Computational science for undergraduate biologists via QUT.Bio.Excel

Molecular biology is a scientific discipline which has changed fundamentally in character over the past decade to rely on large scale datasets – public and locally generated - and their computational analysis and annotation. Undergraduate education of biologists must increasingly couple this domain context with a data-driven computational scientific method. Yet modern programming and scripting languages and rich computational environments such as R and MATLAB present significant barriers to those with limited exposure to computer science, and may require substantial tutorial assistance over an extended period if progress is to be made. In this paper we report our experience of undergraduate bioinformatics education using the familiar, ubiquitous spreadsheet environment of Microsoft Excel. We describe a configurable extension called QUT.Bio.Excel, a custom ribbon, supporting a rich set of data sources, external tools and interactive processing within the spreadsheet, and a range of problems to demonstrate its utility and success in addressing the needs of students over their studies.

Renewing undergraduate IT education

Information Technology (IT) education is in crisis. Enrolments have dropped by up to as much as 70% at some universities (Markoff, 2009). This coupled with traditionally high attrition and failure rates (Biggers et al, 2008) is resulting in the number of graduates nationwide being far lower than industry demand (Queensland Government SkillsInfo Report, 2009). This work reports on a radical redesign of the Bachelor of IT degree at QUT. The initial results are very promising with attrition in first year dropping from being one of the highest at QUT for an undergraduate degree to being one of the lowest. The redesign followed an action research model to reflect on issues and problems with the previous version of the degree and to introduce changes to attempt to rectify some of these problems. The resulting degree intends to produce "business savvy" graduates who are capable of using their IT knowledge and skills within cross-functional teams to solve complex problems.

Don't think but look : a Gestalt interactionist approach to legal thinking

We propose here a new approach to legal thinking that is based on principles of Gestalt perception. Using a Gestalt view of perception, which sees perception as the process of building a conceptual representation of the given stimulus, we articulate legal thinking as the process of building a representation for the given facts of a case. We propose a model in which top-down and bottom-up processes interact together to build arguments (or representations) in legal thinking. We discuss some implications of our approach, especially with respect to modeling precedential reasoning and creativity in legal thinking.