). Other community member volunteers felt thatthe number of students participating in a given geo-logic region would produce significant numbers forthem to be able to recognize outliers and patterns inthe data. Community member volunteers expressedthat these statistics would allow human errors to beeasily identified. Only a couple of community membervolunteers felt that no amount of quality assur-ance ⁄ quality control could replace professional exper-tise and state certified water quality testing labs.Social scientists such as Slovic (1999) have docu-mented that some data users only trust institutionalscience and that some believe only trained scientistsare capable of valid science.

Community member volunteers reinforced Lidskog(1996) and Ferretti’s (2007) assertions that citizenscience allows for local communities to be more trust-ing of the results because the data were generatedand analyzed by local people. These results are alsosupportive of Friedman (2002), Irwin (1995), and Lid-skog (1996) who identified that public trust in scienceis primarily a function of trust in the organization orperson dispensing the results.

The research reported here furthers trust theory inthe discipline of science education. There are no pre-viously published studies regarding the trust in stu-dent-generated data by those interested in andpotential users of their environmental monitoringefforts. Most education research focuses on the pres-ence or absence of trust between groups of teachers,students, parents, and principals but does not focuson student-generated data. Previous research in edu-cation regarding trust is also lacking dimensions oftrust other than the dimension of relational trustfound in Bryk and Schneider (2002). This type ofinterpersonal trust does not focus on what is neces-sary for community member volunteers to trust citi-zen science data generated by students.

This research also furthers trust theory by proposingthat interpersonal trust, dispositional trust, familiar-ity, and quality assurance ⁄ quality control measuresare the key variables involved in trusting citizen sci-ence data generated by students. Although familiarityis a repeating theme in the factors of trust (Gulati,1995) and has been linked to scientific trust (Sztompka,2007), it has not linked interpersonal trust through cit-izen science programs. Researchers that want tounderstand the dimensions of trust necessary to createsuccessful citizen science programs that are trusted bycommunity members will benefit from these results.

Trust in citizen science data, especially data gener-ated by students, is an important area of study if thegoal is to have knowledge created in these settingsemployed in water resources management. We recom-mend that citizen science programs that use students

and collect water quality data should focus on build-ing interpersonal trust between potential users of thedata and those involved in the citizen science pro-gram. Our case study showed that when communitymember volunteers interacted with students andteachers successfully implementing protocols theirtrust increased. As well, trust was enhanced by form-ing community collaboration and having volunteersin the classroom. To the extent that other water-based citizen science programs can involve multiplepartners in their collaborations, it is anticipated thatwill support trust in the validity and reliability of thecitizen science data. As well, citizen science programscan enhance trust by choosing familiar testing kitsand measuring parameters familiar to those whomight use the data. We also discovered that regard-less of trust in the data, all of our case study partici-pants wanted quality assurance ⁄ quality control tests.Citizen science leaders should build this into theirprograms as a way of enhancing trust.

Case studies and qualitative research have limita-tions. It is not possible to tabulate findings in a quanti-tative way. Future research should consider measuringtrust in citizen science data through quantitative psy-chometric tools. In particular, quantitative methodswould be an appropriate way of testing for different lev-els of trust among various kinds of community mem-bers. Future research should also include long-termdata to see if the dimensions and factors that influencetrust change with length of involvement in citizenscience programs. Consecutive years of success withquality assurance ⁄ quality control validation ofstudent-generated data may change the perceptions ofcommunity member volunteers that did not trust thedata. It would also be interesting to study citizenscience effects on student interest in the environment,water resources management, science careers, and citi-zen science. Students were exposed to citizen science,potentially, for the first time through GET WET!Students may take a more active role in the commu-nity, or may return to the school to assist in subsequentcitizen science programs. It is a robust area for futurestudies, as are many aspects of citizen science.

ACKNOWLEDGMENTS

This research was supported by United States Department ofAgriculture NIFA Integrated Water Quality Grant ME0-2008-03618.

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