ABSTRACT:Retention and passing rates as well as student engagement in computer programming and problem solving units are a major concern in tertiary spatial science courses. A number of initiatives were implemented to improve this. A pilot study reviews the changes made to the teaching and learning environment, including the addition of new resources and modifications to assessments, and investigates their effectiveness. In particular, the study focuses on the differences between students studying in traditional, oncampus mode and distance, e-learning mode. Student results and retention rates from 2009-2011, data from in-lecture clicker response units and two anonymous surveys collected in 2011 were analysed. Early results indicate that grades improved for engaged students but pass rates or grades of the struggling cohort of students did not improve significantly.

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As the availability and utilisation of online data blossoms, automated online searches-whether to answer a simple question, seek specific sensor readings, or investigate research in a particular domain-have raised a number of issues. Simple search tools do not access the deep web of services and online forms, and cannot handle knowledge domain-specific search problems, but specialist search tools can have a narrow domain and applicability. Some online tools circumvent these problems by putting more filter controls into the hands of users, but this leads to more complex interfaces which can raise usability barriers. A distributed approach, where specialised search agents act autonomously to find contextualised information, can provide a useful compromise between a simple, general search interface and specialist searches. This paper outlines work in progress on design and use of specialist search agents, with a case study to find public transportation bus stops within a spatial region. The approach is demonstrated with a proof of concept web interface, developed to interpret a text query to find and show bus stop locations within a named boundary by coordinating multiple online search agents. Search agents were designed to follow a common model to allow for future development of agent types, including specialist agents used in the case study to search standard open web services and extract spatial features.