Affinity Research Groups in Practice: Apprenticing Students in Research

Affinity ResearchGroups in Practice:Apprenticing Students in Research

ElsaQ.Villa,a Kerrie Kephart,b AnnQ.Gates,a

Heather Thiry,c and Sarah Hugc

aUniversity of Texas at El Paso, bUniversity of Washington,cUniversity of Colorado Boulder

AbstractBackground The affinity research group (ARG) model is a set of practices built on acooperative team framework to support the creation and maintenance of dynamic andinclusive research groups in which students learn and apply the knowledge and skillsrequired for research and cooperative work. Using situated learning theory, we conducteda qualitative study of current and former ARG members to understand the potential ofthe ARG for preparing students for graduate school and professional research careers.

Purpose Our study investigated how the ARG model influenced students, particularlythose from underrepresented groups, in becoming researchers and practicing computerscientists.

Design/Method We employed multiple data collection methods, including individualand focus group interviews and participant observation, to investigate whether thismodel had lasting effects and sustainability beyond the time students spent in an ARG.

Results Using themes emerging from our data analysis, we can explain how studentsbecome contributing members of ARGs, group identity and cohesiveness are formed,members learn collaboratively, members participate in larger professional communities,and participants’ identities are transformed from student to researcher.

Conclusions Findings suggest that the structural and procedural elements of ARGssupport students’ growth and development as researchers and their gradual socializationinto broader computer science research and professional communities through legitimateperipheral participation and immersion in situated practice.

Keywords communities of practice; cooperative learning; undergraduate research

IntroductionIncreasing the number of qualified graduates in science, technology, engineering, andmathematics (STEM) is a growing and urgent need for the United States (Committee onScience, Engineering, and Public Policy, 2007; PCAST Report, 2007). A multitude ofinitiatives target this need by focusing on the retention of students in the sciences, butfew of these initiatives serve higher education institutions across departments. There is

Journal of Engineering Education VC 2013 ASEE. http://wileyonlinelibrary.com/journal/jeeJuly 2013, Vol. 102, No. 3, pp. 444–466 DOI 10.1002/jee.20016

also a need to increase workforce diversity, which research shows may enhance productivi-ty and creativity of organizations as a whole and design teams (Jackson, 1996). To meetthese needs, engaging undergraduates in research provides an avenue to prepare studentsfor careers in STEM by involving them in problem-solving experiences and exposingthem to the excitement of innovation and discovery. Indeed, engaging students in researchis a widely accepted approach for deepening their knowledge base and providing practicein skills (e.g., communication, critical thinking, problem solving, and team skills) essentialto business, industry, and government. Research is also a means for undergraduates togain and demonstrate domain expertise (Stevens, O’Connor, Garrison, Jocuns, & Amos,2008), and it serves to reduce attrition of STEM majors, in particular those from underre-presented groups, e.g., females, persons with disabilities, and ethnic minorities, who aresignificantly underrepresented at advanced levels of engineering and science (Jones, Barlow& Villarejo, 2010; Nagda, Gregerman, Jonides, von Hippel, & Lerner, 1998).

A common practice in research programs is to recruit and involve the most visibly suc-cessful students, those who achieve what Stevens et al. (2008) call measures of “accountabledisciplinary knowledge” (p. 356), such as competitive grade point averages (GPAs) andhigh test scores. This recruitment model, however, limits the number of promising studentswho can benefit from research experiences, and it provides such experiences only to thosewho may already be highly motivated and well prepared to succeed in their undergraduatestudies and ultimately in their chosen careers.

With a goal of extending research experiences to a broader range of students, in 1995a team of faculty in computing at the University of Texas at El Paso (UTEP) developedand implemented the affinity research group (ARG) model (see Gates et al., 2008;Kephart, Villa, Gates, & Roach, 2008; Teller & Gates, 2001). The ARG model operateswith what Bensimon (2005) described as an “equity cognitive frame” in which facultyview the development of all students as an institutional responsibility. ARG is built on acooperative team framework imbued with cooperative-learning principles, which havebeen shown to increase student achievement and self-esteem (Johnson & Johnson, 1989;Johnson, Johnson, & Holubec, 1992; Johnson, Johnson, & Smith, 1991). This frameworksupports the creation and maintenance of dynamic and inclusive research groups in whichstudents learn and apply the knowledge and skills required for research and cooperativework. Specifically, an ARG emphasizes the conscious and explicit development of skills.

In studying the ARG model, we realized these groups exhibited attributes of a commu-nity of practice in which learners develop the skills, knowledge, and expertise of the groupthrough supported immersion in its practices (Lave & Wenger, 1991). The motivation,then, for our research was to collect and analyze data from two closely related researchgroups to investigate ARGs’ impact on participants’ development of the knowledge, skills,and abilities required of computing professionals.

BackgroundCommunities of PracticeThe concept of communities of practice draws from the theory of situated learning devel-oped by anthropologist Jean Lave and computer scientist Etienne Wenger. Lave andWenger (1991) proposed the notion of communities of practice within the broader theoryof situated learning in order to explain the relationship between the individual learner andbroader social structures and institutions that influence learning. Thus, situated learning

Affinity Research Groups in Practice 445

theory offers a complex and holistic view of what it means to learn – in essence, to learnis to become a knowledgeable, skillful member of a community. Learning is viewed as“situated” because it takes place in the meaningful, authentic activity of a social group.Individual learners participate in meaningful ways at a level appropriate for their depth ofexperience within the community and its practices.

Lave and Wenger (1991) use the term legitimate peripheral participation to describe howlearners begin their engagement in a community of practice and over time gradually increasethis engagement through activities emulating and enacting the community’s practices. In acommunity of practice, learners are becoming members of a community, in this case, a com-munity of researchers. Ideally, expert participants in a community serve as models of profes-sional practice for novices, imparting the community’s values, tools, language, knowledge, andskills through everyday work and interaction in its shared repertoire and purpose. In the pro-cess of becoming members, the nature of their participation changes, their influence on thecommunity’s practices increases, and their identities in relation to other participants change.

We adopt the concept of identity as defined by Holland, Lachicotte, Skinner, andCain (1998), in which identity is viewed as a means of leveraging social tools to express asense of self and to act within sociocultural worlds. Holland et al. argue for a perspectiveon identity that ties individuals’ sense of self to their activities and actions within social-cultural groups:

Persons develop more or less conscious conceptions of themselves as actors in sociallyand culturally constructed worlds, and these senses of themselves, these identities, tothe degree that they are conscious and objectified, permit these persons . . . at least amodicum of agency or control over their own behavior. (p. 40)

The development of this sense of self is dynamic and transforms individuals as theyactively participate in a particular group where specific activities, social interactions, andpractices intertwine. Learning the practices and discourse of a particular group informs anindividual’s identity development, while individuals inform the practices and discourse ofthe group. Identity is developed in largely tacit and unconscious ways as an individual iseither recruited or seeks entry into a specific group and learns and embodies the practices,language, and discourse of others in that group. Bringing this notion of identity into playwith the concept of communities of practice, we suggest that communities of practicegalvanize the production and transformation of identities while learners negotiate themeaning of the discipline-specific practices and activities of the group. As an individualparticipant’s identity vis-�a-vis the group emerges, each participant simultaneously displaysfor others who she or he is and receives feedback from the group about who she or he istaken to be (Holland et al., 1998).

