Targeted Poster Session: TP-A

Challenges for the PER Community:  An Exploration of Common Assumptions, Open Questions, and Current Controversies

Organizer:  Paula Heron (pheron@dirac.phys.washington.edu), Univ. of Washington

Where:  Summit Room
When:  8:15 – 9:45 & 3:45 – 5:15, Thursday, August 5

Goal: In this Targeted Poster Session, we will each identify specific common assumptions, open questions, or current controversies and argue the need for their illumination through research.  We will challenge the community to tackle these issues and propose some initial steps.  Participants in the session will be invited to refine and/or redirect these challenges, and pose additional ones of their own.  The goal will be to stimulate research on some issues of importance for the field.

Individual Poster Abstracts

TP-A1
Macroscopic observations and microscopic models:  What do students really learn from computer simulations?
Paula Heron (pheron@dirac.phys.washington.edu), University of Washington
Abstract: In 2000, Richard Steinberg published an article with the provocative title “Computers in teaching science: To simulate or not to simulate?” Steinberg had investigated student learning of air resistance with and without a computer simulation. Among his goals was to assess the effect of simulated experiments on student understanding of the nature of science. Unfortunately, there are very few examples of research of this sort. The enormous effort being devoted to the development and dissemination of increasingly sophisticated simulations has not been accompanied by a similarly vigorous attempt to understand their effects on student understanding, either of the relevant concepts and principles or of the nature of scientific models. I will argue that the implications of computer simulations for students’ epistemological development are in need of serious, systematic investigation. In particular, we need to understand what to do to ensure that simulations involving microscopic particles and processes enlighten, rather than mislead, students about the nature of scientific models. This kind of research is needed to provide guidance on the use of simulations in courses that have as their goals helping students develop increasingly sophisticated views of the scientific enterprise as well as of scientific concepts.

TP-A2
How Do You Hit a Moving Target? Addressing the Dynamics of Students' Thinking
David Meltzer (dem@iastate.edu), Iowa State University
Abstract: From the standpoint both of research and instruction, the variable and dynamic nature of students’ thought processes poses a significant challenge to PER. It is difficult merely to assess and characterize the diverse phases of students' thinking as they gain and express understanding of a concept. (We might call this the “kinematics” of students' thought processes.) Much harder still is uncovering the various factors (instructional method, student characteristics, etc.) that influence and determine the trajectory of students' thinking, and deciphering the mutual interaction of these factors. (We could call this the “dynamics” of students' thinking.) I will outline some of the initial work that has been done along these lines by various researchers, and I will identify some directions for future research that I think might be fruitful for workers in PER .

TP-A3
Synthesis in PER: How does it all fit together?
Edward F. Redish (redish@umd.edu), University of Maryland
Abstract: We often say that as physics education researchers, we are applying the methods of science to help up understand how our students learn and do not learn physics. Often, however, our “application of the scientific method” is restricted to observing what our students do and trying to correlate their learning with instructional changes that seem, intuitively, to make sense to us. It is more like “seat-of-the-pants” engineering than like physics; more like Edison’s search for the proper filament for a light bulb than like the current attempt to understand spintronics in order to (eventually) build a better microchip. In true science research, our experiment and theory perform an intricate dance, with theory at one time taking the lead and suggesting experiments, at another time with experiment taking the lead and producing results that demand new theoretical explanations. Very little of what we do in PER resembles this complex and productive interplay of theory and experiment. The big problem seems to be the lack of a serious theoretical frame. Without a serious theoretical frame we are unable to synthesize, unable to generate reliable predictions in situations we haven’t observed, and unable to understand what our experimental results are telling us. What theory do we need to know and/or develop in order to be able to move into a more productive and more scientific mode of research?