Pedagogical principles for the design of virtual learning spaces in higher education

This paper focuses on effective learning spaces in contemporary higher education. Drawing on empirical data from a qualitative study of international students’ experience of blended learning programs conducted in three computing courses in two Australian universities, a range of issues and challenges are reported. Three pedagogical principles are then presented that respond to these challenges: 1. Enabling learners – learning how to learn in virtual learning spaces; 2. Programming for flexible learning – learning how to manage virtual learning environments; and, 3. Transforming learning – learning how to capitalise on the affordances of new technologies. The pedagogical principles are presented together with examples of types of practices that they support.

First-principles based force-field for the interaction of proteins with Au(100)(5 x 1): an extension of GolP-CHARMM

Noncovalent recognition between peptides and inorganic materials is an established phenomenon. Key to exploiting these interactions in a wide range of materials self-assembly applications would be to harness the facet-selective control of peptide binding onto these materials. Fundamental understanding of what drives facet-selectivity in peptide binding is developing, but as yet is not sufficient to enable design of predictable facet-specific sequences. Computational simulation of the aqueous peptide-gold interface, commonly used to understand the mechanisms driving adsorption at an atomic level, has thus far neglected the role that surface reconstruction might play in facet specificity. Here the polarizable GolP-CHARMM suite of force fields is extended to include the reconstructed Au(100) surface. The force field, compatible with the bio-organic force field CHARMM, is parametrized using first-principles data. Our extended force field is tailored to reproduce the heterogeneity of weak chemisorbing N and S species to specific locations in the Au(100)(5 × 1) surface identified from the first-principles calculations. We apply our new model to predict and compare the three-dimensional structure of liquid water at Au(111), Au(100)(1 × 1), and Au(100)(5 × 1) interfaces. Using molecular dynamics simulations, we predict an increased likelihood for water-mediated peptide adsorption at the aqueous-Au(100)(1 × 1) interface compared with the Au(100)(5 × 1) interface. Therefore, our findings suggest that peptide binding can discriminate between the native and reconstructed Au(100) interfaces and that the role of reconstruction on binding at the Au(100) interface should not be neglected. © 2013 American Chemical Society.