Conceptual Cultural Historical Activity Theory (CHAT) Framework

We used a modified activity theory framework, originating from Russian scholars (Hakkarainen, 2004), but made popular in North America by Scandinavian theorist Yrjo Engestrom (1987). Specifically, Engestrom combined both theory and practice, developing a formal methodology in research for mapping complex human interactions from qualitative datasets. In its original form, Engestrom included subject, took, object, rules, community, distribution of labor, and outcomes as shown in Fig. 1. 

Figure 1: Activity system adapted from Engestrom (1987)

As explained by Yamagata-Lynch and Smaldino (2007) “subjects are participants of the activity and tools are the resources that subjects use to obtain the object of goal” (p. 366). They continue saying, “rules can be informal or formal regulations that subjects need to follow while engaging in the activity. The community is the group that subjects belong to and the division of labor is the shared responsibilities determined by the community (Yamagata-Lynch & Smaldino, 2007, p. 366). Engestrom (1987) developed this framework to “explore and document the sources of tensions in human or collective activities” (Yamagata-Lynch and Smaldino 2007, p. 366). He wanted to help participants identify tensions in their practices and develop strategies to overcome them, allowing a collective action as opposed to individual efforts (Cole & Engestrom, 1993; Engestrom, 1987, 1993). Both individual and group activities are linked by their social context. Using applications of Engestrom’s activity system framework, along with more recent use from Yamagata-Lynch and Smaldino (2007), not only gives us a descriptive research tool in qualitative analysis, but will also help us research the complex social construction of educational organizations.

For use in evaluating and improving K-12 school and university partnerships, Yamagata-Lynch and Smaldino (2007) went through the methodological process of modifying the Engesstrom’s (1987) original activity systems analysis model. They developed specific language to represent the various components of the model (i.e., subject, tool, object, rules, community, and division of labor) so that teacher participants would be able to understand the framework. By adding questions related to each component (Fig. 2), participants did not need a theoretical background in the accompanying activity systems literature.

Figure 2: Modified activity system from Yamaga-Lynch and Smaldino (2007). Reprinted with permission of Elsevier. Yamagata-Lynch, L.C., & Smaldino, S. (2007). Using Activity Theory to Evaluate and Improve K12 School and University Partnerships.

For our overarching “Schools as effective learning organizations” collaborative learning community research study, we use the modified activity system model from Yamagata-lynch and Smaldino (2007) as a theory of action framework. The instruments shown in Figs. 3-4 engage both student learners and teachers as learners in order to achieve specific objectives.

Figure 3: Activity Analysis Framework: Student Learners C-PEER (2015)

Student Learners

The objective for our student learners is the co-creation of learning experiences with teachers, schools, and the students’ communities.

• Tools. In staying consistent with Yamagata-Lynch and Smaldino’s (2007) framework for an exploratory study of professional learning, we look at the resources that our student learners use in order to obtain the objective or goal. By asking What resources are currently available? and What resources do you need? we want student learners to help analyze what makes them successful as a learner. These include curriculum and instructional materials as well as classroom activities. We also look at home study supports such as available technology. We ask students survey questions about academic language and feedback used in the classroom, including self-assessments. Finally, an important tool we analyze is students’ self-regulation capacity. It is important for us to understand how students direct their own learning in school. Although there is no simple definition of the construct for self-regulation (Boekaerts & Corno, 2005), we hope this framework will help us as researchers to gain a detailed understanding of the cognitive and affective processes that underlie [the] actions that students initiate to regulate their motivation and learning in the classroom” (Boekaerts & Corno, 2005, p. 201). 
• Rules. The rules defined by the activity analysis framework are both the formal and informal norms, policies, and processes that make up an educational environment. For example, classroom and school norms, discipline-related expectations, homework policies, and student academic placement processes are all polices that student learners must navigate in order to be successful in school. 
• Community. The student learners’ community include the other students in the classroom, the teacher or any other supporting adults in the classroom, other students in the school, and parents or guardians engagement within the building. 
• Participation Structures. Whereas Yamagata-Lynch and Smaldino’s (2007) framework describes a division of labor, asking such questions as What specific responsibilities do you have to meet your goal? and What other responsibilities do you share with your colleagues to meet your goal?, we label this as participation structures due to the organization structure of schools. We are analyzing the organization of the learning activities within the school (e.g.: individual versus group projects and heterogeneous versus homogenous student grouping). We look at the support systems in place, such as teacher’s assistants and special education. Finally, we want to know what sorts of technology structures are in place within the classrooms. 
• Outcome and Indicators. Our intended objective for student learners is the co-creation of their learning experience with teachers, school, and the student’s community. Specifically, we are looking for students’ access to learning tools, cognitive, behavioral, and emotional engagement, and their abilities to gain appropriate knowledge and skills for their own defined success in school. Our data sets include performance trends, attendance and discipline data, and students’ perceptions of their school’s climate and the available social and emotional supports for students. 

