This article reports on a study in which activity theory was used to design, implement, and analyze a 10-week curriculum unit about how honeybees collect nectar with a particular focus on complex systems concepts. Students (n = 42) in a multi-year kindergarten and 1st-grade classroom participated in this study as part of their 10 regular classroom activity. The curricular unit was composed of 4 specific activity types, each of which was intended to focus students on a particular dimension of the content: (a) Inquiry with BeeSign software was intended to help students explore the benefit of individual nectar-collecting behaviors for the hive as a whole; (b) traditional drawing activities were intended to help students learn the structures of 15 the bees; (c) participatory representation activities, in which students enacted the behavior of the bees as they collect nectar, were intended to help students link bee structures to individual behaviors; and (d) an embodied nectar-gathering game was intended to help the students recognize the challenges of finding nectar for individual bees. Pre- and posttest interviews reveal a shift in individual student understanding 20 as students progressed from discussing the superficial structures of the system to discussing both behaviors and functions.

In this paper, we synthesize two bodies of work related to students' representational activities: the notions of meta‐representational competence and representation as a form of practice. We report on video analyses of kindergarten and first‐grade students as they create representations of pollination in a science classroom, as well as summarize results from interviews regarding the design choices that they made. Analysis of the semistructured pre‐ and postinterviews reveals that students attend to the content domain, local activity, and their personal preferences when evaluating representations. Analysis of video case studies that followed the students as they created their representations further reveals several key mediators of the students' representational activities, including other students, task constraints, the teacher, and local norms for what constituted a “good representation.” In addition, the data show that these norms shifted over time as new content was covered in the class, and were appropriated in interaction with other students. Finally, both sets of analyses reveal that students often face competing constraints when creating their representations, and resolve these constraints through a complex set of negotiations. © 2006 Wiley Periodicals, Inc.Sci Ed91:1–35, 2007

Research has shown that students respond to social expectations of interviews by engaging with the content in distinct ways that may or may not be productive. These structures of expectations with respect to knowledge are referred to as epistemological framing. In this study our goal is to introduce a systematic way to analyze student behaviors and describe how they cluster together to reflect different epistemological frames. In analyzing the data statistically, frames are regarded as a latent variable that accounts for the co-occurrence of behaviors. We use a computer clustering algorithm to systematically identify behavioral clusters in videotaped data of early elementary students that construct explanations of biological systems in semi-structured interviews. We also examine the relationship between these behavioral clusters and mechanistic reasoning as a way to investigate the importance of the inferences made based on these identified frames. Results show that there is a clear association between epistemological framing and student reasoning. By providing a statistical model of student framing, our approach can support the ongoing refinement of theory around epistemological frames and their impact on learning.