Thus, learning according to this theory is viewed in social, historical, and relationalterms: Learners’ social positions vis-�a-vis other members of the community shift andchange over time, as do the purposes for learning and the shape, purpose, and content ofthe group’s practices. As Lave (1998) describes it, learning is

a social phenomenon constituted in the experienced, lived-in world, through legitimateperipheral participation in ongoing social practice; the process of changing knowledge-able skill is subsumed in processes of changing identity in and through membershipin a community of practitioners; and mastery is an organizational, relational character-istic of communities of practice. (p. 64)

446 Villa, Kephart, Gates, Thiry, & Hug

Another aspect of communities of practice relevant to our study is the existence of anunderlying social purpose for the group’s activities and practices that serves to motivate par-ticipation by its members and, over time, organizes the group’s activities into a body ofpractice. In a communities-of-practice model, learning occurs through apprenticeship. Laveand Wenger (1991) drew on examples of apprenticeships to illuminate some key conceptsof the model. In apprenticeship situations, more-experienced community members carrymore responsibility and are expected to perform at higher levels of expertise than novicemembers, who participate first from the periphery of the group’s core activities and thengradually take on greater responsibility as their knowledge and expertise develops.

Affinity Research GroupsThe affinity research group (ARG) model builds from the research literature regardingpositive student outcomes from undergraduate research experiences. Recent studies of stu-dent outcomes from undergraduate research in STEM fields have empirically identifiedthe range of cognitive, personal, and professional benefits that result when students engagein research. Specifically, undergraduate research students enhance their scientific and com-putational thinking abilities using critical thinking and problem-solving skills (Bauer &Bennett, 2003; Hunter, Laursen, & Seymour, 2007), communication skills (Bauer & Bennett,2003; Kardash, 2000; Ward, Bennett, & Bauer, 2002), teamwork skills (Laursen, Hunter,Seymour, Thiry, & Melton, 2010; Ward et al., 2002), and research skills (Hunter et al.,2007; Kardash, 2000; Seymour, Hunter, Laursen, & DeAntoni, 2004). Students in under-graduate research gain confidence that they can “do” science and “be” scientists (Hunteret al., 2007; Russell, 2005; Seymour et al., 2004; Ward et al., 2002). They develop mentor-ing relationships (Hunter et al., 2007) and feel more prepared for graduate school andfuture careers (Russell, 2005).

Although it is rare, some undergraduate research students present their work at profes-sional conferences or co-author scholarly articles (Hunter et al., 2007). However, participa-tion in undergraduate research rarely fosters highly complex, scientific thinking skills, suchas identifying a research question, developing and modifying a research design, or gaininginsight into the epistemological nature of scientific knowledge (Hunter et al., 2007;Kardash, 2000). Nonetheless, research clearly benefits all participants, in particular studentsfrom groups traditionally underrepresented in the sciences and computing, because it pro-vides enhanced professional socialization and career preparation. Students involved inresearch are more likely than those who are not involved to be retained in their major(Nagda et al., 1998) and pursue graduate degrees (Hathaway, Nagda, & Gregerman, 2002).Undergraduate research students from underrepresented groups also gain increased confi-dence and enthusiasm for their majors. These affective outcomes are particularly importantfor underrepresented students because research shows their interest for their discipline ismore important than their GPA in predicting retention in the major (Grandy, 1998).

Undergraduate research benefits students despite the fact that research advisors oftendo not recognize their role in research as educational (Feldman, Divoll, & Rogan-Klyve,2009). Poorly designed student projects and lack of mentoring during the research experi-ence can result in students’ loss of interest in graduate school or even in the disciplineitself (Thiry, Laursen, & Hunter, 2011). By offering an explicit model of mentoring andstudent development, ARGs encourage advisors to view their role as pedagogical and tofocus on student learning and growth during the research experience. In this way, the ARGmodel consistently delivers the positive outcomes of undergraduate research, without the


negative results reported from poor-quality experiences that can result from ad hoc under-graduate research advising.

An ARG actively engages undergraduate and graduate students in the practices ofeffective research groups through its deliberate design of activities aimed toward develop-ing students’ disciplinary knowledge, research abilities, and team skills (Gates et al., 2008;Kephart et al., 2008). Faculty members in an ARG, for example, set aside time duringresearch team meetings to focus on teaching and practicing a skill, e.g., articulatingresearch in a succinct manner. ARG members have or are developing an affinity for a par-ticular research topic and share, to greater or lesser extents, common research goals. It isimportant to note that the construction of domain knowledge and the ability to articulateunderstanding is also embedded in the day-to-day operation of conducting research.

Figure 1 presents the essential elements of an ARG, which integrates the cooperative-learning principles (Johnson et al., 1992) and the adoption of core values and a sense ofpurpose (Collins & Porras, 1994), all of which actively foster student connectedness. Theuse of cooperative-learning principles structures discourse and activities to support mem-bers in their development as researchers. ARG activities are designed to create cooperativeteams that incorporate the five essential elements of cooperative learning: positive interde-pendence, face-to-face interaction to promote all members, individual accountability,social skills development, and group processing (Johnson et al., 1991).

Identifying core values and a sense of purpose establish reasons for the group’s existencethat are explicit and visible to all members. The sense of purpose should be specific enoughto guide the group’s decision making, especially regarding the types of projects it will takeon and choosing which students to invite into the group, yet it is flexible and broad enoughto endure the inevitable changes in the group composition from year to year. For example,

Figure 1 Essential elements and activities of affinity research groups.


a core purpose of an ARG might be to involve students with diverse backgrounds in solarenergy research that contributes to the betterment of society. While ARG mentors take thelead in defining the group’s core purpose, all group members are introduced to the group’score purpose at the annual orientation meeting where it serves as the foundation for thegroup’s activities.

As shown in Figure 1, an ARG’s defining activities and processes are the annual orien-tation, workshops, regular meetings, and project management. The annual orientation isnormally scheduled at the beginning of the academic year and includes all members –new students, continuing students, and mentors. The activities are designed to introducenew students to the ARG philosophy and values, the group’s research goals, the elementsof the research process, and the principles of cooperative learning that form the basis ofthe group’s interactions. In the orientation, not only do students learn about the projectsbut the focus is on developing cooperative team skills, and returning members have anopportunity to renew their commitment to the group.

Workshops are designed specifically to teach and practice specific skills in a focusedmanner. A workshop can cover writing a research proposal, asking probing questions,writing technical papers, and learning how to constructively critique research posters. Reg-ular group meetings are structured primarily to discuss the research, present deliverables,and monitor progress. Students periodically engage in an activity designed to practicecommunication and team skills. It is in the workshops and group meetings that the delib-erate and intentional development and practice of technical, team, and professional skillsand knowledge occur. Such skills and knowledge are required for research and cooperativework and are a distinguishing characteristic of an ARG.

Project management requires students to define their project goals, objectives, and deliver-ables. After defining project goals and objectives, outlining tasks, and clarifying dependencies,students work together to prepare timelines for assigned tasks. Deliverables are concrete arti-facts, such as presentations, paper summaries, design documents, and an annotated bibliogra-phy, that document progress on a project. Faculty mentors assign tasks to individual membersand help students to understand the expectations associated with the tasks.

The ARG model encourages faculty to identify and recruit students who, althoughthey may not score highly on tests or have high GPAs, nevertheless demonstrate potentialfor research through other aspects of their performance in the classroom, in particularstudents who demonstrate higher level thinking. The ARG model broadens participationof such students who might not otherwise persist to graduation or continue to graduateschool; it supports them to learn research, technical, and professional skills and to inte-grate those skills with domain knowledge. As a result, students and faculty, in particularthose from underrepresented groups, develop the skills and practice that can positionthem to reach higher levels of productivity and achievement and to become leaders inthe workforce.

