Confronting Analytical Dilemmas for Understanding Complex Human Interactions in Design-Based Research From a Cultural—Historical Activity Theory (CHAT) Framework

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Confronting AnalyticalDilemmas for UnderstandingComplex Human Interactionsin Design-Based Research Froma Cultural—Historical ActivityTheory (CHAT) FrameworkLisa C. Yamagata-Lynch aa Department of Educational Technology, Researchand Assessment , Northern Illinois University , DeKalbPublished online: 05 Dec 2007.

To cite this article: Lisa C. Yamagata-Lynch (2007) Confronting Analytical Dilemmasfor Understanding Complex Human Interactions in Design-Based Research From aCultural—Historical Activity Theory (CHAT) Framework, Journal of the LearningSciences, 16:4, 451-484, DOI: 10.1080/10508400701524777

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Confronting Analytical Dilemmasfor Understanding Complex Human

Interactions in Design-Based ResearchFrom a Cultural–Historical Activity

Theory (CHAT) Framework

Lisa C. Yamagata-LynchDepartment of Educational Technology, Research and Assessment

Northern Illinois University, De Kalb

Understanding human activity in real-world situations often involves complicateddata collection, analysis, and presentation methods. This article discusses how Cul-tural-Historical Activity Theory (CHAT) can inform design-based research practicesthat focus on understanding activity in real-world situations. I provide a sample dataset with activity systems analyses of a yearlong teacher professional developmentprogram designed to foster technology integration into rural Indiana schools. I pres-ent the analytical dilemmas I faced while maintaining trustworthiness in the qualita-tive data analysis. Through the sample data analysis, I demonstrate how the school-wide technology reform initiative affected and was affected by classroom-basedteacher technology implementation projects. Additionally, I introduce the theoreticalfindings from the data analyses that contribute to further development in activity sys-tems analysis.

Understanding human activity in real-world situations often involves compli-cated data collection, analysis, and presentation methods. Therefore, making cred-ible systemic inferences and drawing coherent theoretical implications from thesedata sets is often challenging. Activity systems analysis, developed by Engeström

THE JOURNAL OF THE LEARNING SCIENCES, 16(4), 451–484Copyright © 2007, Lawrence Erlbaum Associates, Inc.

Correspondence should be addressed to Lisa C. Yamagata-Lynch, Department of EducationalTechnology, Research and Assessment, Northern Illinois University, DeKalb, IL 60115. E-mail:[email protected]

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(1987), is one method that can provide guidance to researchers when analyzingand presenting complicated qualitative data sets.

The purpose of this article is to introduce the use of activity systems analysisin design-based research. I begin with an overview of the theoretical origins of ac-tivity systems analysis within the context of cultural–historical activity theory(CHAT). Then I present a sample data set of a year-long teacher professional de-velopment program designed to foster technology integration into rural schools. Inthe sample data analysis, I address the following research question: How doteacher technology integration activities and professional development activitiesaffect one another within a school district? I also provide an activity systems analy-sis of the sample data set.

After presenting the data analysis, I examine the strengths and weaknesses ofactivity systems analysis. I discuss the analytical dilemmas I had to address whileusing this data analysis technique. These dilemmas included (a) defining activitysettings from a rich data set, (b) drawing human activities as series of activity sys-tems, and (c) identifying tensions within single units of activity from networks ofactivity. I conclude by arguing that when researchers develop data analysis meth-ods that accommodate real-world learning contexts, they need to share analyticaldilemmas they confronted and how they addressed those dilemmas. This will ulti-mately help to identify new research methods that address complicated real-worlddata sets.

ADDRESSING CHALLENGES THAT LEARNINGSCIENTISTS FIND IN DESIGN-BASED RESEARCH

Learning scientists conduct empirical studies to explain how educational innova-tions work in messy real-world situations (Barab & Squire, 2004; Cobb, Confrey,diSessa, Lehrer, & Schauble, 2003; Design-Based Researcher Collective, 2003). Inthis process learning scientists often conduct design-based research to explain howthe observations from the field inform both theory and practice (Brown, 1992; Col-lins, 1992; Joseph, 2004). Unfortunately, design-based research often becomesproblematic because data collection, analysis, and presentation methods inevitablyinvolve complicated procedures (Collins, Joseph, & Bielaczyc, 2004; Hoadley,2004).

Many researchers who conduct design-based research struggle with those pro-cedures (Schoenfeld, 1992). They find it challenging to manage the overwhelmingamount of information generated (Collins et al., 2004) while coordinating multiplelevels of necessary analyses (Cobb et al., 2003). This problem is difficult to solvebecause conventional data analysis methods do not adequately address design-based research, and there is no agreed-upon method for evaluating such data(Brown, 1992). As a result, new data analysis methods have often been limited to

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studies that take place in single classrooms. Furthermore, the findings from thesestudies often do not systematically address pressing school-wide issues in kinder-garten through Grade 12 settings (Fishman, Marx, Blumenfeld, Krajcik, & Solo-way, 2004) and do not adequately add value to theory development (Barab &Squire, 2004; Collins et al., 2004; diSessa & Cobb, 2004).

Activity systems analysis has the potential to provide some solutions for man-aging complex qualitative design-based research data sets. This analysis method isdesigned to be used to understand human activity situated in a collective context(Engeström, 1987; Kaptelinin, 2005) through a series of triangle diagrams. Al-though it cannot solve all challenges in design-based research, it can provide aninitial framework for making sense of complex data sets to find systematic impli-cations that inform both theory and practice.

In my work, the persistent use of activity systems analysis has helped me toaddress some of the overwhelming nature of complicated data sets and to isolatemethods for managing them. I have used activity systems analysis as a tool todevelop (a) a common vocabulary to compare complex learning situations, (b) anew method for capturing complex data sets, and (c) systemic implications fromresearch results. These experiences have provided me with strategies for how toanalyze and present real-world data sets while addressing issues of trustworthi-ness.

For example, I used activity systems analysis to conduct a qualitative study andgain a historical understanding of interactions that took place between selectedteacher activities within a school district and a technology professional develop-ment program (Yamagata-Lynch, 2003b). Over a 2-year period, I analyzed the ac-tivities of the program, participating teachers, and nonparticipating teachers thatled to changes in classroom- and district-level technology integration practices. Ipresented the changes that occurred in teacher activities surrounding technologyintegration in a series of four activity system diagrams.

The main struggle I confronted in that study was how to organize individual ac-tivity systems in a trustworthy and nonarbitrary manner. The activity systems dia-grams I drew were derived from traditional naturalistic research methods followingstrategies for maintaining trustworthiness. When I began to draw the diagrams, I re-alized that the real-world context was far more complicated than the triangle repre-sentations I was drawing. As a result, I became unsure of how to select which perti-nent contextual information to include in the individual diagrams while maintaininga trustworthy interpretation and presentation of the changes that had occurred inteacher activities.

I addressed this struggle by affirming that my role as a researcher was to presentthe participants’ worldview of the context. In order to identify the contextual ele-ments in the activity systems analysis, I included the recurring themes in the dataset that participants reported as having affected their technology integration activi-

CHAT ANALYTICAL DILEMMAS IN DESIGN-BASED RESEARCH 453

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ties. Additionally, once I drew the series of diagrams representing historical epi-sodes, I presented them to participants for member-checking purposes and gainedtheir input for revisions.

CHAT BACKGROUND

In the early 1920s, Vygotsky attempted to reformulate psychology based onMarxian theory to overcome the dichotomous analysis of the organism and the en-vironment (Kozulin, 1990; Luria, 1979). Vygotsky adapted Marx’s political theoryregarding collective exchanges and material production to capture the coevo-lutionary process individuals encounter in their environment while learning to en-gage in shared activities (Stetsenko, 2005). Vygotsky described this process as me-diated action, in which he did not treat the organism and the environment asmutually exclusive entities.