Figure 4: Activity Analysis Framework: Teachers as learners C-PEER (2015)

Teachers as Learners

The objective for our teacher colleagues groups aggregated at the individual school level is the co-creation of learning experiences for their students as well as the continual improvement of skills, knowledge, and a mindset for effective teaching. Similar to the student learners, teacher participants are analyzing resources that they use in order to obtain the stated objective.

• Tools. Similar to the tools described in the activity analysis framework for student learners, teachers as learners need to ask the same questions: What resources are currently available? and What resources do you need? For teachers, their tools include, curriculum and instructional materials, timely access to student progress data, protocols and time for collaborative consideration of student work, response to intervention (RtI) processes, feedback from teacher evaluations, and options for professional learning. 
• Rules. Rules can be informal or formal regulations that teachers need to follow while teaching. These include instructional expectations, school norms as well as classroom norms, teacher resources for professional learning, collaboration among colleagues, and coaching, teacher evaluation systems, supports for innovations, and school requirements regarding professional learning communities (PLC’s). Our teacher surveys and focus group interviews will help us analyze schools as effective learning organizations. 
• Community. A teacher’s community includes many of the same supports for students (e.g.: students and other adults in the classroom); however, teachers can also rely on other adults in the school. For example, teacher leaders, colleagues, coaches, administrators, and evaluators. A teacher may also have access to external facilitators or trainers, specifically related to professional learning opportunities. 
• Participation Structures. We use the same questions Yamagata-Lynch and Smaldino (2007) ask for their framework, when analyzing teachers. Participation structures for teachers include time for planning and instruction, professional learning opportunities (whether required or by choice), and support systems (e.g.: coaching, mentoring, and access to teacher assistants and special education support). We want to analyze what structures are in place for peer learning and planning, supervisor/administrator-teacher interactions, and possible co-teaching. 
• Outcome and Indicators. The objective for teachers as learners is the same as for students; however we are adding a continual need for improvement of knowledge, skills and mindset for effective teaching. Teachers’ objective to co-create a learning experience for their students can be measured through student engagement, modifications in pedagogical practice, and teachers’ active participation in school-wide improvement and innovation. Measuring student engagement is a dynamic process that has limited theoretical research (Handelsman, Briggs, Sullivan, & Towler, 2005). There are many tools to measure engagement (Marzano & Pickering, 2011). Our outcome indicators include data-driven reflection.

STEM Perspectives

The most comprehensive and coherent meta-analysis of the differing perspectives of STEM education comes from Rodger Bybee’s (2013) The Case for STEM Education: Challenges and Opportunities. Many current discussions of STEM view all of STEM as either science or mathematics, rather than separate delineations. This can be the most confusing because it contrasts multiple disciplinary orientations with a single discipline reference. The analogy Bybee (2013) uses is one of a forest ecosystem and looking for an individual tree. When teachers feel that STEM equals science or equal mathematics, then they incorrectly categorize STEM-foundational thinking as that found in a science or mathematics class (e.g.: scientific method or mathematical equation). To say that a single tree equates to an entire forest ecosystem is similarly misguided (see Figure 6).