Like any other teaching method, the ARG philosophy involves a particular way ofstructuring interaction and can be taken up by any faculty member interested in learningthe method. One type of interaction that is common in some classrooms – but rarely per-formed in a laboratory setting – is the instructional conversation. To demonstrate howskills are deliberately and intentionally taught, Figure 2 presents excerpts with commen-tary from a transcript of an ARG research group meeting elucidating how ARG elementscan be realized. To set the context, the research group met to discuss a research paper


Figure 2 Probing question activity.


and simultaneously work on the essential research skill of asking probing questions. Thefaculty mentor began the meeting by describing the goals of the meeting and telling thegroup that the author would be presenting a colloquium at which the students will beexpected to ask probing questions.

Research DesignResearchQuestionsOur research questions were designed to investigate the connection between the elementsof situated learning theory, as aforementioned, and the lived experiences of ARG partici-pants. The research questions were

1. To what extent and how do former ARG participants perceive that their experi-ences in the ARG have influenced their professional roles and identities?

2. Which specific components of the ARG model, if any, do the participants mentionas influential in forming their identities and shaping their postgraduate experiences?

3. How do the structure and practices of ARGs support student apprenticeship inthe local (campus-based) and global communities of computer science research?

Study ContextParticipants were drawn from graduates and current students of two ARGs at UTEP inwhich approximately 100 undergraduate, master’s, and doctoral students have participatedsince 1995. Their time in an ARG ranged from one semester to five years. For example,one participant’s tenure in an ARG ranged from the time she was an undergraduate fresh-man through completion of a master’s program. ARG student researchers typically spendapproximately 20 hours a week in an ARG lab and are funded through research grants.Occasionally, students volunteer in an ARG if money is not available and, in some instan-ces, they are eventually supported when funds become available.

MethodsWe take an interpretive approach to our data and to our role as researchers. Interpretivistsseek to understand the meaning within human social interactions, focusing on the“immediate and local meanings of actions as defined from the actors’ point of view”(Erickson, 1986, p. 119). We see qualitative analysis, as explained by Geertz (1973), as aninterpretive science in search of meaning, as ascribed by the study participants themselves.Thus, to locate meaning within human social interaction, the researcher must interprethuman actions and behaviors. In order to understand the meaning within human interac-tions, researchers must also place those actions within the social, cultural, linguistic, andbelief systems of the individuals (Schwandt, 2000). In this study, we sought to make senseof the experiences of ARG members through their point of view and to locate thesemeanings within social and cultural contexts.

To better understand the meanings and local contexts of ARGs in practice, wevideo-recorded ARG participants in deliberate skills development activities, such as theprobing question activity described in the previous section. We also observed partici-pants in large group meetings, such as the annual orientation or skills developmentworkshop, in their research labs, at professional conferences, and in their classrooms.


These observations allowed us to analyze the professional behaviors in which partici-pants engage in a naturalistic rather than in a contrived experimental setting (Lincoln& Guba, 1985), and primarily informed our last research question regarding the struc-ture and practices of ARGs that support student apprenticeship into communities ofcomputer science research.

We conducted one-on-one and focus group interviews to obtain samples of the lan-guage participants use to make sense of and describe their interpreted experiences in theARG and to gauge the long-term effects of these experiences. The research participantswere identified on the basis of their availability to participate in the study and representa-tiveness, e.g., variation in gender, ethnicity, amount of time spent in an ARG, and periodduring which they were ARG members (see Table 1).

It is important to note that we do not claim that our participants are a statistically rep-resentative sample of the broader ARG population. Rather, as a group, they represent thebroad range of demographic, other characteristics, and outcomes for students who partici-pated in an ARG in an institution where over 80% of enrolled undergraduate students areHispanic. In particular, we were interested in interviewing past ARG participants whorepresented a range of professional positions, such as recent graduates transitioning intothe workforce, new faculty members, industry professionals, and soon-to-be graduates inadvanced studies. For our data collection, we interviewed former participants at variousevents, such as alumni gatherings at the university, when alumni visited family in El Paso,or at a focus group with alumni who had attended an accreditation site visit. The individ-ual and focus group interviews were audio recorded and transcribed verbatim. Standardinstitutional review board procedures were followed, including the use of pseudonyms toprotect the research participants’ privacy and to ensure their anonymity.

We conducted three individual interviews of approximately one hour each and onefocus group interview with three ARG alumni and three current ARG students, lastingapproximately two hours. Interview protocols of open-ended questions were based onSpradley (1980) to elicit descriptive responses. The protocol included questions about thestudents’ ARG experiences and their perceptions of possible connections between theircurrent work and experiences in an ARG.

Table 1 ARG Interviewee Summary Information

Name Gender Ethnicity

Status at timeof of interview/Highest degree

received Employment titleYears of

employmentYears

in ARG

Maggie F Hispanic Alumna/M.S. Technical Writer 5 6Mark M Hispanic Alumnus/M.S. Computer Scientist II 2 3Jorge M Hispanic Alumnus/B.S. Sr Software Engineer 3 1Leticia F Hispanic Alumna/M.S. Technical Support 2 3Ahman M Middle

EasternAlumnus/Ph.D. Assistant Professor 5 5

Lin F Asian Alumna/M.S. Technical Support 3 3Ignacio M Hispanic Doctoral Student na na 4Felix M Hispanic Doctoral Student na na 4Ana F Hispanic Master’s Student na na < 1


Data AnalysisAfter conducting the first few interviews and examining the emerging themes, we were ableto reformulate our research questions to hone our inquiry using an iterative process of datacollection and analysis (Creswell, 2003). Specifically, we adopted an inductive approach(Creswell, 2005; Thomas, 2006) to allow themes to emerge from the data as we coded eachline of the transcripts and then subsequently identified overarching themes. We analyzed thedata in a flexible manner while at the same time using insight informed by situated learningand communities of practice theories. From the viewpoints of the participants, this generalinductive process allowed us to extract themes, some of which were not accounted for bytheory (Corbin, 2009). Themes were divided among our team members in the analysis ofinterviews; our team iteratively and cooperatively performed these analyses to improvedependability of findings. As a result, the major themes, identified in the Findings section,emerged. Each research team member independently re-examined the data to confirm anddisconfirm evidence that addressed our research questions (Lincoln & Guba, 1985).

TrustworthinessRather than use the terms reliability and validity that are traditionally used in quantitativeresearch, we use the term trustworthiness to validate our qualitative research (Goetz &LeCompte, 1984; Janesick, 2000; Lincoln & Guba, 1985; Merriam, 2001). Lincoln andGuba (1985) suggest the following criteria to establish trustworthiness: credibility, trans-ferability, dependability, and confirmability. Credibility (internal validity) ensures anaccurate representation of what was experienced at a particular moment in time throughprovision of sufficient activities of the research, such as persistent observation and triangu-lation of sources, methods, and theories. Transferability (external validity) is determinedby sufficient evidence to reify the same outcome, given the particular environment andinteractions. Establishing transferability may be difficult, if not impossible, since no twoindividuals have the same life experiences. Dependability (reliability) is addressed by pro-viding enough information to convince other researchers that the same outcomes wouldhappen given the same situation. Finally, confirmability (objectivity) is the assurance thatthe researchers interpreted the data in a manner that was not influenced by bias or predis-positions. Taken together, these four criteria ensure trustworthiness.