Vygotsky explained mediated action as a semiotic process between sub-ject/individuals, mediating artifact/tools, and the object/goal of an activity(Wertsch, Tulviste, & Hagstrom, 1993). This process guides and influences theway individuals make meaning of the world, and it has been identified as the ba-sic structure for mediated action as shown in Figure 1 (Cole, 1996; Cole &Engeström, 1993). In mediated action the subject, object, and tool have a dialec-tical relationship whereby they can affect one another and the entire activity(Stetsenko, 2005).

Activity theory itself was originally developed by S. L. Rubinshtein, independ-ent of Vygotksy’s work, as a philosophical and psychological theory during theearly 20th century (Brushlinskii, 2004). Post-Vygotskian CHAT theorists such asA. N. Leontiev, P. Ia. Galperin, and V. V. Davydov extended Rubinshtein’s work bytreating activity as a holistic unit of analysis directed by an individual’s or group’sof individuals goals and motives for participating in an activity (Davydov, 1999;Galperin, 1992; Leontiev, 1974). They took Vygotsky’s mediated action as theirbasic framework and continued to contribute to the theoretical development of ac-tivity theory.

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FIGURE 1 Vygotsky’s Basic Mediation Triangle, adapted from Cole (1996).

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Leontiev introduced activity as the unit of analysis that incorporates bothhuman behavior and mental processes. He proposed that activity is regulated bythe interaction among subject, object, motivation, action, goals, sociohistoricalcontext, and the consequences of the activity (Davydov, 1999; Galperin, 1992;Lazarev, 2004). Leontiev (1974)1 defined activity as

… a molar and nonadditive unit of a material subject’s life. In a narrower and morepsychological sense, activity is a unit of life mediated by mental reflection whose realfunction is to orient the subject to the world of objects. Activity is thus not a reactionor a totality of reactions, but rather a system possessing structure, inner transforma-tions, conversations, and development. (p. 10)

In other words, from an object-directed activity theoretical perspective learning isexplained as a self-regulated meaning-making process in which individuals orgroups of individuals choose to participate based on their goals and motives. Fur-thermore, the events that occur during the activity and the consequences of the ac-tivity can qualitatively change the participant, his/her object and motives for par-ticipation, the social environment of the activity, and the activity itself (Kaptelinin,2005; Rogoff, 1995).

Due to translation problems, there is a fair amount of philosophical debateamong CHAT theorists regarding Leontiev’s use of the word object. Object hasbeen used interchangeably to refer to the goal of an activity, the motives for par-ticipating in an activity, and material products that participants try to gainthrough an activity. As a result, the meaning of object-directed activity hasbecome confused (Nardi, 2005). It is important for researchers using activity the-ory as a methodological framework to remember that the object is the reason in-dividuals and groups of individuals choose to participate in an activity (Kap-telinin, 2005), and it is what holds the elements involved in an activity together(Hyysalo, 2005).

Leontiev and his colleagues’ works were focused on the psychological explana-tions for understanding activity. His definition of activity allowed researchers tomove away from the mentalist approaches of understanding human learning and in-stead explain it as series of object-directed activities (Bedny & Harris, 2005;Lazarev, 2004). This provided a theoretical framework of human psychology thatdid not treat the organism and the environment as separate entities (Galperin, 1992;Rozin, 2004).


1Leontiev’s work on defining object-directed activity has been published in English (Leontiev,1974, 1978, 1981). These works are all based on the same work published originally in Russian in 1972in Voprosy filosofii, No. 9, pp. 95–108, and the multiple versions in English indicate that there havebeen several attempts to translate the original work. For this article I used the translation published in1974 in Soviet Psychology.

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However, Leontiev and his colleagues did not adequately address the method-ological challenges for capturing, analyzing, and presenting activity-based data.Engeström (1987) addressed this shortcoming and contributed to the developmentof activity theory as an analytical framework by introducing a descriptive model ofactivity. The result of Engeström’s research was the development of activity sys-tems model, shown in Figure 2 , which can be used in analyses of complex qualita-tive data. This model allows researchers to map complex human interactions thattake place in collective settings.

The top triangle in Figure 2 is identical to Vygotsky’s basic structure of medi-ated action. The rules, community, and division of labor in the bottom portion ofthe triangle model add the sociohistorical collective nature of mediation that wasnot addressed by Vygotsky (Engeström, 1999). Rules are any formal or informalconstructs that in varying degrees constrain or allow activities to occur. Addi-tionally, rules are the procedures and acceptable interactions to engage in withother community members (Engeström, 1993). The community is the social groupto which the subject belongs while engaging in an activity. The division of labor isthe tasks that community members share while the subject is participating in theactivity. The outcome is the results or consequences that the subject finds once theactivity is completed (Engeström, 1993).

The interactions among the components of the triangle model can cause ten-sions that can hamper or assist in the attainment of the object (Cole & Engeström,1993; Engeström, 1987, 1993; Yamagata-Lynch, 2003b). These tensions or distur-bances do not occur accidentally or arbitrarily but instead are inherent in humanactivities (Engeström, 1996). Researchers find tensions in activity systems whenelements from one or more components pull the participants away from fulfillingthe activity purpose. These tensions can encourage the activity to collapse or be-come the reason for change (Engeström, 1993). Therefore, tensions can be a liber-ator or an obstacle to human activity (Yamagata-Lynch, 2003b).

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FIGURE 2 Activity systems, adapted from Engeström (1987).

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Activity Systems Analysis in Practice

Several researchers have used activity systems analysis as a descriptive tool inqualitative data analysis. In these works this method has been used to (a) capturethe processes involved in organizational change (Barab, Schatz, & Scheckler,2004; Engeström, 1993, 2000), (b) identify contradictions and tensions that shapedevelopments in educational settings (Barab, Barnet, Yamagata-Lynch, Squire, &Keating, 2002; Roth & Tobin, 2002), and (c) demonstrate historical developmentsin organizational learning (Yamagata-Lynch, 2003b). These studies have demon-strated how individual or group activities are closely bound by the social contextand how individuals, groups, and the social context shape one another.

For example, Engeström (2000) conducted a qualitative study tracing multi-organizational activities involved in children’s medical care in Helsinki, Finland.Engeström described the turn-taking activities between physicians and specialistswith varying objects while they were trying to diagnose a patient and decide acourse of treatment. He used the findings from the activity systems analysis topoint out the tensions in hospital patient care that resulted in both lack of coordina-tion among physicians and expensive outcomes. He presented the work redesignactivities that the hospital staff engaged in to minimize tensions in patient care.

Roth and Tobin (2002) used activity systems analysis to identify strategies toredesign an urban inner city teacher education program. Through activity systemsanalysis, Roth and Tobin examined ethnographic vignettes of participant experi-ences in a teacher education program and during the first year of teaching at urbaninner city school settings. The authors found that new teachers placed in urban set-tings who completed student teaching in suburban settings experienced over-whelming difficulties because the methods they had become comfortable with insuburban settings were not considered legitimate teaching activities in inner cityschools. These teachers found great difficulty surviving their first year of teachingwhile constantly exploring new methods. Roth and Tobin used the findings fromthe activity systems analysis to identify strategies to redesign the teacher educationprogram at the institutional and classroom level in order to minimize the tensionsthat new teachers encounter.