Figure 6. STEM represented as a science discipline.

Since science and mathematics are such a strong part of STEM education, many educators and district leaders feel that STEM refers to these disciplines, especially in middle and high schools. Bybee (2013) feels that this perspective “should not be surprising due to the long history of these disciplines as curricular components in American education” (p. 74) (see Figure 7).

Figure 7. STEM represented as separate disciplines of science and mathematics.

Many teachers, especially science teachers, incorporate technology (and sometimes engineering) into their course of study. In this perspective, elementary school teachers often introduce an engineering-design cycle to students when solving a problem such as: how can you design a container that will protect an egg when dropped from a specific height? “This perspective represents the first step toward integration, but the teacher keeps science (or math) as the dominant discipline and, as appropriate or needed, introduces the other disciplines” (Bybee, 2013, p. 75) (see Figure 8).

Figure 8. Separate science disciplines that incorporates technology, engineering, or mathematics.

When teachers teach specific subject areas, oftentimes, it is referred to “teaching in a silo” because their content area is separated from the other content areas. For example, the math department is separate from the science department. It is not surprising then that some teachers define STEM education as a series of separate content disciplines. With separate disciplines there is no connection between the two, similar to separate chapters or units of a textbook (see Figure 9). Bybee (2013) takes issue with this particular perspective because, especially in high school, although “the representation shows the silos as equal, this is not usually the case, especially when requirements for graduation are considered” (p. 76). Research on STEM education policy agrees with Bybee’s (2013) contention of this model. Oftentimes, different stakeholders have varying opinions about what STEM entails (Breiner et al., 2012), slowing down reform efforts.

Figure 9. STEM represented as separate disciplines (silos).

Again, when science and mathematics are separate disciplines, there is little or no connection to each other. Many teachers attempt to bridge these content areas using technology or engineering (see Figure 10). For example, when preparing for a career that requires a technical education, many career and technical education (CTE) programs use this perspective of STEM education. The California project Linked Learning: Pathways to College and Career Success uses “technology and engineering projects to connect core subjects of science and math to experiences in professional and technical education in fields such as biomedical and health sciences, energy resources, information technology, and agriculture” (Bybee, 2013, p. 77).

Figure 10. STEM as connections between science and math made by technology and engineering

When teachers make connections between the different content areas, STEM education becomes a coordination of specific concepts that will be used in other courses. For example, a science teacher may ask their mathematics colleague to introduce a concept that will be needed in science (see Figure 11). However, “less frequently do math teachers ask science or technology teachers to apply math concepts” (Bybee, 2013, p. 77). Bybee (2013) recognizes that this perspective represents an ideal because “in reality, two of the four disciplines likely will coordinate concepts and processes” (p. 77).

Figure 11. STEM as concepts, processes, and resources coordinated across separate disciplines.

Another form of integration of disciplines occurs when teachers begin to combine two or more subjects in order to create another course. For example, a high school principal may decide to create a new science and technology course (see Figure 12). Here, both disciplines would have equal emphasis.

Figure 12. STEM model as combining two or more disciplines in order to form a course.

According to Bybee (2013), “STEM can be integrated by sequencing disciplines in units or courses, or in lessons so STEM becomes a central emphasis of the education experience” (p. 78). This perspective offers a unique sequence of overlapping in order for students to progress through the disciplines (see Figure 13).

Figure 13. STEM represented as integrated disciplines.

Finally, STEM education can be seen as a transdisciplinary course or program where real-world problems are addressed using each discipline: science, technology, engineering, and mathematics. For example, a high school could create a course called Sustainable Society where students could use “the entire group of STEM disciplines, and perhaps others (e.g.: ethics, politics, economics) to understand a major contemporary challenge” (Bybee, 2013, p. 78). By having a transdisciplinary approach to STEM education, students would be presented with issues such as global climate change, health problems, or renewable energy resources (see Figure 14).