To address credibility, this study utilized multiple data collection methods to acquire amore accurate picture of practices (Denzin, 1989). Our team consisted of five researcherswith different perspectives and backgrounds. We also conducted frequent member checks,i.e., meeting with participants to see if our interpretations of these practices and meaningsreflected participants’ reality (Creswell, 1998; Lincoln & Guba, 1985; Peshkin, 2000).The thick descriptions of data provided in this study, together with the emergence of pat-terns, further contributed to the credibility of the study. These detailed descriptions inthis study also addressed transferability by creating the context of the phenomenon understudy; that is, the descriptions created a snapshot of what occurred under these particularsets of circumstances. If it were possible to duplicate these circumstances, the same resultsmight occur, ensuring dependability of the study.

Finally, our role as team members in this research created confirmability. While wedeveloped relationships with ARG participants, we were not insiders, or actual partici-pants in the ARG groups. Specifically, one author, Ann Gates, was a principal developerof the ARG model, and her role in this study was to join the research team in providing


insight into specifics of the model rather than to participate in evaluation of the model.The remaining team members collected and analyzed data as a team effort; our diverseperspectives, backgrounds, and roles contributed to the effort. For example, authors Thiryand Hug were external evaluators for funded projects expanding the ARG model andhave been involved in objectively observing participants at multiple sites. Our remainingteam members, authors Villa and Kephart, were internal evaluators investigating researchquestions regarding the model’s effectiveness at the original institution. Thus, our analytictechniques of coding and analyzing the data among our team provided inter-rater reliabil-ity. In like manner, a wide variety of current and former participants provided differentperspectives and different types of data. Social situations also affect what participants willreveal; thus, all observations were conducted during actual ARG activities and meetings asa way to create a boundary for the study.

FindingsSeveral themes emerged from the analysis that allow us to explain how participants per-ceive their participation in an ARG to have influenced their sense of professional identityand which aspects of the ARG model they believe influenced the formation of their iden-tities and shaped their postgraduate experiences. These themes are: becoming a memberof an ARG, building group identity and cohesiveness, learning through working withothers, becoming members of larger professional and disciplinary communities, and trans-formation of identities from students to researchers.

Becoming a member of an ARG: Gaining access to the community of practice Inorder to understand the influence of ARG participation on students’ developing profession-al identities, it is worthwhile to start at the beginning and examine how they describe theirinitiations into the research group. Several participants described their self-perception priorto participation in the ARG as that of being outsiders vis-�a-vis the academic and researchcommunities. Given the ARG faculty mentors’ commitment to identifying and invitingstudents into the research group who are competent, but not necessarily confident, it is not sur-prising that the alumni and longtime members, whom we interviewed from specific ARGresearch groups in computing, reflected on this as they described themselves and how theybecame members of the research group. Ignacio, who was a Ph.D. student at the time of ourinterview and had become a member of the ARG as an undergraduate, described his under-standing of why he was selected for the ARG:

Back then I thought my mentor just needed someone to help her, and she had pickedme just ’cause I knew the system they were developing because it was the project forthe software engineering class. But now I know that she’s trying to find those peoplewho most likely would not have continued [into graduate school]. I feel that I wouldhave been one of those that would not have continued with my master’s if she had notoffered me [the research position].

Jorge, a software development leader in a small company, echoed Ignacio’s comments:

I think that my mentor just has a knack for finding students that don’t look verygood on paper. Myself, personally, I didn’t have the greatest GPA. I probably wouldhave had no shot to go for my master’s. But, thanks to my mentor, I got involved ina lot more research, and he did help me bring up my GPA.


Leticia, who was the first member of her family to attend college, joined the ARG as anundergraduate. At the time of her interview, she had completed her master’s degree and wasworking in technical support in the information technology department of a large organization.Prior to joining the ARG, she had had no exposure to research in computer science and describedherself as ignorant about the nature of research and lacking in confidence in her abilities:

I was the type of student that would go do my homework and go home. I really didn’tknow what was available and didn’t know my professors to the level to where I wouldtalk to them until I started talking to my mentor, and I realized that even though Ididn’t think that I could do certain things, whatever I could was enough and you justkept growing from there.

Leticia’s self-confidence did continue to grow through her experiences in the ARG.Later, as a graduate teaching assistant in a course that her ARG mentor taught, she feltsecure enough in her abilities to identify for her mentor another promising student whohad been “written off ” by most of his professors. In calling her mentor’s attention to thisstudent’s untapped potential, she also demonstrated that she had developed the self-assuredness to be able to challenge her mentor when she felt he was making a mistake.

Building group identity and cohesiveness: Becoming a community of practice It isnot unusual for members of a group or community to find it difficult to describe thedevelopment of the group, especially if the group was already in existence prior to theirjoining. The ARG participants we interviewed showed varying degrees of awareness ofthe development of the research group and their own active roles in its ongoing develop-ment and transformation. Several of them reflected on how participation in the ARG’spractices reinforced their sense of belonging to something special. Nevertheless, they pro-vided numerous examples of how cohesiveness, cooperation, and a sense of group identityform and are maintained through ARG practices.

Maggie, an alumna who entered the ARG as a sophomore and remained in itthroughout her master’s program, compared her experiences in the ARG with the typicalexperiences of undergraduates at UTEP:

UTEP is primarily a commuter school. And what was nice for me was that [theresearch group] gave me a home outside of lectures to interact with other students andget to know people better. We ended up spending a lot of time there . . . I rememberworking long hours late at night, on weekends, writing papers or discussing with otherstudents. So it brought us closer, as a group, and we just were friends.

Maggie went on to describe how the sense of commitment to the group grew as sheand her friends in the group approached their thesis defenses:

When Fabian did his thesis, he presented his presentation first to us. And this was notsomething that any faculty said we should do. He just did it, and then we asked himquestions. When Marina got her Ph.D., we did the same thing for her. I did my thesis,and they did the same thing for me . . . I guess that just illustrates the culture of thegroup. It was friendship, but it was also, “I want to do this for you, and you will do itfor me when I’m there.”

Thus, for Maggie and many of the other ARG alumni, the ARG became the primaryfocus of their academic and social lives. And for many, the bonds they formed with others


in the group still remained several years after graduation. Mark, who graduated with amaster’s degree in computer science, describes these bonds of friendship when he talks topotential graduate students about the people in the research group who became his friendsand how, even having been gone three years, there are “eight or nine of us who still con-tinue to talk and that shows you how close everyone was.”

Learning through working with others: Legitimate peripheral participation inARGs When asked to talk about the way their ARG operates, the students described indetail how the strong group ties and the close, structured interaction of members allowedthem to grow professionally. Felix expressed how he grew to understand that the critiqueof members’ work was essential to their growth:

I remember when I first joined the group I used to get mad because I’d give mypresentations to Ignacio and he’d tear them apart. They would be all [marked in]red and he’d tell me, “This is how you do it; this is how you say it.” . . . So youactually learn that they are not attacking you. They are just trying to make you be abetter individual.

Ahman, an assistant professor of software engineering whose participation in the ARGbegan during his doctoral studies, described the process by which he gradually becameable to write journal articles by attempting a first draft on his own and then sitting along-side his mentor and talking through revisions, and later by sending multiple drafts andrevisions back and forth with her:

My mentor had a very hands-on approach . . . Sometimes we would just stay inher office and work on [a paper]. I mean, we would never start working fromscratch. I’d have to write something and then we would edit it or rewrite . . .She would go through every paragraph, and let me know that, “this should havebeen this way, and this, do it this way.” . . . Before, I would have needed sevenor eight revisions. Now I need five.

