Learning by Teaching SimStudent: Technical Accomplishments and an Initial Use with Students

The purpose of the current study is to test whether we could create a system where students can learn by teaching a live machine-learning agent, called SimStudent. SimStudent is a computer agent that interactively learns cognitive skills through its own tutored-problem solving experience. We have developed a game-like learning environment where students learn algebra equations by tutoring SimStudent. While Simulated Students, Teachable Agents and Learning Companion systems have been created, our study is unique that it genuinely learns skills from student input. This paper describes the overview of the learning environment and some results from an evaluation study. The study showed that after tutoring SimStudent, the students improved their performance on equation solving. The number of correct answers on the error detection items was also significantly improved. On average students spent 70.0 minutes on tutoring SimStudent and used an average of 15 problems for tutoring. © Springer-Verlag Berlin Heidelberg 2010

First Ground-Based Validation of SCIAMACHY V5.01 Ozone Column

In early 2004, the near real-time data processor of ENVISAT SCIAMACHY (SCI_NL) was upgraded to version 5.01. Based on the correlative measurements acquired and collected during the commissioning phase of the satellite in 2002, a preliminary validation was organised to verify the improvement and assess the geophysical consistency of the new SCIAMACHY ozone vertical column data product. The present overview summarises the results obtained by a list of validation teams and involving ground-based data acquired from pole to pole by complementary ground-based sensors. The studies conclude to an improvement compared to previous versions 3.5x. They also confirm the presence of expected errors (e.g. dependence on solar elevation and on ozone column) inherited from the GOME Data Processor GDP 2.4, on which the SCIAMACHY processor SCI_NL is based

Learning by Teaching SimStudent: Technical Accomplishments and an Initial Use with Students

The purpose of the current study is to test whether we could create a system where students can learn by teaching a live machine-learning agent, called SimStudent. SimStudent is a computer agent that interactively learns cognitive skills through its own tutored-problem solving experience. We have developed a game-like learning environment where students learn algebra equations by tutoring SimStudent. While Simulated Students, Teachable Agents and Learning Companion systems have been created, our study is unique that it genuinely learns skills from student input. This paper describes the overview of the learning environment and some results from an evaluation study. The study showed that after tutoring SimStudent, the students improved their performance on equation solving. The number of correct answers on the error detection items was also significantly improved. On average students spent 70.0 minutes on tutoring SimStudent and used an average of 15 problems for tutoring. © Springer-Verlag Berlin Heidelberg 2010

Measurements from ground and balloons during APE-GAIA – A polar ozone library

Many long-term monitoring sites in Antarctic regions, which deploy ground-based stratospheric remote sensors and fly radiosondes or ozonesondes on balloons, supported the Airborne Polar Experiment in September and October 1999. Support consisted of supplying data to the campaign in real time, and in some cases by increasing the frequency of measurements during the campaign. The results will strengthen scientific conclusions from the airborne measurements. But results from these sites are allowing important scientific studies of new aspects of the ozone hole in their own right, because like the aircraft and its campaign, many sites traverse the vortex edge and are close to the largest source of lee waves, or measure infrequently observed trace gases such as HNO3. Examples of such studies are the behaviour and value of NO2 in midwinter, ozone filamentation with no apparent horizontal advection, the frequency and amplitude of gravity waves over the Antarctic Peninsula, mixing in the lowest stratosphere in Antarctic spring, the mechanism and frequency of HNO3 enhancement above the ozone peak in midwinter, and trends in UV dose in southern South America

Equations, contractions, and unique solutions

One of the most studied behavioural equivalences is bisimilarity. Its success is much due to the associated bisimulation proof method, which can be further enhanced by means of 'up-to bisimulation' techniques such as 'up-to context'. A different proof method is discussed, based on unique solution of special forms of inequations called contractions, and inspired by Milner's theorem on unique solution of equations. The method is as powerful as the bisimulation proof method and its 'up-to context' enhancements. The definition of contraction can be transferred onto other behavioural equivalences, possibly contextual and noncoinductive. This enables a coinductive reasoning style on such equivalences, either by applying the method based on unique solution of contractions, or by injecting appropriate contraction preorders into the bisimulation game. The techniques are illustrated on CCS-like languages; an example dealing with higher-order languages is also shown