Figure 14. STEM as transdisciplinary approach.

Bybee (2013) does not offer preference for any of these STEM perspectives; however, for school or district-wide STEM integration, “the whole represents more value than just a sum of its parts” (Chiu, Price, & Ovrahim, 2015, p. 24). Good instructional design, collaboration, sustainable professional development, and organizational leadership are all key to any integrated program, but especially STEM education. Existing research on organizational performance and equitable school improvement discuss the need for values, collaboration and planning, curriculum and instruction, professional learning, and communication (Chiu, Price, & Ovrahim, 2015; Bryl, 2010; Seabring et al., 2006; Rogers, 1995; Basham, Israel, & Maynard, 2010; Wang et al., 2011; Wiebe et al., 2013; Mahoney, 2010).

          Values. In looking at comparative case studies of 10 STEM-focused high schools, Scott (2012) found that a school’s mission statement has an overall impact on school culture. There is an obvious connection between a school’s mission statement and “the characteristics of the programs that each school provide[s]” (Chiu, Price, & Ovrahim, 2015, p. 6). Schools that have a strong STEM focus imbedded in their mission statement, culture, and leadership will have more successful STEM students, “whereas a principal who does not support science or science learning could do just the opposite” (Chiu, Price, & Ovrahim, 2015, p. 7). Both Bryk (2010) and Seabring, Allensworth, Easton and Luppescu (2006) offer five essential supports for school improvement that can also be tied to a strong STEM program: (a) leadership, (b) professional capacity, (c) parent-community ties, (d) student-centered learning, and (e) instructional guidance. According to Bryk (2010), “leadership drives change” (p. 25). Therefore, it only makes sense that one would question the form of leadership necessary to drive sustainable change. The leadership factors for successful school improvement are a combination of inclusive and instructional leadership. Closing the opportunity gap, especially with regards to STEM inequity, is a large problem that must begin at the local level. Teachers must have a “can-do” attitude continually seeking new ideas for culturally responsive pedagogy and STEM education. School improvement must involve parents. Teachers must “outreach to parents” in order to “develop common goals and understandings to strengthen student learning” (Seabring, Allensworth, Easton & Luppescu, 2006, p. 22). For example, having a STEM parent-outreach program connects parents and teachers so that they may collaborate in the best interests of their students. Having more parent involvement will also better hold teachers accountable for culturally responsive classroom practices. It makes sense that in order to increase student achievement one must have a school culture centered on student learning. This includes high academic standards and increased academic rigor for all students (especially those marginalized by the school system). Finally, a coherent instructional guidance system must be in place to increase student learning. This “articulates the what and how of instruction”, creates assessments that provide feedback to inform subsequent instructional decisions. There needs to be an emphasis on the need to “prepare all students to be proficient in STEM, including girls and minorities that are underrepresented in these fields, as well as to inspire these students to learn STEM and motivate them to pursue careers in these fields” (Chiu, Price, & Ovrahim, 2015, p. 8). Every grade level must be committed to STEM and students of color, and collaborating between grade levels so that teacher instruction is refined.

          Collaboration and planning. Collaboration is “when members of an inclusive learning community work together as equals to assist students to succeed in the classroom” (Powell). Friend and Cook (1992, pp. 6-28) explain that collaboration has six defining characteristics: (a) collaboration is voluntary, (b) collaboration requires parity among participants, (c) collaboration is based on mutual goals, (d) collaboration depends on shared responsibility for participation and decision making, (e) individuals who collaborate share their resources, and (f) individuals who collaborate share accountability for outcomes.