Barab et al. (2002) used activity systems analysis to capture the moment-to-mo-ment transitions in undergraduate student understanding of astronomy conceptswhile building and engaging with three-dimensional (3-D) virtual models of thesolar system in a participatory learning environment. Barab et al. (2002) presentedseries of student and instructor dialogue that captured various levels of student un-derstanding of astronomical concepts. The authors conducted activity systemsanalyses of these dialogues and demonstrated how students and the instructor usedthe 3-D models as tools to confront tensions in their activities while (a) developingan understanding of astronomical concepts, (b) becoming members of the partici-patory learning environment, and (c) learning how to use the 3-D modeling tool.


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Specifically, they used Engeström’s (1987) characterization to examine the rela-tions of participant (student) and object (3-D models and astronomy understand-ings) and how, in the course, object transformations leading to scientific under-standings were mediated by tools (both technological and human), the overallclassroom microculture (emergent norms), division of labor (group dynamics andstudent–instructor roles), and rules (informal, formal, and technical).

ACTIVITY SYSTEMS DATA ANALYSIS METHODS

The following qualitative data came from a larger study in which I investigated thedevelopments of a year-long university partnership program between Indiana Uni-versity and rural Indiana schools. To retain anonymity the school district has beenassigned a pseudonym and is referred to as the Blackwell School District, and allindividuals mentioned have been assigned a pseudonym as well. The partnershipprogram in this study was the Teacher Institute for Curriculum Knowledge AboutIntegration of Technology (TICKIT). In the sample analysis I examine howteacher technology integration activities and professional development activitiesin TICKIT affected one another and the activities of other pertinent actors withinthe school district.

I was involved in TICKIT both as one of the three staff members who facilitatedthe professional development program and as a researcher. As a researcher I inves-tigated how the activities of individual teachers, groups of teachers, school tech-nology support staff, the school district, and TICKIT interacted with one anotherin the school-wide technology curriculum integration process. I collected data us-ing naturalistic inquiry techniques (Lincoln & Guba, 1985) including documentanalysis, semistructured interviews, classroom observations, and individual orgroup exit interviews. I then used NUD*IST 4.0 to conduct a thematic analysis ofthe qualitative data sets.

Identifying activity systems that emerged from qualitative data required me toengage in a reflective process in which I drafted and redrafted possible trianglemodels. My reflections did not follow a clean step-by-step process. In most cases Ihad to synthesize the information each participant shared with me before I couldunderstand the collective nature of their activities. Similar to in Miettinen’s (2005)report, individual participants were not always aware of the collective nature oftheir activities. Therefore, as my data analysis progressed I had to modify thedrafts of activity systems based on new information shared by each participant.

In this iterative data analysis process, I began by identifying how the informa-tion from the qualitative data fit into the activity systems model. In most cases Iidentified the subject first and went back to the data set to identify the object andother components in the activity systems. I chose this approach because I was ask-ing questions of participants or observing participant activities, so my data were all

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subject centered. Once I identified the relationship between the subject and object,I mapped out the tools, rules, community, division of labor, and tensions that af-fected the nature of the activity in relation to the subject’s effort to attain the object.There were instances in which I modified the subject and object relationship Idrafted because as I got deeper into the data analysis I developed a greater appreci-ation of my participants’ worldviews and gained a better understanding of the ac-tivities in which they were engaged. I repeated the above process for every activitysystem in the study and then examined how each activity affected one another.

This process raised questions regarding the activity systems model itself andmade me revisit the theoretical literature to test the robustness of the trianglemodel. There were instances in this process when I had to enhance the model sothat it could reflect what I observed from the TICKIT data set. Therefore, in mydata analysis I engaged in a reflective process examining both the data and how thedata informed the development of the theoretical model itself.

For example, as I progressed in the data analysis it became very difficult tomanage the simultaneous cycles of activities that were initiated by multiple indi-viduals directed toward similar objects. In these situations I relied on Rogoff”s(1995) three planes of CHAT analyses to unpack the unit of analysis associatedwith the subject. Her theory consists of personal, interpersonal, and institu-tional/community planes of analyses. She recommended that researchers zoominto one plane of analysis at a time to avoid losing focus. I used this technique toidentify activities initiated by individual teachers or groups of teachers with a com-mon object, and policy-driven school district activities. In this process I modifiedEngeström’s original conception of the subject and used a broader definition to in-clude nonhuman entities that research participants reported had initiated activitiesthat influenced their individual and group activities. This procedure enabled me totease out the relationships between multiple activities initiated by various subjectswith common objects.

Additionally, I found that the activity systems model alone did not capture howthe activities I analyzed fit into the general context in which participants were situ-ated. In the historical analysis I conducted in Yamagata-Lynch (2003b), I intro-duced the bare contextual elements in the activity systems that participants re-ported had affected their individual and group technology integration activities.Since that study, I have come to realize that even though activity systems can beidentified as isolated units of activities, those units exist within the broader,real-world context, which had to be reported in my analysis to report systemic im-plications.

I used the concept of activity settings to address this shortcoming and also toavoid being trapped in what Barab and Squire (2004) referred to as “over–theoriz-ing the context” (p. 12). Activity settings are environments that situate individualactivities in relation to other activities with similar goals (Gallimore & Tharp,1990; Tharp & Gallimore, 1998). I used this concept to place participant technol-


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ogy integration activities within a bounded context of daily teaching activities.Therefore, I still encapsulated the context within a bounded system, but I broad-ened it beyond the triangle diagram unit to provide other researchers with furthercontextual data. I identified the activity setting by piecing together the contextualinformation I found in the qualitative thematic analysis of participant interviewsand reflective papers that had affected their daily teaching activities.

SAMPLE DATA SET: HUMAN ACTIVITIES AT THEBLACKWELL SCHOOL DISTRICT

The sample data were from the Blackwell School District, which was one of thedistricts involved in TICKIT from 1998 to 2001. The school district serves fourschools that include one elementary school, one intermediate school, one middleschool, and one high school. It is located in a rural midwestern farming area, andthere are no large businesses or manufacturing plants nearby. The school district isisolated from resources that could be available in urban settings, such as a public li-brary, museums, and cultural centers.

Prior to the school district enrolling in TICKIT, there were several self-moti-vated, enthusiastic teachers at Blackwell who were experimenting with the use oftechnology in their classrooms. These teachers were interested in integrating tech-nology into their teaching. They were very motivated to continue their professionaldevelopment and learn about new teaching methods that would help their students.

These teachers worked on their technology integration projects with extremelylimited software and hardware resources. Additionally, they had to juggle compet-ing responsibilities from the school district to meet state-mandated curricular stan-dards, use required curriculum packages, and provide remediation programs forstudents in need. As a result, there was a mixture of successful and unsuccessfulteacher technology projects. There were lessons that met curricular goals and thatteachers were very satisfied with, and there were instances when teachers got stucktroubleshooting the technology and were not able to deliver their intended lesson.

While the self-motivated teachers worked on their technology integration pro-jects, administrators at Blackwell, independent of these activities, decided to prior-itize school-wide technology curriculum integration. The district applied for anIndiana High Tech school grant that was subsequently awarded during the1998–1999 school year. As a first step to support district technology integration,administrators hired Andrew as the new technology coordinator. They chargedAndrew with using the money from the state grant to develop a strong technologyinfrastructure in the schools and to provide teachers with a technology profes-sional development program.

During the first year in his position, Andrew focused on providing teachers withsound technology infrastructure. Andrew had future plans for developing an

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in-house technology professional development program. However, for the firstyear he identified five teachers whom he could trust to become technology leadersfor the district and enrolled them in TICKIT. Many of these TICKIT teachers werethe previously identified self-motivated teachers. Andrew used the opportunitiesfrom TICKIT to align what were initially disconnected activities with similar goalsinitiated separately and independently by individual teachers and the school district.