Ignacio also talked about working closely with his mentor on writing. He had a strongsense of accomplishment and pride when one day, he was able to catch a grammar errorhis mentor made in a paper they were editing together:

I corrected the use of “which” and “that,” and my mentor was like “Ohhh, goodjob!” She was surprised and extremely happy. I corrected her, based on her teach-ing. It was a great accomplishment.

Teaching and learning in the ARG is not a unidirectional process. Part of the strengthof the community is that its knowledge is distributed across all members. Expertise is val-ued, whether it is held by senior members or by novices. Leticia described how she gradu-ally began to understand that her mentor trusted and counted on her knowledge:

My mentor used to say, “You’re the expert on that. I’m just supposed to helpyou reach your goal. You’re here to teach me.” That’s the trust you build. They[the mentors] trust you and you trust them.

In an ARG, novices have opportunities to develop expertise, and the model emphasizesthe importance of the mentor’s role in providing constructive feedback and positive inter-action. The mentor’s reinforcement and explicit identification of a researcher’s developing


expertise can help students begin to realize their potential, which can result in increasedconfidence.

Becoming members of larger professional and disciplinary communities Severalparticipants connected what they had learned in the ARG to their later professional suc-cesses. Maggie, for example, credited her experience in the ARG with preparing her towork well and flexibly with people in a wide range of positions in the Fortune 50 IT firmwhere she is employed as a technical writer:

I think it was the process of doing it and seeing how the other students did it, or see-ing how [my mentor] asked questions. Just being part of that and learning the pro-cess. And [now] I work with developers, I work with architects, I work with othertechnical writers, and it’s the same kind of process that we went through. It’s reallywhat I learned here and in working not with just [my mentor] but with the other stu-dents as well.

Jorge, a software development leader in a small company, described how he has lever-aged skills he developed in the ARG in order to get to know and impress the top execu-tives in his firm:

At my office, when it comes time to do a presentation, no one wants to do it. Every-one’s saying, “Jorge you do it. You present really well. You did really well the last fivetimes we made you do it.” . . . In our setting, the more you present, the more you getto interact with people higher up in the company, and the more you get to knowthem. [Others on my team] can do okay, but they’re just intimidated by it.

Mark, who has by choice made three job changes since graduation, believes that hisexperience in the ARG gave him more than technical skills. He credits the ARG withenabling him to “hit the ground running” at each of his jobs and to have the confidenceto speak up when he believes there is a problem:

It’s been a lot easier for me to transition from one job to another or from onetask to another compared to other people. I don’t know how it was at their uni-versities, but [on the job] it has been a lot more difficult for them to get started.That’s how it was with us [in the ARG] . . . It was one task after another. Itwas either buckle under the pressure, or multi-task.

Learning as indexed by the transformation of learners’ identities Many of the par-ticipants described themselves as having been changed by the experience of being in theARG. Leticia, for example, initially resisted joining the ARG when her mentor approachedher because she did not feel prepared to do research and did not know what was in-volved. Through her participation in the ARG, however, she came to realize that “whatever[she] could [already] do was enough” and her confidence “just kept growing from there.”Like Leticia, Ignacio also repeatedly referred to having gained self-confidence throughparticipation in the ARG, but he also pointed to a deeper transformation in his self-perception, as well as how others perceived him:

I didn’t have great grades when I was an undergraduate. And I really didn’t pushmyself. I was quiet, I was too shy, and my grades suffered because of that. Until I gotinto the research group. My mentor saw something in me and that’s why she offered


me a job. And because of that I felt a little bit better. I felt like, “Maybe I’ll work a littlebit harder.” And that’s when I became more outgoing and creative, more of a leader.

Ignacio described a similar transformation undergone by Vic, the student who had been“written off ” by most of his professors until Leticia had pointed him out to her mentor:

He was unmotivated. He didn’t care. He was just like, “I just want to graduateand get out of here.” But [through participation in the ARG], he totally turnedon, and he’s one of the brightest we’ve got. And he’s like a 4.0 graduate studentthat’s going to go on to his Ph.D.

It is important to note that what we refer to as identity transformations are shifts in self-perception, as well as changes in how these individuals are perceived by others. Such trans-formations are said to originate in the ways that individuals (and groups) are “positioned”relative to one another in social space in everyday discourse and social practice (Hollandet al., 1998; Holland & Leander, 2008). In this view, learning is at once both a social andcognitive process, and since cognitive change is shaped and made possible by social inter-action, everyday positionings are profoundly consequential for one’s learning potential andeventual identity transformations. For example, in the story of Vic, the ARG mentor posi-tioned Vic as a computer scientist with potential to do research following Leticia’s sugges-tion. Vic could have rejected that role, but instead took up the opportunity to work in theARG group. Through Vic’s interactions with peers and application of computing conceptsthrough research, ARG members and Vic himself began to see him as a capable, bright com-puter scientist. We argue, following Holland et al. (1998), that these changes are connectedto participation in the day-to-day practices of the ARG in which members perform certainsocial identities and take up social positions made available to them within the group. In thisway, members of a community are gradually able to perceive themselves from others’ per-spectives as they acculturate to the community’s values, concerns, and ways of thinking andinteracting. Thus, the ARG as a community of practice plays a crucial role in mediating stu-dents’ experiences of the global community of computer science research because it affordsthem the means to take up positions of increasing centrality and influence within thatcommunity.

DiscussionThe alumni and graduate student participants provided rich descriptions of the impor-tance of the relationships they had made and skills they had gained through their legiti-mate peripheral participation in ARG practices. They also described the effects of theirparticipation in the ARG on their growth and changes in self-perception as researchers,as well as changes in others’ perceptions of them, within and beyond the ARG. Theyreferred to certain ARG practices, such as critiquing each other’s papers and presentations,as having been crucial in their development of professional and research skills. They alsospoke of the strong group ties and sense of camaraderie as having supported their devel-opment of self-confidence and ability to “hold their own” outside the local group in thelarger computing research community. What was probably less obvious to these studentmembers and alumni was the fact that certain structures and practices of ARGs that sup-ported their learning and the development of such a cohesive community had been delib-erately designed into the model to do so.


Using theoretical constructs of situated learning theory, this section explains how aspectsof the model’s design lead to positive results for participants in research groups that fullyembrace it. Two aspects of the theory map particularly well to features of the ARG modeland help to explain ARG members’ perceptions of success: (1) the definition of a commu-nity of practice and (2) the notion of legitimate peripheral participation, which describesthe relationship of individual learners to the group and explains their development in termsof gradually increasing responsibilities and shifting participation vis-�a-vis the group’s activ-ities. We take up each aspect in turn. First, we describe ARG structures and practices thatcreate and build community, maintain group cohesiveness, and foster connections tobroader computer science academic and professional communities, all aspects that corre-spond to the definition of a community of practice. Second, we analyze ARG participationstructures that define intragroup relations and support individual students’ membership andsocialization within the group as legitimate participants in the local ARG, as well as thebroader discipline of computer science. Finally, we reflect on several crucial elements of theARG model that are not explained by situated learning theory, nor prefigured in the notionof communities of practice.

ARG Community-Building Structures and PracticesThat the alumni and graduate students perceived themselves to have been active membersof a research community formed around a shared purpose is evident from comments suchas those of Maggie and Leticia. In fact, many of the day-to-day practices and proceduresof an ARG could be said to contribute to its continual development and redevelopmentas a community, in particular the orientation, group meetings, and workshops.

