Persuasive Design in Teaching and Learning

The EuroPLOT project (2010-2013) has developed Persuasive Learning and Technologies (PLOTs) and has evaluated them in four real-world case studies, which cover the widely different teaching scenarios of university education, adult learning in industry, informal learning at a museum, literature studies, and language learning. At the International Workshop of EuroPLOT Persuasive Technology for Learning, Education and Teaching (IWEPLET 2013), the results of the project were presented, and an overview of related research was given. One of the main conclusions of EuroPLOT has been that the specific learning context has to be considered when applying persuasive designs. At IWEPLET 2013, both the theoretical background as well as evaluations of persuasive technology demonstrations were presented. This paper provides an overview of these presentations

Experimental Measures of Affine and Non-affine Deformation in Granular Shear

Through 2D granular Couette flow experiments, we probe failure and deformation of disordered solids under shear. Shear produces smooth affine deformations in such a solid and also irresversible so-called non-affine particle displacements. We examine both processes. We show that the non-affine part is associated with diffusion, and also can be used to define a granular temperature. Distributions for single particle non-affine displacements, \dri, satisfy P_1(\dri) \propto \exp [-|\dri/\Delta r|^{\alpha}] ($\alpha \stackrel{<}{\sim} 2$). We suggest that the shear band forms due to a radially outward diffusive flux/non-affine motion which is balanced in the steady state by inward diffusion due to density gradients.Comment: 4 pages, 5 figure

Refractive Index Matched Scanning and Detection of Soft Particle

We describe here how to apply the three dimensional imaging technique of refrecative index matched scanning to hydrogel spheres. Hydrogels are water based materials with a low refractive index, which allows for index matching with water-based solvent mixtures. We discuss here various experimental techniques required to handle specifically hydrogel spheres as opposed to other transparent materials. The deformability of hydrogel spheres makes their identification in three dimensional images non-trivial. We will also discuss numerical techniques that can be used in general to detect contacting, non-spherical particles in a three dimensional image. The experimental and numerical techniques presented here give experimental access to the stress tensor of a packing of deformed particles.Comment: 9 pages, 9 figures, submitted to review of scientific instruments, Issue 1

Fluctuations in Shear-Jammed States: A Statistical Ensemble Approach

Granular matter exists out of thermal equilibrium, i.e. it is athermal. While conventional equilibrium statistical mechanics is not useful for characterizing granular materials, the idea of constructing a statistical ensemble analogous to its equilibrium counterpart to describe static granular matter was proposed by Edwards and Oakshott more than two decades ago. Recent years have seen several implementations of this idea. One of these is the stress ensemble, which is based on properties of the force moment tensor, and applies to frictional and frictionless grains. We demonstrate the full utility of this statistical framework in shear jammed (SJ) experimental states [1,2], a special class of granular solids created by pure shear, which is a strictly non-equilbrium protocol for creating solids. We demonstrate that the stress ensemble provides an excellent quantitative description of fluctuations in experimental SJ states. We show that the stress fluctuations are controlled by a single tensorial quantity: the angoricity of the system, which is a direct analog of the thermodynamic temperature. SJ states exhibit significant correlations in local stresses and are thus inherently different from density-driven, isotropically jammed (IJ) states.Comment: 6 pages, 4 figure

Why Do Granular Materials Stiffen with Shear Rate? : Test of Novel Stress-Based Statistics

Peer reviewedPublisher PD