Pupils' Interaction with the Exhibits According to the Learning Behaviour Model

Science centres are one of the best opportunities for informal study of natural science. There are many advantages to learn in the science centres compared with the traditional methods: it is possible to motivate and supply visitors with the social experience, to improve people’s understandings and attitudes, thereby bringing on and attaching wider interest towards natural science. In the science centres, pupils show interest, enthusiasm, motivation, self-confidence, sensitiveness and also they are more open and eager to learn. Traditional school-classes however mostly do not favour these capabilities. This research presents the qualitative study in the science centre. Data was gathered from observations and interviews at Science North science centre in Canada. Pupils’ learning behaviours were studied at different exhibits in the science centre. Learning behaviours are classified as follows: labels reading, experimenting with the exhibits, observing others or exhibit, using guide, repeating the activity, positive emotional response, acknowledged relevance, seeking and sharing information. In this research, it became clear that in general pupils do not read labels; in most cases pupils do not use the guides help; pupils prefer exhibits that enable high level of interactivity; pupils display more learning behaviours at exhibits that enable a high level of interactivity.

A pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion

Objective Levodopa in presence of decarboxylase inhibitors is following two-compartment kinetics and its effect is typically modelled using sigmoid Emax models. Pharmacokinetic modelling of the absorption phase of oral distributions is problematic because of irregular gastric emptying. The purpose of this work was to identify and estimate a population pharmacokinetic- pharmacodynamic model for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Methods The modelling involved pooling data from two studies and fixing some parameters to values found in literature (Chan et al. J Pharmacokinet Pharmacodyn. 2005 Aug;32(3-4):307-31). The first study involved 12 patients on 3 occasions and is described in Nyholm et al. Clinical Neuropharmacology 2003:26:156-63. The second study, PEDAL, involved 3 patients on 2 occasions. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Plasma samples and motor ratings (clinical assessment of motor function from video recordings on a treatment response scale between -3 and 3, where -3 represents severe parkinsonism and 3 represents severe dyskinesia.) were repeatedly collected until the clinical effect was back at baseline. At this point, the usual infusion rate was started and sampling continued for another two hours. Different structural absorption models and effect models were evaluated using the value of the objective function in the NONMEM package. Population mean parameter values, standard error of estimates (SE) and if possible, interindividual/interoccasion variability (IIV/IOV) were estimated. Results Our results indicate that Duodopa absorption can be modelled with an absorption compartment with an added bioavailability fraction and a lag time. The most successful effect model was of sigmoid Emax type with a steep Hill coefficient and an effect compartment delay. Estimated parameter values are presented in the table. Conclusions The absorption and effect models were reasonably successful in fitting observed data and can be used in simulation experiments.