Instructional Systems of Practice: A Multidimensional Analysis of Math and Science Undergraduate Course Planning and Classroom Teaching

Abstract

Descriptions of faculty practice that illuminate nuances of how course planning and classroom instruction occur in specific contexts are important to inform pedagogical interventions. The study reported in this article draws on systems-of-practice theory to focus on the dynamic interplay among actors, artifacts, and tasks that constrains activities such as course planning and constitutes other activities, such as classroom instruction. This qualitative case study of faculty teaching in math and science disciplines at 3 research universities is based on interview and classroom observation data (n = 57 instructors) that are analyzed using causal network and social network analysis techniques. Results indicate that course syllabi are important organizational artifacts that are created by curriculum committees, inherited from previous instructors, and shaped by consideration of the sequential acquisition of knowledge. Faculty perceived that although course syllabi delimit the type and temporal sequencing of material for faculty, they are generally free to teach how they like. Observation data reveal discipline-specific configurations in frequently used teaching methods, cognitive engagements, and the use of instructional technology. These results also demonstrate that conceptualizing teaching solely as the use of particular methods (e.g., lecture) obscures subtle features of practice. Using the approach outlined in this article, instructional designers can obtain insights into meanings and practices that can be used to design and implement locally attuned reform initiatives.

Notes

¹By faculty, we mean all people who hold undergraduate teaching positions—whether full or part time, tenured or untenured—in postsecondary institutions.

²This is also a basic premise in fields long involved in behavior change efforts, such as public health. A key problem is the misalignment between the sociocultural context of the target population and the underlying assumptions regarding behavior that inform particular interventions (Helman, 2007; Rogers, 1995).

³This body of research provides perhaps the most robust and detailed descriptive accounts of classroom instruction at the postsecondary level.

⁴This use of the term artifact is preferred to tools because it draws attention to the role of designers in fashioning key elements of the world in which people work and live. In contrast, tools refers to found as well as designed objects that are navigated in the course of daily life. The emphasis on design is useful in highlighting both the created aspects of educational organizations and the potential for leaders or faculty to themselves create the conditions for task performance (R. Halverson, personal communication, July 24, 2011).

⁵In a conceptual analysis of the role of cultural tools in interdisciplinary work, Lattuca (2005) emphasized the well-known fact that each academic discipline has its own set of cultural tools, such as foundational concepts, disciplinary jargon, research methodologies, and teaching practices (see also Becher & Trowler, 2001; Bourdieu, 1990). When faculty from other disciplines borrow these tools, a process of transformation occurs as the disciplinary assumptions and practices of the new users necessarily alter how the tool is used. This process is particularly salient for pedagogical change in math and science, as faculty must appropriate some cultural tools from education research or the learning sciences, which results in the tool undergoing a certain degree of reinterpretation and quite possibly being used in new and unforeseen ways.

⁶This conceptualization is specific to our target sample for the study reported here, which consists primarily of large undergraduate courses in science and mathematics at three research universities. Other teaching contexts (e.g., a high school math course) will likely include different activities.

⁷We use the terms chalkboard and blackboard interchangeably in reference to the writing surface on walls at the front of classrooms, and not the learning software or its parent company.

⁸Future research examining instructional systems of practice should take into account faculty activities in each of these separate venues and how, if at all, coordination among different course components influences planning and teaching.

⁹Although 57 faculty participated in this study, one respondent declined to be recorded. Thus, the study sample for the observation component of the study was 57, whereas the study sample for the interview component was 56.

¹⁰On a few occasions instructors were not immediately available before or after the class period. In those cases, we conducted the interviews as close to the observations as possible. All interviews were conducted within 2 days of the observations.

¹¹The version of the TDOP included in the Appendix has been revised to include new dimensions of practice (e.g., pedagogical strategies such as organizational skills) and new codes for existing dimensions.

¹²Given the limitations of observation-based data in discerning pedagogical intentions or instructional decision making that may be informing classroom behaviors, it is especially important to pair observations with interviews with instructors. This is particularly important in regard to the role of artifacts in systems of practice, as task analysis on its own will not illuminate all of the artifacts (and their features) that inform practice.

¹³This means that, at least initially, each instructor had multiple rows of data, one for each 5-min interval that was observed.

¹⁴There is also a tacit or unconscious element to this process, as artifacts and the networks in which they are embedded embody particular values and behavioral expectations that are often not perceived as such by users (Greeno, 1998; Pea, 1993). However, we do not explore this aspect of the process in this article.

¹⁵Other respondents either did not discuss the origins of their syllabi or referenced other influences.

¹⁶The volume of content included in a syllabus also may have implications for student learning, as one physicist noted that “the course is very difficult just because we're covering so much so fast.” In his view, although the content itself was challenging to learn, it was the volume of content and the lack of time spent on each topic that represented the most difficult part of the course for students.

¹⁷Note that the codes arranged vertically along the upper left side of the graph are those that were not observed in any class and are thus disconnected from the graph.

¹⁸In practice it is not likely to be possible that a complete graph (density = 1.000) would be observed in this context, because some techniques cannot feasibly be used together.

¹⁹In this context “greater” should not be equated with “better.” We are not making any evaluative judgments here but rather are seeking to make comparative descriptions and raising hypotheses about the nature of the cross-disciplinary variations.