Andrew made special efforts to meet the individual technology needs ofTICKIT teachers with the assumption that these teachers would later assist intraining other teachers in the district. Therefore, TICKIT teachers were explicitlynotified that the school district would provide monetary and technical support forthem. In return, they were expected to take leadership roles for school-wide tech-nology implementation. The five Blackwell TICKIT teachers were provided withvarious types of support for completing their projects. These supports included (a)Internet access in their classrooms, (b) release time for ongoing TICKIT work-shops and the Indiana Computer Educators conference, (c) technical support fromthe technology staff, and (d) opportunities to share teaching-related ideas and sto-ries with other teachers in TICKIT workshops.

However, teachers still experienced frustrating moments related to technologywhile participating in TICKIT. For example, Samantha, a first-grade teacher, haddifficulties implementing her multimedia autobiography project using Hyper-Studio. She commented in her project reflection paper that as she started her pro-ject she quickly learned that understanding the nature of hypermedia environmentswas too complicated for her students. Additionally, equipment such as digital cam-eras and scanners, which she needed in the classroom for her project, were notavailable in her building. Consequently, her access to necessary equipment waslimited to short periods during nonschool days. These difficulties were exacer-bated by the fact that she had set the goals of her project too high for herself as ateacher and for her first-grade students. To Samantha’s surprise, when she com-pleted her project she was extremely happy with her students’ work.

Many TICKIT participants shared Samantha’s sentiment. During teacher inter-views they revealed that by completing TICKIT projects and overcoming frustrat-ing moments with technology it was more likely that they would integrate technol-ogy into their future classrooms. Teachers commented that they were now aware oflocal and university support that was available to them for future technology inte-gration efforts. Teachers further expressed that not only were they comfortablewith technology applications, but that after TICKIT their confidence was boostedto stay motivated to use technology in their teaching. Additionally, teachers re-ported that they had gained a new sense of respect from their colleagues becausethe technology integration projects they had completed during the school yearwere within the context of a university professional development program.

Confidence building was important not only for classroom teachers but for theschool district as well. Andrew commented that teacher accomplishments from


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TICKIT resulted in increased school district confidence. Andrew referred to this as“confidence from the top on down.” This type of administrative confidence hadrippling effects on classroom teachers, because once the Blackwell school boardwas confident in its teachers it became more willing to spend more money towardtechnology school reform, and it decided to support teachers with more software,hardware, and professional development release time.

SAMPLE ACTIVITY SYSTEMS ANALYSIS

At Blackwell there were five distinct activity systems before, during, and afterTICKIT that describe and help explain the development of activities related totechnology curriculum integration and how teacher activities, school administratoractivities, school district activities and TICKIT activities interacted with one an-other. Table 1 summarizes Activity Systems A through E in Figures 3 to 7. The fiveactivity systems are discussed in chronological order and include (a) beforeTICKIT and before technology coordinator teacher activity, (b) before TICKIT

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TABLE 1Pertinent Activity Systems With Corresponding Planes of Analysis

Activity System Plane of Analysis

Activity System ABefore TICKIT and before technology coordinator teacher activityTeachers work individually with limited technology resources and

unsatisfactory results

Individual

Activity System BBefore TICKIT and before technology coordinator Blackwell School

District activitySchool district decides to approach the school technology implementation

plan by hiring a new technology coordinator and by supportingenthusiastic teachers

Institutional

Activity System CBefore TICKIT technology coordinator activityTechnology coordinator begins building solid infrastructure to support

teacher use of technology and enrolls teachers in TICKIT by aligningActivity Systems A and B

Individual

Activity System DDuring TICKIT teacher activityTeachers work collaboratively with new resources and expectations and

gain satisfying results

Interindividual

Activity System EAfter TICKIT Blackwell School District activityAdministrators decide to continue supporting school technology reform

Institutional

Note: TICKIT = Teacher Institute for Curriculum Knowledge About Integration of Technology.

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FIGURE 3 Activity System A: Before Teacher Institute for Curriculum Knowledge About Integra-tion of Technology program and before technology coordinator teacher activity.

FIGURE 4 Activity System B: Before Teacher Institute for Curriculum Knowledge About Integra-tion of Technology Blackwell School District activity.

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FIGURE 5 Activity System C: Before TICKIT technology coordinator activity. TICKIT = TeacherInstitute for Curriculum Knowledge About Integration of Technology.

FIGURE 6 Activity System D: During TICKIT teacher activity. TICKIT = Teacher Institute for Cur-riculum Knowledge About Integration of Technology.

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and before technology coordinator Blackwell School District activity, (c) beforeTICKIT technology coordinator activity, (d) during TICKIT teacher activity, and(e) after TICKIT Blackwell School District activity. These activities involved allthree planes of analyses and affected one another.

Activity System A: Before TICKIT and Before TechnologyCoordinator Teacher Activity

Activity System A in Figure 3 captures the teaching-related activity in which ahandful of self-motivated teachers at Blackwell individually chose to engage.Here, the subject is a group of self-selected enthusiastic teachers in the individualplane of analysis working to attain the object of integrating technology into thecurriculum. These teachers worked alone for the most part and were willing to ex-periment with technology because they saw its potential as a motivational tool forstudents.

Unfortunately, because technology integration was not a shared object in theschool building or the school district, there were extremely limited resources andrules that supported and guided these teachers. There were no district-level poli-cies or procedures in place regarding technology integration initiatives. The scarceresources are captured in the tool component, which included unstable technology,limited time, and limited funds. The rules included self-generated goals and dailyteaching responsibilities. The self-generated goals pertained to the goals that


FIGURE 7 Activity System E: After TICKIT school district activity. TICKIT = Teacher Institute forCurriculum Knowledge About Integration of Technology.

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teachers set for themselves regarding how they wanted to use technology in theclassroom and what types of results they were anticipating from student perfor-mances. The daily teaching responsibilities included individual responsibilities forstudents in the classroom and responsibilities teachers had to fulfill to meet thestate-mandated curriculum.

The community and division of labor affecting teachers in Activity System Adid not exist at this time. Teachers worked individually and did not share rules withother teachers in their building or the school district. Therefore, the self-selectedteachers did not have a community with which to share technology-related respon-sibilities.

The conditions of this activity brought about four tensions. These tensions in-cluded (a) sustaining enthusiasm while working with a lack of resources, (b) sus-taining enthusiasm with unstable project results, (c) actualizing self-generatedgoals and balancing competing responsibilities, and (d) sustaining enthusiasmwhile working with a lack of shared vision. These tensions created difficult situa-tions in the teachers’ everyday activities while the educators attempted to integratetechnology into the curriculum. These situations did not help the teachers in theirtechnology integration goals, and at times teachers had to give up their goals whenother teaching responsibilities took priority.

The outcome associated with Activity System A was a mixed sense of successand failure. Teachers were very satisfied when their technology projects were suc-cessful and they were able to meet student learning goals. However, it was discour-aging when the technology infrastructure was unreliable. Teachers who main-tained their enthusiasm regardless of these failed attempts were able to take theseexperiences as learning opportunities for their professional development.

Activity System B: Before TICKIT and Before TechnologyCoordinator Blackwell School District Activity

Activity System B in Figure 4 captures the Blackwell School District as the subjectengaged in an activity to attain school-wide technology curriculum integration asthe object. The school district was the subject in this activity because it owned thecollective activity. The tool that supported this activity was the Indiana High Techgrant. The rules that guided this activity included taxpayer expectations, studentperformance standards, and teacher performance standards. This activity was situ-ated in the community of local residents in the Blackwell area, and the division oflabor was defined by specific roles that school district employees were designatedthrough their job assignments.