Whenever one is trying to change a paradigm, it is important to recognize how people adapt to change. For example, Rogers (1995) discusses diffusion of technology as a series of stages, where the process occurs over time, however, I feel that his hypothesized distribution of adopters categories within a typical population can be used for implementing any sustainable change (see Figure 14).

Figure 14. Hypothesized distribution of adopter categories within a typical population.

This bell curve indicates that voluntarily collaborating on the STEM equity gap will be easier for those innovators, early adopters, and early majority. Teachers will be able to set mutual goals and share not only the responsibility for participation and decision making, but also sharing resources and accountability. It is more difficult to engage the late majority and laggards, since closing the opportunity gap requires much more of a paradigm shift than just adopting new technology. Glen Singleton says that “race isn’t the only factor; it is the missing factor” and that to “see race is not racist. The meaning we attach to what we see can be racist” (p. 167). Basham, Israel, and Maynard (2010) suggest that teachers should work together as a team to make instruction authentic. Brown, Brown, and Merrill (2011) introduce the idea that science, technology, engineering, and mathematics teachers teach multiple concepts that lend themselves to possible collaboration on a daily basis. Collaborative STEM leadership “distributes power, authority, and responsibility across [a] group” (Anderson-Butcher et al., 2004, p. 4). True collaboration requires an interdependence “characterized by trust, norms of give-and-take, shared responsibilities, consensus-building and conflict resolution mechanisms, shared power and authority and shared information and decision-making systems” (Anderson-Butcher et al., 2004, p. 2). Collaborative teachers must agree to teach STEM in a framework that fits the school’s mission and vision before true integration is possible.

          Curriculum and instruction. Current literature offers schools suggestions for STEM curriculum and instruction; however, there are limited examples. For example, projects such as Engineering is Elementary and Project Lead the Way offer teachers ways to integrate STEM into their curriculum. They provide example lesson plans and units for teachers to follow, but do not offer ways to create (or recreate) a system-wide elementary school STEM program, especially one that focuses on marginalized student populations.

Basham, Israel, & Maynard (2010) state:

The curriculum that is utilized in a school and its instructional practices are important pieces to look at when considering student achievement. STEM educational strategies must move beyond discipline-specific education. Integrating all disciplines offers students the opportunity to make sense of the world in an authentic way (p. 15)

True STEM integration requires applying all content to solving real-world problems.

          Professional learning. Schools with an effective STEM program often place great importance on teacher professional learning. For example, “one barrier to successful STEM education is the lack of investment in the professional development of teachers to build a strong knowledge base in science, which has been attributed to poor student performance” (Ejiwale, 2013). In order to overcome this barrier, schools must adopt professional learning that can “simultaneously help existing teachers develop deeper understanding of the subjects they teach while exploring mechanisms for integration across STEM and non-STEM disciplines” (Chiu, Price, & Ovrahim, 2015, p. 14; Wang et al., 2011). When an organization has a sustained professional development program, with a clear understanding of the goals, both pedagogical practice and student achievement strengthen.

          Communication. STEM in as acronym, which stands for Science, Technology, Education, and Mathematics. However, despite having a clear idea of the acronym, many teachers do not have a clear understanding of what STEM education means, especially in K-12 buildings. “A survey of educational professionals in Northeast Tennessee found that educators have a variety of definitions of STEM, including varied and contradictory terms such as student-focused, integration, hands-on, and project-based education (Chiu, Price, & Ovrahim, 2015, p. 15). Although these are good ideas in theory, educators and administrators need a clear definition of STEM education; one that is based on current research literature. If teachers do not understand STEM, then students will also have a disconnected perception, and will be unprepared for STEM careers upon graduation. For example, “surveys of grade 4-12 students show a lack of awareness of STEM careers, little opportunity to engage with STEM industries, and declining student attitudes in STEM subject areas (Wiebe et al., 2013; Mahoney, 2010, p. 30). School districts need to have clear communication, amongst staff, students, and the parent community, as to the definition STEM and justification for school-wide integration.