ARG project management activities mirror best management practices for team proj-ects and, as a result, these activities contribute to community building and cohesiveness byensuring that individual members are aware of the group’s goals, the scope of the project,and the importance of their respective contributions toward achieving the goals. Indeed,ARG practices and procedures exemplify many of the elements of the community of prac-tice framework. Table 2 enumerates the elements of communities of practice and relatesthem to an ARG.

Structures to Support Membership and SocializationMany of the ARG practices described above are designed to build a cohesive local researchcommunity, resulting in the socialization or enculturation of novice members into the groupas legitimate peripheral participants (Lave & Wenger, 1991). Certainly one of the mainfunctions of the orientation is to begin the process of assimilation of new students to thegroup, and the definition of project goals and deliverables provides both new and experi-enced members with a clear outline of the group’s work and their role in it. For new mem-bers, having a defined role helps to motivate and legitimate their participation in the group.

Over time, as individual members are initiated and oriented into a new ARG, the groupbegins to achieve a level of cohesiveness and cooperation that supports the achievement ofits goals, and the group begins to exhibit the characteristics of a community of practice.For ARGs these purposes include the development and acculturation of student membersinto the broader research community. Several types of day-to-day ARG practices are worthhighlighting for the way that they facilitate the socialization of new members to the groupand support them on a trajectory toward more central participation in the local group aswell as toward entrance into the broader research community. As described above, in


regular group meetings, the group periodically engages in a structured activity designed topractice some aspect of students’ research, communication, and team skills. For example,mentors and more-experienced students model questioning and providing constructive cri-tique for newer student members, who later observe and critique other group members’presentations before making ones of their own. Students come to value such critique veryhighly – as evidenced by Felix’s remarks about his friend Ignacio’s reviews of his presenta-tions – and the practices become so engrained within the community that students rou-tinely seek and receive reviews from at least several other members before sharing theirwork with the whole group.

The cooperative learning framework on which ARGs are based supports the socializa-tion of members to the local community, the groups’ explicit and continual focus on pro-cess improvement, and the way the groups manage conflict. The ARG model structuresinto the day-to-day operations of the group interdependence and individual accountabilityfor all project tasks and goals. Each member knows which tasks have been assigned to himor her and how these tasks support overall project goals. Even the most novice membersmay be called upon in a group meeting as the local expert on the topic or problem of theirassigned tasks and asked to explain the issue to the group. Subgroups comprising under-graduate and graduate student members may be formed to collaborate on specific tasks.Through frequent structured group meetings, ARG members make time to reflect on anddiscuss how the group is progressing toward its goals and to address any problems thatmay have arisen. Mentors may ask students to reflect on how well they are functioning as

Table 2 Mapping of Elements of a Community of Practice

to an Affinity Research Group (Lave & Wenger, 1991)

Key elements of communities of practiceActualization of key community of practice

elements in affinity research groups

Have an implicit “shared” purpose Have an explicit “core” purpose

Are realized through the social interactionamong learners and experts and their partici-pation in and enactment of the community’spractices

Are realized through deliberately designed activitiesand a cooperative team framework that support skillsdevelopment, participation, and social interactionamong student researchers and faculty mentors

Provide learners situated opportunities to learnby engaging in the community’s practices

Deliberately structure situations in which studentresearchers practice skills and provide situated oppor-tunities to learn, observe, and reflect through experi-ence, e.g., the practice of asking probing questionsand then applying the skill at regular meetings andseminars

Produce and transform participants’ identities(becoming part of the community and belongingto it)

Produce and transform participants’ identities asresearchers when students conduct research, collabo-rate, and receive critical review of deliverables

Provide learners opportunities to participatelegitimately and peripherally in the commun-ity’s practices and have access to its resourcesand expertise

Provide learners opportunities to interact with moresenior researchers and visiting scientists through groupmeetings, seminars, poster presentations, and partici-pation at conferences; faculty mentors legitimize andmediate development as students become researchers;learn and practice skills at workshops


a group. Such ongoing reflection on process helps to address potential conflicts amonggroup members or other problems in the group’s work before they become acute.

Explanatory Limits of the TheoryWhile situated learning theory and the notion of communities of practice provide apowerful lens through which to examine the ARG model and to explain its apparenteffectiveness at creating cohesive groups and developing students’ skills and identities asresearchers, there are, as with any theory, limitations to its explanatory power. In this sec-tion we outline those features of the ARG model that do not seem to be illuminated bysituated learning theory or the notion of communities of practice.

First, with regard to the recruitment of new ARG members, as we have describedabove, there is an explicit emphasis on identifying students who display inherent compe-tency, but who may not be exemplary students as measured by class standing or GPA.Moreover, the founders of the ARG model hold a philosophical belief in the value ofexpanding participation to include students who typically are not involved in research. Nosuch goals for building diversity into local or global communities are described in thefoundational literature on communities of practice. While Lave and Wenger (1991) dis-cuss some issues of access to community resources and distribution of power within com-munities, they are silent on the mechanisms by which new members self-select, arerecruited, or initially join communities of practice. In later work, Lave (2008) acknowl-edged this lack of focus on power and the political, institutional, and social factors thatshape which individuals are typically given opportunities for legitimate peripheral partici-pation. By including recruitment practices that focus on developing students who do notinitially fit the traditional mold for high-quality research students, ARG mentors chal-lenge what Lave and Wenger (1991) might call “old timers’ knowledgeabilities,” or theways in which computing research is typically carried out.

Second, although the focus on practices that develop students’ research, teaming, andcommunication skills in ARGs appears to support their socialization and legitimate periph-eral participation in the group, the deliberateness with which the ARG model has incorpo-rated such practices seems to run somewhat counter to the way that learning typically occursin the apprenticeship situations described in Lave and Wenger (1991), where learning is dis-cussed in terms of immersion in the situated practices of the group. The role of explicitinstruction in learning is downplayed in situated learning theory. While ARG members cer-tainly are immersed in situated group practices around research, the periodic, explicit focusin group meetings on skill building may be one of the reasons why the model has beeneffective in providing access to global research communities for groups of students who havebeen traditionally underrepresented in scientific and technological research. Several ARGmembers credited their participation in research group activities with their understandingand mastering of skills needed to conduct research and scholarship within and beyond thegroup. Given that many traditional research groups assume members come to the groupalready possessing such skills and knowledge, we believe explicit skill building may be a cru-cial and defining aspect of the ARG model. Yet in its quintessential forms as a model oflearning through apprenticeship and immersion in practice, the communities of practice con-cept does not offer any substantial insights into the potential role of explicit instruction inthe ARG model.

Third, while the tenets of cooperative learning upon which the ARG model is founded,such as fostering interdependence and individual accountability, also seem to support learners’


socialization into the local community’s practices and their sense of belonging to the group, sit-uated learning theory does not suggest that a cooperative environment is necessary for learningto occur. Indeed, as outlined in Lave and Wenger (1991), the communities of practice model islargely silent about issues of competition and cooperation among community members andtheir effects on learning. We note the rejection of the teacher–student dichotomy and the men-tion of newcomers as potential resources for learning that suggest collaboration and coopera-tion as influential for community development (Lave, 2008); however, the original modeladdressed these ideas only obliquely through discussion of access to the groups’ activities, toolsand artifacts, and expert members. While Lave and Wenger (1991) acknowledge that lack ofaccess to such community resources can hinder learning, the communities of practice modeloffers little in a way of a prescription for ensuring such access. The ARG model’s founders, onthe other hand, believe that fostering cooperation within the group is essential to providingaccess to local and global community practices, creating the conditions for a healthy learningenvironment, and promoting the prosperity and longevity of the local group.