In the above activity, the district administrators faced a tension between attain-ing the object of school-wide technology curriculum integration while meetingmultiple expectations in the rule component. In order to alleviate this tension, theschool district hired a new technology coordinator, which was the outcome of this

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activity. Andrew, the new technology coordinator, was given the responsibility touse the money from the High Tech grant to prepare a sound technology infrastruc-ture and provide professional development opportunities to teachers. This districtactivity brought new opportunities and resources for future teacher technology in-tegration activities and alleviated some of the tensions that teachers had confrontedin Activity System A.

Activity System C: Before TICKIT Technology CoordinatorActivity

In Activity System C in Figure 5, Andrew is the subject in the individual planeof analysis. His activity was directed by the object of providing sound technol-ogy infrastructure and professional development to Blackwell teachers. Thetools available to Andrew were district support and the High Tech grant fromActivity System B, and the enthusiastic teachers from Activity System A. How-ever, he did not have access to stable technology equipment or reliable profes-sional development programs. This limitation of resources created tension inAndrew’s activity.

The rules for Andrew’s activity were individual expectations, school district ex-pectations, and guidelines from the state on how to spend the High Tech grantmonies. These rules were shared among the community members, which includeda handful of enthusiastic teachers and the technology support staff. Additionally,the division of labor was shared among himself, the school district, and his tech-nology support staff.

The outcomes of Andrew’s activity included purchasing new and stable tech-nology equipment and enrolling selected teachers in TICKIT. Andrew acted as abroker who aligned the two disconnected activities between the teachers and theschool district. This brokerage activity introduced TICKIT as a new tool for teach-ers in future technology integration activities. He was able to bridge the activitiesthat teachers had participated in as part of Activity System A and the policy deci-sions that the school district had made to support school technology reform in Ac-tivity System B.

Activity System D: During TICKIT Teacher Activity

In Activity System D in Figure 6, the subject is the TICKIT participants fromBlackwell on the interindividual plane of analysis. Through TICKIT activities,these teachers worked jointly toward the object of integrating technology into thecurriculum. They had access to new resources, rules, and a group of colleagues thatchanged the dynamic of their technology integration activities. The tools availableto them included software and hardware support, release time, TICKIT staff sup-port, and opportunities to share ideas with other TICKIT teachers. Because An-


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drew acted as a broker who found TICKIT as a tool that the school district couldprovide to teachers and teachers could take advantage of during their technologyintegration activities, teachers found valuable resources that had not been availableto them before. These resources alleviated some of the tensions in Activity SystemA. The tensions that TICKIT and other school district support helped resolve in-cluded (a) sustaining enthusiasm while working with lack of resources, (b) sustain-ing enthusiasm with unstable project results, and (c) sustaining enthusiasm whileworking with lack of shared vision.

The rules in Activity System D were individual teacher expectations, TICKITexpectations, school district expectations, and daily teaching responsibilities. Dur-ing the interviews teachers commented that these rules brought more work andhardship to their already busy work lives, and there were times that they felt verybitter about all of the expectations they had to meet. However, teachers felt thatwithout the demanding rules from both TICKIT and work they would have notbeen compelled to complete their projects.

The community in Activity System D was TICKIT participants (includingteachers from the same and different school districts), TICKIT staff, and the lo-cal technology support staff at Blackwell. TICKIT teachers from Blackwell nowhad a community that shared a common goal. The division of labor within thiscommunity was shared by the partnership with the university. In this partnership,teachers were responsible for completing their technology projects, the schooldistrict provided necessary equipment support, and TICKIT staff provided tech-nical support.

Even though several of the tensions that teachers had previously confronted inActivity System A were alleviated in Activity System D, teachers still faced thetension of actualizing expectations for integrating technology into the curriculumwhile balancing competing responsibilities in their everyday practice. TICKIT ex-pectations and district expectations for daily teaching responsibilities competedagainst one another for teachers’ attention, energy, and time. Therefore, althoughTICKIT and district support provided teachers with resources for technology inte-gration, the program also complicated teacher activities by introducing newwork-related expectations. In Figure 6 this phenomenon is represented as a circu-lar tension because the elements within the rule component are bringing a tensionto the system.

As an outcome of this activity, teachers gained confidence, skills, credibility,and new communication channels for technology-related issues. These findingswere reflected in Samantha’s experience and in other teacher interview data. Con-fidence and skills helped teachers become local leaders of technology curriculumintegration. Consequently, immediately after TICKIT during the summer, allBlackwell TICKIT teachers facilitated at least one technology workshop as aninservice program for other local teachers. This helped move the school districttechnology reform activities forward.

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Activity System E: After TICKIT Blackwell School DistrictActivity

In Activity System E in Figure 7, the Blackwell School District is the subject onthe institutional plane of analysis. In this activity, the district worked to establishsound educational policies and practices as the object. The tool for this activity wasthe TICKIT teacher program results and the school district confidence, both out-comes from Activity System C. The rules that the school district needed to meet inthis activity were local tax payer expectations, student performance standards, andteacher performance standards. The community that the school district workedwith was the local residents. Finally, the division of labor was designated by indi-vidual job assignments.

In the above activity, the school district still faced a tension while attempting toattain sound educational policies and practices and meet multiple expectations. Asthe outcome of this activity, the school district decided to continue supportingteachers by providing technology equipment and professional development oppor-tunities. Andrew was able to take advantage of this policy decision to continue pur-chasing and maintaining sound technology infrastructure and to enroll another setof teachers in TICKIT during the 2000–2001 academic year.

Changes in the Activity Settings

Two important factors emerged that necessitated recording changes in the activitysettings for Activity Systems A through E. First, the contextual information in theactivity systems analyses represented in the lower portion of the triangle model didnot fully encapsulate the key characteristics of the context in which the researchparticipants engaged in their activities. Second, if readers of my work are to findany systemic implications of the activity systems analysis, they will need more in-formation about that context.

Figure 8 represents the activity setting at Blackwell before and during TICKIT.The qualitative data that support Figure 8 are reported in Yamagata-Lynch(2003a), which is an in-depth qualitative case study. In that study, BlackwellSchool District teachers as well as TICKIT teachers from another school districtreported that they engaged in technology integration within their school contextthat required them to (a) comply with state mandated standards, (b) provide stu-dents with remediation programs, (c) work with unreliable hardware and software,(e) work with a limited amount of time, (f) implement district-mandated curricu-lum packages, (g) accommodate student comprehension skills, and (h) accommo-date student computer skills. The upper portion in Figure 8 represents this activitysetting.

As I continued my analysis of Blackwell TICKIT activities, changes in the ac-tivity setting became evident. After teachers joined TICKIT, their technology inte-


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gration took place in a joint activity setting of school and TICKIT, represented inthe lower portion of Figure 8. I decided to characterize the new activity setting inthis manner because the school activity setting in the upper portion of the figurewas still the context in which most Blackwell teachers continued their work. As re-ported for Activity System D, TICKIT introduced new elements into teacher tech-nology integration activities that helped them overcome several tensions of Activ-ity System A. However, the new opportunities introduced by TICKIT complicated

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FIGURE 8 Teacher activity settings at Blackwell School District before and during TICKIT.TICKIT = Teacher Institute for Curriculum Knowledge About Integration of Technology.

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the participants’ work conditions. The elements that complicated the activity set-ting included (a) meeting new TICKIT expectations, (b) working with technicalsupport staff, (c) taking advantage of release time from the classroom, (d) partici-pating in ongoing workshops, and (e) participating in ongoing online forums to ex-change ideas with other teachers. These elements became new puzzle pieces in theparticipants’ work environment to which they had to respond while engaging intheir daily school-related activities.

