Flood Harrar Wittmann and many others on embodied cognition in chemistry

Virginia J. Flood, Fran├žois G. Amar, Ricardo Nemirovsky, Benedikt W. Harrer, Mitchell R. M. Bruce, and Michael C. Wittmann

Paying Attention to Gesture when Students Talk Chemistry: Interactional Resources for Responsive Teaching

Journal of Chemical Education
J. Chem. Educ., 2015, 92 (1), pp 11–22
DOI: 10.1021/ed400477b
Publication Date (Web): October 21, 2014

Abstract: When students share and explore chemistry ideas with others, they use gestures and their bodies to perform their understanding. As a publicly visible, spatio–dynamic medium of expression, gestures and the body provide productive resources for imagining the submicroscopic, three-dimensional, and dynamic phenomena of chemistry together. In this paper, we analyze the role of gestures and the body as interactional resources in interactive spaces for collaborative meaning-making in chemistry. With our moment-by-moment analysis of video-recorded interviews, we demonstrate how creating spaces for, attending to, and interacting with students’ gestures and bodily performances generate opportunities for learning. Implications for teaching and assessment that are responsive to students’ ideas in chemistry are discussed.


Smith Wittmann Carter on analyzing the FMCE

Trevor I. Smith, Michael C. Wittmann, and Tom Carter

Applying model analysis to a resource-based analysis of the Force and Motion Conceptual Evaluation

Phys. Rev. ST Phys. Educ. Res 10, 020102 – Published 2 July 2014
DOI: http://dx.doi.org/10.1103/PhysRevSTPER.10.020102

Previously, we analyzed the Force and Motion Conceptual Evaluation in terms of a resources-based model that allows for clustering of questions so as to provide useful information on how students correctly or incorrectly reason about physics. In this paper, we apply model analysis to show that the associated model plots provide more information regarding the results of investigations using these question clusters than normalized gain graphs. We provide examples from two different institutions to show how the use of model analysis with our redefined clusters can provide previously hidden insight into the effectiveness of instruction.


Clark, Thompson, and Mountcastle on PV diagrams in physics and engineering

J. W. Clark, J. R. Thompson, and D. B. Mountcastle
Investigating Student Conceptual Difficulties in Thermodynamics Across Multiple Disciplines: The First Law and P-V Diagrams
Proceedings of 121st ASEE (American Society for Engineering Education) Annual Conference and Exposition (2014).

Thermodynamics is a core part of the curriculum in physics and many engineering fields. While individual courses in each discipline appear to cover many of the same topics at some level, the emphasis, applications, and many representations are idiosyncratic to the field. Education researchers in both disciplines have studied thermodynamics learning and teaching. Physics education researchers have identified student difficulties with foundational concepts such as heat, temperature, and entropy as well as with larger grain-sized ideas such as state variables, path-dependent processes, etc.  Engineering education research shows analogous findings and has identified additional difficulties unique to engineering contexts, such as confusion between steady-state and equilibrium processes.
     An open question is the extent to which discipline-specific research findings apply across disciplines.  Previous work by us and our colleagues in physics education research has explored student difficulties with thermodynamics and statistical mechanics in upper-division physics courses.  We have recently broadened the scope of our own investigation to include mechanical and chemical engineering courses, to see whether similar difficulties are present in these disciplines and how certain instructional pedagogies may affect student learning.  At our institution, thermodynamics is not covered in the introductory physics course sequence, so for most students this is their first formal encounter with the topic.
     Our initial focus is on the First Law of Thermodynamics and its constituent elements, as this topic is fundamental to all the courses of interest.  We have administered hand-written, free- response questions to students at various points before and/or after instruction.  The questions discussed here require interpretation of graphical information about thermodynamic processes. We have coded responses according to student reasoning (e.g., area under the curve, time- related) provided in the data so as not to confine our understanding of student ideas  We find that most reasoning patterns are present in all disciplines although the frequency varies by discipline. Initial answering patterns are similar across disciplines with a high proportion of students responding with incorrect ideas.  The post-instruction patterns are improved but show persistence of some specific difficulties (e.g. work is path-independent).  These outcomes vary between courses and are consistent with disciplinary emphasis and individual instructional practice.


Wittmann and Black on Consistency Plots

Michael C. Wittmann and Katrina E. Black

Visualizing changes in pretest and post-test student responses with consistency plots
Phys. Rev. ST Phys. Educ. Res 10, 010114 – Published 5 May 2014

Tabular presentations of student data often hide information about the switches in responses by individual students over the course of a semester. We extend unpublished work by Kanim on “escalator diagrams,” which show changes in student responses from correct to incorrect (and vice versa) while representing pre- and postinstruction results on questions. We introduce the representation of “consistency plots,” containing three pieces of information: each student’s method of solution and correctness of solution and the shift from before to after instruction. We present data from students in an intermediate mechanics class answering (nearly) identical midterm and final examination questions. These data serve as a proof of concept of the method; we suggest other possible uses of consistency plots in physics education research, as well.