Summary

A review of the literature supports the need to create equitable access and opportunities to a rigorous curriculum centered on STEM-foundational thinking; however, there is a gap in STEM education literature for creating equal access and opportunities for underperforming students of color at the elementary level. Whereas previous research indicates a lack of diversity in STEM education and careers coupled with research on organizational performance and specific schools structures that support successful STEM integration, there is a need to research what elementary school structures are needed in order to support STEM-foundational thinking and instructional activities while supporting students of color in STEM curricular areas.

Reforming STEM Education

In his 2011 book on reforming Science, Technology, Engineering, and Math education in America, STEM the Tide, David Drew outlines the current research of eight changes needed in order to improve STEM education: (a) leadership; (b) evaluation; (c) better teachers; (d) high expectations; (e) committed mentors and role models; (f) value of a college education; (g) closing the achievement gap; and (h) revitalizing university research. Each of these elements are supported by research on effective leverage points in public education. However, the focus on the achievement gap dominates his discussion of reforming STEM education. For example, because students of color are denied opportunities to master STEM, their underrepresentation in STEM fields puts the field at a disadvantage.

Diversity leads to better decision outcomes, enhanced task performance, and greater innovation and creativity. The pervasiveness of unconscious bias and stereotyping having to do with gender and ethnic composition of our technical talent limits the possibility of technological innovation around the world (Klawe, Whitney, & Simard, 2009, p. 69).

Drew (2011) does describe various examples of how mentor teachers with high expectations have closed the achievement gap at a variety of institutions. For example, the calculus workshop programs at California State Polytechnic Institute, which was inspired and patterned after Uri Treisman’s 1985 doctoral dissertation research on the “efficacy of individualized tutoring, self-paced instruction, and short course aimed at the development of study skills” (Drew, 2011, p. 113) with students at the University of California, Berkeley. This case study, as well as other examples from The Louis Stokes Alliance for Minority Participation (LSAMP) in Louisiana and Texas, illustrate his point on the importance of mentoring students of color and creating a supportive peer culture in closing the STEM achievement gap. In order to ensure more equitable access to STEM curriculum, it is important to note current research on STEM perspectives and frameworks.

Racial Consciousness in STEM Classrooms

When defining a teacher’s role in designing and facilitating a classroom’s dynamics, it is important to note both course design and instruction (Haynes, 2013). Teachers need to have a high level of racial consciousness in order to promote STEM equity for students of color. Joseph, Haynes, and Cobb (2016) describe the importance of inclusion and racial discourse for all teachers and grade levels; however, they specify their research to “faculty who teach science, technology, engineering, and mathematics (STEM), including those who train pre-service teachers seeking licensure in that discipline” (p. 2). Their STEM system conceptual framework (see Figure 5) “plays a critical role in diversifying [the] labor force by increasing participation in STEM among racially minoritized students” (Joseph, Haynes, & Cobb, 2016, p. 2).

Figure 5. STEM system conceptual framework. Graphically designed by N. Joseph, 2015, to explain the STEM system as a White institutional space.

Transforming STEM education in order to increase participation in STEM among racially minoritized students, will undoubtedly disrupt White institutional space. Haynes and Joseph (2016) describe that especially in higher education “the STEM system functions as White institutional space that positions Whiteness as normal, reproduces hegemony, and contributes to the differing of experiences among students based on race” (Martin, 2008; McGee & Martin, 2011; Moore, 2008; Tate, 1994; Terry, 2010). Reforming education, then, means reforming STEM systems of thinking, using it as disruptive innovation. “A system-wide shift to claiming STEM as a disruptive innovation calls for students to become engaged in their learning as explorers, who share their learning with each other and with authentic audiences to serve real purposes” (Berkowicz & Myers, 2016). By displacing the STEM status quo, teachers, administrators, and other school leaders must increase their racial consciousness, and that of the school system, in order to impact STEM teaching and learning, ultimately expanding the STEM pipeline for students of color.