DISCUSSION

Programmatic Findings From Activity System Analysis

The activity systems analysis from the overall TICKIT data identified three pro-gram-related findings that influenced subsequent program implementations. Thefirst finding indicated that TICKIT implementation was affected by the way theprogram itself fit into participants’daily teaching activities. When the professionaldevelopment program requirements such as assigned readings and online discus-sion activities were incompatible with participants’ daily teaching activities, par-ticipants often chose not to complete program requirements. Within the Blackwelldata, this finding was highlighted when I examined the changes between ActivitySystems A and D, and the changes that occurred to the activity setting before andduring TICKIT. When the contextual changes overwhelmed the teachers, they of-ten decided to ignore various elements of the TICKIT expectations.

The second finding indicated that individuals within a school district who wereselected by administrators or self-selected as a technology reform leader had an in-fluence on TICKIT activities. For example, in the sample activity systems analysisAndrew was selected by school district administrators to lead the technology re-form process. As shown in Activity System C, although Andrew did not participatein the program, he played a key role by getting teachers to enroll and successfullycomplete TICKIT.

The third finding indicated that TICKIT as a program was likely to assist thedistrict technology reform process when individual and institutional goals and mo-tives for teacher participation were aligned. In the Blackwell data, Activity Sys-tems B, C, and D are initiated by different actors at different planes of analysis;however, they are all well aligned in the sense that the school district’s object wasto promote school-wide technology integration, Andrew’s object was to pro-vide reliable technology infrastructure and professional development programs toteachers, and the teachers’ object was to integrate technology into the curriculum.In other school district data, TICKIT staff found that when teachers were recruitedinto the program by their superintendents against their own will, they were un-likely to complete the program with a satisfactory result.


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Program Reconfigurations

The findings from the activity systems analysis led to programmatic changes inTICKIT during subsequent program iteration cycles. These revisions focused ondesigning TICKIT to better (a) complement teacher work situations; (b) assisttechnology reform leadership development; and (c) align teacher, administrator,and program goals. Additionally, the activity systems analysis reminded TICKITstaff that program initiatives cannot possibly eliminate all tensions or even all as-pects of a single tension that teachers confront while integrating technology intotheir classroom. Therefore, rather than try to eliminate all tensions, program stafffocused on identifying strategies to minimize some aspects of an identified ten-sion.

For example, as a result of my research and other corroborating evidence fromthe program evaluation data, beginning the third year of TICKIT implementationthe program provided school districts with the funds to hire substitute teachers ondays that participants were involved in TICKIT activities. Providing teachers withextra time out of the classroom did not eliminate the difficulties teachers had whileactualizing expectations for integrating technology into the curriculum and bal-ancing competing responsibilities from their job. However, it provided some reliefso that teachers could step out of their classrooms to design and develop their tech-nology integration projects or meet with TICKIT staff at their school to receive in-dividualized assistance for their projects. Further discussion on the overall pro-gram reconfiguration processes appears in Ehman, Bonk, and Yamagata-Lynch(2005).

Methodological Benefits From Activity Systems Analysis forDesign-Based Research

Identifying a meaningful unit of activity. The effective communication ofactivity systems depends on the researcher’s ability to identify distinct and mean-ingful units of object-directed activities. In order to identify these meaningful unitsof activity, I critically examined my research question, what unit effectively ad-dressed that question, and whether the data set itself presented natural breaks.Therefore, I examined the data set to identify units of activities that provided in-sights on how the interaction between teacher technology integration activities andTICKIT activities affected one another. I made a distinction between object-di-rected activities before and after TICKIT, where I found natural historical breaksin the data set, as baseline information for comparing teacher activities.

For example, the research question in this study was the following: How doteacher technology integration activities and professional development activitiesin TICKIT affect one another and activities of other pertinent actors within theBlackwell School District? By examining the research question I decided that it

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was necessary to illustrate technology integration activities that took place atBlackwell before, during, and after TICKIT. Even though I did not want to paint apicture through my data presentation that TICKIT was the sole intervention thathad brought change to teacher activities, I decided that it was necessary to isolatethe above historical time frame in order to adequately address the research ques-tion.

Then I examined the qualitative thematic analysis to identify actors who had in-teracted with teacher technology integration efforts before, during, and afterTICKIT. The activities of these actors became the meaningful units in the activitysystems analysis. These actors were represented by individuals and organizationalentities from multiple planes of analyses that included individual teachers, thetechnology coordinator, groups of teachers, and the school district. Finally, once Idrew Activity Systems A through E, I reexamined the data to make sure that I hadsufficiently addressed the interconnectedness between the activities.

Each activity system I identified in this article enabled me to analyze the com-plex field-based TICKIT data in a manner that was neither overly simplistic nor ex-cessively complicated. I was able to bracket sets of human activities situated intheir context on the basis of qualitative findings. I then used the activity systems asa guide in my analysis in order to contextualize the data narrative. This helped meto avoid becoming overwhelmed by data analysis.

Identifying networks of activity in multiple planes of analyses.After drafting Activity Systems A through E, I found that the series of triangle

diagrams provided a misguided impression that each activity was isolated fromone another. While examining single activity system units, it was very difficult tovisualize the interconnected nature of activities initiated by different actors onmultiple planes of analyses. I drew Figure 9 to address this difficulty.

Each activity system I presented in this study was derived from the research par-ticipants’ points of view of events that had taken place before, during, and afterTICKIT. Activity Systems A through E are continuous static snap shots of eventsand not a real time account of events. Therefore, each diagram alone cannot cap-ture the essence of how activities unfolded while interacting with other activitiesinitiated by several different actors. One of the main goals of this study was to cap-ture and present the interactions between TICKIT activities, teacher activities, andschool district activities, but I found it very challenging to present this interconnec-tedness among the interactions that had taken place in a series of isolated activitysystems.

For example, while examining the Blackwell data set, it became apparent thatActivity Systems A through E were part of a series of activities that had taken placeat different times at different planes of analyses. Each activity was a separate event,yet several of them were dependent on one another. I concluded that activities weredependent on one another when the outcomes of a historically previous activity af-fected the composition of future activities and/or alleviated some of the persistent


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tensions. Additionally, there were activities that were completely independent ofone another, and the outcomes of these activities did not affect any other activitiesat Blackwell. In order to highlight these interdependent and independent relation-ships between Activity Systems A through E, I prepared Figure 9 by examining thequalitative data set and the triangle diagrams I had prepared in the analysis.

The relationships among activity systems in Figure 9 indicate that Andrew’s in-dividual activity in Activity System C and TICKIT participant interindividual ac-tivity in Activity System D were both not likely to happen without the outcomesfrom the Blackwell School District’s institutional activity in Activity System B.Additionally, the institutional activity in Activity System E, whereby the schooldistrict decided to continue its support for technology integration, was dependenton the outcomes of previous activities.

When analyzing the networked activities in Figure 9, it became apparent thatteacher activities in Activity System A had minimal impact on the school district’stechnology integration efforts because they had been independently initiated andwere disconnected from the school-wide initiative. The networks of activities Ipresent in Figure 9 demonstrate how the Blackwell technology reform process wasmaximized by the merger between district and teacher initiatives. More important,

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FIGURE 9 Activities shared over time at multiple planes of analyses. TICKIT = Teacher Institute forCurriculum Knowledge About Integration of Technology.

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by preparing Figure 9 I came to understand that interactions among TICKIT as aneducational intervention, the local school district context, and activities initiatedby various actors all contributed to the successful teacher curricular technology in-tegration in Activity System D and the school district’s continued support for tech-nology reform in Activity System E.

Identifying tensions in activity systems. After drawing the triangle mod-els for Activity Systems A through E, I focused on identifying how each element inthe various activity systems affected the subject’s effort in attaining the object andultimately the outcome. During this process, I was able to identify the tensions thatwere involved in each activity. These tensions represent the internal relationshipsamong the elements and how those relationships contribute to shape the nature ofthe activity system.