Finally, the ARG model emphasizes building expertise and trust across all members of thegroup, regardless of individuals’ levels of seniority within the group. It could be said that one ofthe ways that the ARG model builds legitimacy into novice members’ participation is throughexpecting them to become experts in limited but significant portions of the group’s researchproject. As their longevity and expertise in the group increases, members cross-train on eachother’s areas of expertise in order to expand participants’ expertise and to ensure the group’scontinuation as members graduate and leave the group. Such distribution of knowledge andexpertise across group members creates a relatively flat group hierarchy in which mentors andother senior group members often need to rely on the expertise of more junior members tocomplete research tasks, and all members’ expertise is valued no matter their age, gender,degree status, or seniority within the group. While the notion of the distribution of knowledgeand cognition has long been elaborated within situated learning and situated cognition theories(see, e.g., Brown, Collins, & Duguid, 1989; Palinscar & Brown, 1985; Herrenkohl, Palinscar,DeWater, & Kawasaki, 1999; Rogoff, 1995), the mechanisms by which such interdependencedevelops among members of a community of practice or relatively flat organizational hierar-chies are not theorized. Rather, their existence is largely taken for granted as endemic to thesituated learning process. The ARG model, by contrast, relies explicitly on cooperative learn-ing practices to foster the building of expertise and trust across participants.

ConclusionTo summarize, we take up each of our research questions in turn. First, the participantscredited their experiences in the ARG with having had a profound influence on their pro-fessional roles and identities, and they provided numerous examples and anecdotes toillustrate how deeply formative their experiences were. Participants described the researchgroup as having become a focal space for all their academic and social activities. As aresult, they developed deep commitment to the work and to each other’s development andsuccess. For many alumni, these bonds have continued several years beyond graduation,and they also invariably described themselves as having developed self-confidence andskills that afforded them mobility in the job market as well as the ability to hit theground running and quickly distinguish themselves from their peers on the job. Theyreadily traced these gains back to specific ARG practices. Current ARG participants men-tioned having gained skills that supported them in their coursework, and referred directly


to the influence of the ARG on their senses of self in relation to research and academics.Several specifically mentioned the invitation to join the ARG as marking a turning pointin their academic lives. Prior to joining the ARG, they had been disengaged from aca-demics and unsure of their own skills and abilities regarding research, but as a result ofthe ARG had developed a deep interest in their discipline and research, and had come tosee themselves as smart, capable, and academically successful.

Regarding our second question, we found that, although all of the participants could referto specific ARG practices that helped form their identities and shape their experiences, theyhad varying levels of awareness of the details of the ARG model. The longer their participationin the ARG, the greater their awareness of the components of the ARG model. This is not sur-prising, given that after a few years in the ARG, participants would have experienced certainpractices several times and could themselves orient and mentor new members.

Finally, our findings indicate that the ARG model supported students to become expertresearchers and facilitated the apprenticeship of students who quite likely would not havebecome involved in undergraduate research in a more traditional model. Furthermore, theparticipants indicate the model’s value for developing the group’s identity as researchers wholearn from one another, engaging students effectively with the larger professional community,and transforming students’ identities into those of competent researchers. The ARG modelthus exemplifies many of the central theoretical tenets of communities of practice.

While situated learning theory and the notion of communities of practice have somelimitations in terms of their explanatory power, these theoretical constructs have enabledus to isolate and describe certain mechanisms by which the ARG model moves such stu-dents from outsider, novice status toward expertise in a field. While many means andmodels exist for providing undergraduates with research experiences, we suggest that theARG model shows promise for influencing the future direction and development ofundergraduate research. This potential aligns with what Dowd, Malcolm, and Bensimon(2009) suggest for supporting Hispanic students to be successful in the sciences: Establisheffective practices and proven exemplars. ARG is such an exemplar.

The ARG model is currently being disseminated beyond computing at the initial insti-tution and in other STEM departments across the country using external funding.Throughout this process, it is important to ensure that students at new institutions areexperiencing similarly positive outcomes and development of researcher identities. Ourqualitative analysis of the long-term impact of ARGs contributes to understanding howARG participants are becoming researchers and assists in honing the model. We continueto follow ARG alumni of the originating institution and more recent adopters of themodel at over 10 institutions. With these efforts, we have begun to engage new researchquestions about the model’s transferability, specifically the mechanisms crucial to its effec-tive adoption at other institutions and to disciplines beyond computing.

AcknowledgmentsWe wish to thank the past ARG participants who contributed their insights into theirexperiences as ARG undergraduate and graduate researchers. We especially wish to thankDrs. Andy Bernat, Sergio Cabrera, Connie Della-Piana, Gabriel Della-Piana, and SteveRoach for their contributions in developing the ARG model framework. Funding for thisresearch was supported in part by grants from the National Science Foundation,DUE-0443061, DUE-0920300, and CNS-0540592.


ReferencesBauer, K. W., & Bennett, J. S. (2003). Alumni perceptions used to assess undergraduate

research experience. Journal of Higher Education, 74(2), 210–230.Bensimon, E. M. (2005). Equality as a fact, equality as a result: A matter of institutional

accountability. Washington, DC: American Council on Education.Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of

learning. Educational Researcher, 18(1), 32–42.Collins, J., & Porras, J. (1994). Built to last: Successful habits of visionary companies. New

York: Harper Business.Committee on Science, Engineering, and Public Policy. (2007). Rising above the gathering

storm: Energizing and employing America for a brighter economic future. Washington,DC: National Academies Press.

Corbin, J. (2009). Taking an analytic journey. In J. M. Morse, P. N. Stern, J. Corbin, B.Bowers, K. Charmaz, & A. E. Clarke (Eds.), Developing grounded theory: The secondgeneration (pp. 35–54). Walnut Creek, CA: Left Coast Press.

Creswell, J. W. (1998). Qualitative inquiry and research design: Choosing among five tradi-tions. Thousand Oaks, CA: Sage.

Creswell, J. W. (2003). Research design: Qualitative, quantitative, and mixed methodsapproaches. Thousand Oaks, CA: Sage.

Creswell, J. W. (2005). Educational research: Planning, conducting and evaluating quantita-tive and qualitative research. Columbus, OH: Pearson.

Denzin, N. (1989). The research act: A theoretical introduction to sociological methods. Engle-wood Cliffs, NJ: Prentice Hall.

Dowd, A. C., Malcom, L. E., & Bensimon, E. M. (2009). Benchmarking the success ofLatino and Latina students in STEM to achieve national graduation goals. LosAngeles, CA: University of Southern California.

Erickson, F. (1986). Qualitative methods in research on teaching (Occasional Paper No. 81).East Lansing, MI: Michigan State University, Institute for Research on Teaching.

Feldman, A., Divoll, K., & Rogan-Klyve, A. (2009). Research education of new scientists:Implications for science teacher education. Journal of Research on Science Teaching,46(4), 442–459.

Gates, A. Q., Roach, S., Villa, E. Y., Kephart, K., Della-Piana, C., & Della-Piana, G.(2008). The affinity research group model: Creating and maintaining effective researchteams. Los Alamitos, CA: IEEE Computer Society.

Geertz, C. (1973). Thick description: Toward an interpretive theory of culture. In Theinterpretion of cultures: Selected essays (pp. 311–323). New York, NY: Basic Books.

Goetz, J. P., & LeCompte, M. D. (1984) Ethnography and qualitative design in educationalresearch. New York, NY: Academic Press.

