1. Understanding life science majors’ ideas about diffusion
Samuel Luke Tunstall, 1 Abhilash Nair,2 Kathleen Hinko,3,2 Paul Irving,2 and Vashti Sawtelle 3,2
1Mathematics Education, Michigan State University, 220 Trowbridge Rd, East Lansing, MI USA 48824
2Department of Physics & Astronomy, Michigan State University, 567 Wilson Rd, East Lansing, MI USA 48824
3Lyman Briggs College, Michigan State University, 919 E. Shaw Ln, East Lansing, MI USA 48824
Diffusion as an Interdisciplinary Thread
Incoming Resource Analysis
Links between Resources
Synthesizing relationships between the content of various disciplines is an increasingly important skill within science education, especially in relating chemistry, biology, and physics.
Diffusion is one concept (among many) that arises in multiple contexts in science courses for undergraduates [1]. However, to date, only one study has explored students’ understanding of diffusion in a physics context [2].
The purpose of the present study was to explore life science majors’ incoming conceptions of diffusion, the goal being to leverage that understanding for present and future instruction.
An odds ratio of 1 or lower for two resources a and b indicates that a has a likelihood that is not mathematically affected by the presence of resource b.
Table 1. Pre-semester diffusion conceptions.
Conception of diffusion
Percentage of students (n = 119)
High-to-low concentration
84%
Relates to energy
55%
Balance or equilibrium
50%
Spreading or dispersing of particles
39%
Dynamic
30%
Randomness
27%
Concentration
16%
Collisions
11%
Spreading of energy or momentum
10%
Entropy 8%
Key Results.
The majority of students came in with conceptions of diffusion tied to their course experiences in biology and chemistry.
Most students noted at least two resources, and the majority (71%) had at least three resources they articulated in their response.
Few students discussed collisions or the spreading of energy or momentum in their description of diffusion.
Table 2. Notable confidence intervals for odds ratios
Resource pair (a; b) read as “a, given b”
Confidence interval for odds ratio
Relates to energy; spreading of particles
Entropy; relates to energy
Collisions; spreading of energy/momentum
Collisions; high-to-low
Chemistry
Equilibrium in solutions
Concentration gradients
Entropy
Biology
Active and passive transport
Osmosis
Physics
Collisions
Probabilistic motion
Key Results.
The 100 students who used ”high-to-low” as a resource were significantly less likely to have also discussed collisions.
Those whose responses included the spreading out of things other than particles, as well as those who described the process as dynamic, were more likely to have included collisions in their response.
Figure 1. Common concepts or contexts for diffusion in introductory science coursework.
Future Work
Theoretical Framing
Instructional Unit on Simulating Diffusion
We approach the question of student ideas
about diffusion from a resources perspective [3]. This perspective allows us to focus our instructional design on modifying the resources students activate and to consider what additional conceptual resources students might need to be activated.
From this work, we will modify a week-long instructional unit centered on computation and diffusion. It will expand on student initial ideas of diffusion and focus on developing and activating resources of elastic collisions and entropically-driven processes.
Unit begins with PER-based investigations into conservation of momentum [5]
Transitions to analytic problems asking students to consider the relevant transfer of momentum in a two-particle collision
Simulations begin by modeling this two-particle collision
Next we increase the number of particles and ask students to confine the collisions to a box
Finally students work with a program that models two different types of particles in a box
References
Method
[1] J. Shen, O. L. Liu, and S. Sung, ”Designing interdisciplinary assessments in sciences for college students: An example on
osmosis,” International Journal of Science Education 36, (2014).
[2] B. W. Dreyfus, B. D. Geller, D. E. Meltzer, and V. Sawtelle, ”Resource letter TTSM-1: Teaching thermodynamics and statistical mechanics in introductory physics, chemistry, and biology,” American Journal of Physics 83, 5-21 (2014).
[3] D. Hammer, ”Student resources for learning introductory physics,” American Journal of Physics 68, S52-S59 (2000).
[4] J. A. Morris and M. J. Gardner, ”Statistics in Medicine: Calculating confidence intervals for relative risks (odds ratios) and standardised ratios and rates,” British Medical Journal (Clinical Research Ed.) 296, (1988).
[5] The Modeling Collaboration
Course Context. Introductory physics for life science majors, primarily taken by biology and chemistry majors
Primary Data : Beginning-of-semester assignment asking students to “put together a definition of diffusion.”
Analytical Approach:
Open coding for emergent resources
Use of odds ratios [4] and associated confidence intervals to determine the probability that—within the dataset—students who employed one resource also employed another
The lead author acknowledges MSU’s Graduate School for funding this project. We also thank Lisa Lapidus for her contributions to the computational activities