I relied both on the qualitative data set and the activity systems I had drawnwhen identifying tensions. In some cases the tensions were obvious from examin-ing the data set because they were recurring themes that participants reported af-fected their activity by bringing hardship to their technology integration efforts.For example, a recurring theme from participants at Blackwell was that they hadvery limited resources for successfully integrating technology into their curricu-lum. In other cases, the tensions became more obvious only after examining the ac-tivity systems that I had drawn and when I questioned myself about how each ele-ment in the activity system affected the subject’s ability to attain the object. Forexample, while examining Activity System A, I realized that it was very difficultfor teachers to juggle their demanding responsibilities at their schools and inte-grate technology into the curriculum when there was not a clear division of laborregarding technology at the school district.

An interesting observation regarding tensions at Blackwell was that in ActivitySystems A and D teachers faced the tension of actualizing expectations for inte-grating technology in the classroom while balancing competing responsibilities inthe rule component even though there were several other tensions that had been al-leviated as a result of Activity Systems B and C. The tension in the rule componentin Activity System D came about because teachers who participated in TICKITwere responsible for meeting TICKIT expectations as well as work-related expec-tations. These conditions competed for precious teacher time and thus manifestedas a tension.

By identifying systemic tensions in this study, I was able to demonstrate howinnovations from a professional development program can bring new pressures toteachers’ work that cannot be overcome. TICKIT teachers were responsible formeeting all work-related expectations in their regular school year while workingextra hours meeting TICKIT expectations. These conditions became an obstacle inall teacher activities that the program itself could not overcome.


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Confronting Analytical Dilemmas in Activity SystemsAnalysis

There were several analytical dilemmas I confronted while conducting the activitysystems analyses in the process of carrying out this study. These dilemmasstemmed from my efforts to understand complicated real-world data sets while atthe same time drawing systemic implications and identifying theoretical and prac-tical implications. The analytical dilemmas I confronted during data analysis were(a) defining activity settings from a rich data set, (b) drawing human activities asseries of activity systems, and (c) identifying tensions within single units of activ-ity from networks of activity.

Dilemma 1: Defining activity settings from a rich data set. The first an-alytical dilemma I addressed involved the methods for explicating tacit interac-tions between participant activities from the rich context. Identifying activity set-tings is not a simple process, as Scribner (1997) reported, because individualparticipant activities contribute to shaping the nature of the activity setting as muchas the activity setting shapes the participant activities. In this study, similar toLave’s (1993) findings, activity settings and participant activities became inter-twined and I found they were changing from moment to moment as I progressed inthe data analysis.

I drew Figure 8 in order to confront this dilemma in this study. While creatingFigure 8 I questioned myself about the contextual information that was not in-cluded in the lower triangle portion of each individual activity systems but that stillaffected technology integration activities at Blackwell. My goal was to identifycontextual information at Blackwell that affected TICKIT participant activities.Therefore, I decided to extract information from the qualitative data analysis thatdirectly contributed to the subject’s ability to attain the object. I did not includecontextual information that did not directly affect subject’s ability to attain the ob-ject. Additionally, in this analysis process and in constructing Figure 8 I was notable to address how the participants’ activities brought changes into the activitysetting itself.

Dilemma 2: Drawing human activities as series of activity systems. An-other dilemma I confronted was related to the problem of representing complex hu-man activities in identifiable units while simultaneously avoiding oversimplifyingthe data using the triangle model. Throughout my analysis, I found it very frustrat-ing to represent activity systems based on rich data using the static methods ofEngeström’s (1987) model. I was stripping participant activities from their richcontext by summarizing the data in units of activity systems. This made it difficultto capture the interdependent relations of multiple activities.

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In order to confront this dilemma, I included contextual data that was mostprevalent in the qualitative data analysis and was most relevant to the object of anactivity. Then I created Figure 8 and Figure 9 to present other contextual data thataffected teacher activity and communicated the dynamic relational informationbetween activity systems. The triangle model in activity systems analysis allowsresearchers to synthesize contextual data and participant data; however, it still hasits limits because the real-world context is far more complicated and dynamic thanthe two-dimensional triangle model can represent.

Dilemma 3: Identifying tensions within single units of activity from net-works of activity. Finally, I confronted another dilemma while identifying ten-sions within activity systems. Even though tensions were encapsulated within sin-gle activity system units, I found that they were influenced by other related activi-ties enacted by various subjects within the real-world context but beyond the scopeof the triangle diagram. I realized that although my intention to zoom in to a spe-cific subject’s activity was a useful method for extracting complex human activi-ties and identifying some of the obvious tensions, in order to identify more compli-cated tensions brought about by activities enacted by other participants I had tozoom out of the single activity unit of analysis and analyze the relationships be-tween activities and the implications of those relationships.

Inotherwords, Ihad toshiftmyfocusbackandforthbetween individualactivitysys-tem units and related activities that had an effect on those units. Creating and examiningTable 1 and Figure 9 helped this process because it reminded me of the various levels ofinfluencethat individual, interindividual,andinstitutionalactivitieshadonaspecificac-tivity I was analyzing. For example, the differences in the number and type of tensionsthat teachers faced in Activity Systems A and D were explained by the outcomes fromthetechnologycoordinatorandschooldistrictactivities inActivitySystemsBandC.

Maintaining Trustworthiness in Activity Systems Analysis

Barab and Squire (2004) and Schoenfeld (1992) agree that, to maintain trustwor-thiness, the outcome of design-based research ought to generate new theory. Baraband Squire stated that research needs to connect theory to practice. Schoenfeldstated that researchers need to include enough information about their studies toprovide the reader with findings that are replicable. Additionally, Schoenfeld pro-posed the following as standards for researchers using novel methodologies:

1. Establish the context; describe the issues to be addressed.2. Describe the rationale for the method.3. Describe the method in sufficient detail so that readers who wish to can ap-

ply the method.


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4. Provide a body of data that is large enough to allow readers to (a) analyze iton their own terms, to see if their sense of what happened in it agrees withthe author’s; and (b) employ the author’s method and see if it produces theauthor’s analysis.

5. Offer a methodological discussion that specifies the scope and limitationsof the method, as well as the circumstances in which it can profitably beused, and that treats issues of reliability and validity. (p. 181)

My efforts to maintain trustworthiness in this study spanned several works re-lated to TICKIT. In those works I addressed Schoenfeld’s first criterion by intro-ducing the literature related to the research question, new issues that need to be ad-dressed within this literature, and how my work addressed those issues. Becausethe sample study in this article came from a larger study, I did not sufficiently ad-dress this criterion in this work alone. Instead, I provided more information in mypast work (Yamagata-Lynch, 2003a, 2003b).

I addressed the second criterion in this article by providing background infor-mation on CHAT and the rationale for choosing to modify the existing activity sys-tems analysis methods. These suggestions for modifying the activity systems anal-ysis methods did not come from the sample study alone. In Yamagata-Lynch(2003b), one of the critical theoretical findings I presented when following a tra-jectory of teacher professional development activities related to TICKIT was thateach triangle model had its limits on how much it could encapsulate real-world dy-namic data because the graphic model itself was static and two dimensional. In thepresent article, I continued to explore resolutions to this challenge, developing andexplaining new methods I used for creating Figure 8 and Figure 9 from the richreal-world data set.

I addressed the third criterion by explaining the steps I took in the activity sys-tems analysis. I worked on this criterion more heavily in this article than in some ofmy other works because this article is focused on the methods involved in activitysystems analysis. In some of my past work, in which the goal of the article was topresent research findings based on this methodology, I did not find the opportunityto provide an in-depth methodology section.