Grandy, J. (1998). Persistence in science of high-ability minority students: Results of alongitudinal study. Journal of Higher Education, 69(6), 589–504.

Hathaway, R., Nagda, B., & Gregerman, S. (2002). The relationship of undergraduateresearch participation to graduate and professional educational pursuit: An empiricalstudy. Journal of College Student Development, 43(5), 614–631.

Herrenkohl, L. R., Palincsar, A. S., DeWater, L. S., & Kawasaki, K. (1999). Developingscientific communities in classrooms: A sociocognitive approach. Journal of the LearningSciences, 8(3–4), 451–493.


Holland, D., & Leander, K. (2008). Ethnographic studies of positioning and subjectivity:An introduction. Ethos, 32(2), 127–139.

Holland, D., Lachicotte, W., Skinner, D., & Cain, C. (1998). Identity and agency in cul-tural worlds. Cambridge, MA: Harvard University Press.

Howard, G. S., & Dailey, P. R. (1979). Response-shift bias: A source of contaminationin self-report measures. Journal of Applied Psychology, 64(2), 144–150.

Hunter, A.-B., Laursen, S. L., & Seymour, E. (2007). Becoming a scientist: The role ofundergraduate research in students’ cognitive, personal, and professional development.Science Education, 9(1), 36–74.

Jackson, S. E. (1996). The consequences of diversity in multidisciplinary work teams. In M.A. West (Ed.), Handbook of work group psychology (pp. 53–75). Chichester, UK: Wiley.

Janesick, V. J. (2000) The choreography of qualitative research design: Minuets, improv-isations, and crystallization. In N. Denzin and Y. S. Lincoln (Eds.), Handbook of quali-tative research (2nd ed.; pp. 379–400). Thousand Oaks, CA: Sage.

Johnson, D., Johnson, R., & Holubec, E. (1992). Cooperation in the classroom. Edina, MN:Interaction.

Johnson, D., Johnson, R., & Smith, K. A. (1991). Active learning: Cooperation in the col-lege classroom. Edina, MN: Interaction.

Johnson, R., & Johnson, D. (1989). Cooperation and competition: Theory and research.Edina, MN: Interaction.

Jones, M. T., Barlow, A. E., & Villarejo, M. (2010). Importance of undergraduate research forminority persistence and achievement in biology. Journal of Higher Education, 81(1), 82–115.

Kardash, C. M. (2000). Evaluation of an undergraduate research experience: Perceptionsof undergraduate interns and their faculty mentors. Journal of Educational Psychology,92(1), 191–201.

Kephart, K., Villa, E., Gates, A., & Roach, S. (2008). The affinity research group model:Creating and maintaining dynamic, productive and inclusive research groups. CURQuarterly, 28(4), 13–24.

Laursen, S., Hunter, A.-B., Seymour, E., Thiry, H., & Melton, G. (2010). Undergraduateresearch in the sciences: Engaging students in real science. San Francisco, CA: Jossey-Bass.

Lave, J. (1998). Situated learning in communities of practice. In L. Resnick, J. Levine, &S. Teasley (Eds.), Perspectives on socially shared cognition (pp. 63–82). Washington, DC:American Psychological Association.

Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. NewYork, NY: Cambridge University Press.

Lincoln, Y., & Guba, E. (1985). Naturalistic inquiry. Newbury Park, CA: Sage.Merriam, S. B. (2001). Qualitative research and case study applications in education. San

Francisco, CA: Jossey-Bass.Nagda, B. A., Gregerman, S. R., Jonides, J., von Hippel, W., & Lerner, J. S. (1998).

Undergraduate student-faculty research partnerships affect student retention. Review ofHigher Education, 22(1), 55–72.

Palinscar, A., & Brown, A. (1985). Reciprocal teaching: A means to a meaningful end. InJ. Osborn, P. Wilson, & R. C. Anderson (Eds.), Reading education: Foundations for aliterate America (pp. 299–310). Lexington, MA: D. C. Heath.

President’s Council of Advisors on Science and Technology. (2007). Leadership under challenge:Information technology R&D in a competitive world. Washington, DC: The National


Coordination Office (NCO) for Networking and Information Technology Research andDevelopment (NITRD).

Peshkin, A. (2000). The nature of interpretation in qualitative research. EducationalResearcher, 29(9), 5–9.

Rogoff, B. (1995). Observing sociocultural activity on three planes: Participatory appropri-ation, guided participation, and apprenticeship. In J. V. Wertsch, P. del Rio, & A.Alvarez (Eds.), Sociocultural studies of mind (pp. 139–164). Cambridge, UK: CambridgeUniversity Press. Reprinted (2008) in K. Hall & P. Murphy (Eds.), Pedagogy and prac-tice: Culture and identities (pp. 58–74). London: Sage.

Russell, S. H. (2005). Evaluation of NSF support for undergraduate research opportunities:Survey of STEM graduates. Menlo Park, CA: SRI International.

Schwandt, T. A. (2000). Three epistemological stances for qualitative inquiry: Interpretivism,hermeneutics, and social constructionism. In N. K. Denzin & Y. S. Lincoln (Eds.), Hand-book of qualitative research (2nd ed.; pp. 189–213). Thousand Oaks, CA: Sage.

Seymour, E., Hunter, A.-B., Laursen, S. L., & DeAntoni, T. (2004). Establishing thebenefits of research experiences for undergraduates in the sciences: First findings froma three-year study. Science Education, 88(4), 493–534.

Spradley, J. (1980). Participant observation. New York, NY: Holt, Rinehart and Winston.Stevens, R., O’Connor, K., Garrison, L., Jocuns, A., & Amos, D. M. (2008). Becoming

an engineer: Toward a three dimensional view of engineering learning. Journal of Engi-neering Education, 97(3), 355–68.

Teller, P., & Gates, A. (2001). Using the affinity research group model to involve under-graduate students in research. Journal of Engineering Education, 90(4), 549–555.

Thomas, D. R. (2006). A general inductive approach for analyzing qualitative evaluationdata. American Journal of Evaluation, 27, 237–46.

Thiry, H., Laursen, S. L., & Hunter, A.-B. (2011). What experiences help students becomescientists? A comparative study of research and other sources of personal and professionalgains for STEM undergraduates. Journal of Higher Education, 82(4), 357–388.

Ward, C., Bennett, J., & Bauer, K. (2002). Content analysis of undergraduate research stu-dent evaluations. Retrieved from http://www.udel.edu/RAIRE.

AuthorsElsa Q. Villa is a research assistant professor in the College of Engineering at the Univer-

sity of Texas at El Paso, 500 W. University, El Paso, TX, 79968; [email protected].

Kerrie Kephart is a lecturer in the Department of Human Centered Design & Engineering atthe University of Washington, Box 352315, Seattle, WA, 98195; [email protected].

Ann Q. Gates is a professor and Chair of Computer Science in the College of Engineer-ing at the University of Texas at El Paso, 500 W. University, El Paso, TX; 79968,[email protected].

Heather Thiry is a research associate in ethnography and evaluation research at the Uni-versity of Colorado Boulder, 580 UCB, Boulder, CO, 80309; [email protected].

Sarah Hug is a research associate in the ATLAS Assessment and Research Center at theUniversity of Colorado Boulder, 1125 18th St., Boulder, Colorado, 80309; [email protected].


http://www.udel.edu/RAIRE

Affinity Research Groups in Practice: Apprenticing Students in Research

Documents

Transcript of Affinity Research Groups in Practice: Apprenticing Students in Research