In none of my works related to TICKIT data do I provide a sufficient body ofdata to address the fourth criterion. Therefore, it is rather difficult for the reader totest Criterion 3 as well. The goal of this article was to provide enough data andmethodological details to demonstrate the processes involved in activity systemsanalysis to begin a discussion on methodological issues involved in research meth-ods within design-based research. However, in order to be confident about Crite-rion 4, in the future I ought to involve other researchers while drawing the individ-ual activity systems.

I addressed the fifth criterion in my past work and in this article through discus-sions of the methodological benefits and shortcomings of activity systems analysis

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and by pointing out the theoretical contributions my work brings to the activitysystems model. In this article I specifically focused on: (a) Rogoff’s (1995) con-cept of the three planes of CHAT research can be used to manage multiple subjectunits of analysis, (b) Tharp and Gallimore’s (1988) concept of activity settings canhelp situate activity systems within a bounded context, and (c) tensions within ac-tivity systems can result from influences that one activity has on another or fromelements within a component of an activity system that compete against one an-other. Although this article alone does not provide resolutions that address all ofthe limitations of activity systems analysis, it does provide strategies for how re-searchers can use CHAT theoretical constructs for overcoming some of the weakareas.

Criticisms of Activity Systems Analysis

Several valuable critical reviews of activity systems analysis have been made.These critics have argued that activity systems analysis complicates research with-out adding value, oversimplifies human psychology, and does not generate gen-eralizable outcomes. Each of these criticisms needs to be addressed before re-searchers use activity systems analysis in design-based research.

Does activity systems analysis complicate research? One of the criti-cisms of activity systems analysis is that it complicates research when it could beexamined and communicated in more simple terms. As an activity theorist herself,in the field of human computer interaction, Nardi (1996) reported her experienceof having a special issue journal proposal on activity theory and human computerinteraction rejected because the editors believed that activity systems analysis wastoo complex and did not bring any value to her field. The editors argued that in or-der to understand activity systems analysis readers had to invest their time in learn-ing a new language system; however, in the end this analysis method would not addany value to research beyond that of traditional research methods.

The value that activity systems analysis adds to traditional qualitative researchis that it provides a method for researchers to examine how complicated real-worlddata sets are intertwined with the context beyond individual activities. Observa-tions made in the natural settings are systematically affected by the actors, re-sources, goals, and community. Perhaps researchers using this methodology havenot done a sufficient job of emphasizing this added value that activity systemsanalysis brings to their work.

As expressed earlier, through my own work with activity systems analysis Ihave been able to develop (a) a common vocabulary to compare complex learningsituations, (b) a new method for capturing complex data sets, and (c) systemic im-plications from research results. In the sample study, I addressed how many of thetensions in Activity System A were removed after tracing the developments in Ac-


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tivity Systems B and C. The methodological path I took with the activity systemsanalysis made me examine how activities enacted by various individuals at sepa-rate times interacted with one another and the real-world context.

Using this method has automatically made my work more complicated com-pared to if had I engaged in a standard qualitative analysis; however, it has also pro-vided me with new opportunities for addressing rich real-world data sets and iden-tifying findings that are not isolated from their context. This methodology providesresearchers with a framework for organizing and communicating data about hu-man interactions. Therefore, when researchers use this method I suggest that oneof their goals ought to focus on addressing interactions that take place at multipleplanes of analyses and how observing those interactions can lead to findings withsystemic implications.

Does activity systems analysis oversimplify human psychology? Anoth-er criticism regarding activity systems analysis is that the examination of activitiesalone is not sufficient to capture and understand the entirety of human psychology(Toomela, 2000). Toomela is concerned that human activity does not necessarilyrepresent the entirety of human consciousness. He believes that activity systemsanalysis oversimplifies human activity and its relation to human consciousness. Hecautions that human behavior and consciousness are inseparable from the interac-tion between human activity and the environment, and when activity is used as theunit of analysis human activity is separated from human consciousness.

Toomela’s arguments are spurious because he is equating CHAT and activitysystems analysis as synonymous ideas. It is important that researchers clearly un-derstand that CHAT is the theoretical framework that attempts to explain the pro-cesses involved in human psychology, and activity systems analysis is the method-ological tool derived from that theoretical framework. Activity systems analysis orthe triangle model analysis technique is one method within CHAT that attempts tocapture the complicated nature of the human psychology during data analysis, andthe model itself is not designed to explain the entire complexity involved in humanpsychology.

Research methodologies, whether they are quantitative or qualitative, are oftenderived from specific theoretical frameworks. In order to capture observable evi-dence in laboratory or field settings the original theory becomes simplified intovariables or qualitative observations that can be analyzed. While developing activ-ity systems analysis, Engeström (1987) focused on identifying the simplest formof human activity to enable researchers to analyze the dynamic interactions amongthe individual, historical setting, ecological context, and cultural setting. As fur-ther research continues with new researchers using this methodology, there needsto be more discussion surrounding how to identify contextual data that are perti-nent in the analysis and how they can be represented in forms other than the simpletriangle model.

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Are findings from activity systems analysis generalizable? Roschelle(1998) cautioned that activity systems analysis may bring a common vocabulary toresearchers, but this common vocabulary does not allow activity theorists to makegeneralizable claims regarding the situation they are investigating. As Roschellepointed out, activity systems analysis has been used as a descriptive tool for enrich-ing qualitative research methods. Therefore, I agree that findings that result fromthis method are not generalizable. When activity systems analysis is used solely asa qualitative data analysis tool it will not gain the power for making generalizableclaims because it is context specific.

If researchers are to address this issue there needs to be more collaborative workbetween both quantitative and qualitative researchers who are willing to identifywhat quantitative methods compliment activity systems analysis when studyingcomplicated real-world learning situations that would yield findings that can beapplied to multiple contexts. Additionally, researchers need to replicate the imple-mentation of their educational interventions in more than one setting to findwhether there are common systemic implications that arise from the statistical andactivity systems analyses.

CONCLUSION

Activity systems analysis is one method within CHAT that provides an analyticaltechnique for addressing complex qualitative data sets. It is a powerful method forenriching qualitative design-based research, and it provides a systematic methodfor treating contextual data. It provides a starting point for researchers to trace crit-ical contextual elements that affect the object and outcome of an activity.

However, researchers need to be aware that methodologies following the CHATframework are still struggling to emerge (Packer & Goicoechea, 2000). There is along way to go from appreciating the organic psychological nature of human activ-ity to being able to identify methods to capture and communicate the complexitiesinvolved in it. Therefore, if activity systems analysis is to become a powerful quali-tative research tool, it is very important that researchers be honest in their work re-garding the shortcomings they find in this method and explaining how they ad-dressed those shortcomings in their data analysis.

Learning scientists need to work on sharing their experiences using activity sys-tems analysis. They need to share their experiences regarding what analytical di-lemmas they confronted in their work and what strategies they used to addressthem. Additionally, they need to share what were new practical and theoreticalfindings that they found by addressing those analytical dilemmas. Finally, re-searchers need to provide more discussion on how they approached issues relatedto generalizability when using activity systems analysis and what steps, if any, theytook for making their findings generalizable.


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ACKNOWLEDGEMENTS

A previous version of this article was presented at the 2002 biannual meeting ofthe International Conference of the Learning Sciences. This project was originallyfunded by a grant from the Ackerman Family Foundation and, more recently, bythe Arthur Vining Davis Foundation. Dr. Matthew Pamental, Dr. Hayley Mayall,and my Writing Circle members are thanked for their editorial comments and fortheir valuable constructive suggestions. I would also like to thank the editors andthe anonymous reviewers for sharing their comments that significantly advancedmy work on this article.

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Documents

Confronting Analytical Dilemmas for Understanding Complex Human Interactions in Design-Based Research From a Cultural—Historical Activity Theory (CHAT) Framework