There is a flat list of the 175 tasks currently available with few constraints on how they can be used. This gives students freedom in the experiments they design. Some of the tasks apply treatments, such as giving the subject a tablet containing 1 mg of alprazolam or making them swim freestyle for 200 m. These do not show any output in the interface but the tasks have changed the state of the Islander in the simulation. Since the simulation happens in real time the students need to wait to observe effects. Other tasks then produce data, such as measuring blood pressure or pulse rate, or taking a blood or urine sample to detect a particular substance. The onus is on the student to develop the protocol for applying the treatments and making the measurements. In addition to tasks that mostly behaved like measurements, the students could also design a survey for their Islanders to complete. Questions that students were interested in asking were added to the system, along with a range of standard survey questions that we typically ask the students themselves . The Islanders would take longer to complete longer surveys, discouraging students from just asking all the questions. Some Islanders were predisposed to lie on the surveys,vertical farm systems particular for questions related to age and weight. Students can always tell they are lying because the actual age of each Islander is displayed on the profile and there is a measurement task for weighing an Islander. There is also a chance that an Islander will decline to respond to a survey. This chance varies between the different cultural groups on the Island making a pattern in non-response bias for students to explore.

The instructor can see all tasks assigned by an individual student to each Islander they used as well as Islanders that have been visited by the student but who have not had any tasks assigned to them . These monitoring tools provide a useful level of accountability for individual student work and also give the instructor a broad insight into how the environment is being used by their class.Villages and individuals, tasks and results are all navigated through mouse clicks on a web browser. This has made the Island well suited to the many mobile devices that now have touchscreen interfaces. For example, although it was released after the Island was conceived, the iPad has been an ideal hardware interface to the Island. Mobile devices are also useful with the Island since the experimental simulations run in real time. For example, students can allocate their treatments to subjects during group work in a computer lab and are then able to check on the subjects, such as monitoring blood pressure or some hormone level, while riding on a bus. The Islanders have a pair of chromosomes that they inherit in the usual way from their parents. The 256 ‘genes’ on each these chromosomes are used to determine a variety of attributes, including the physical characteristics seen in Figures 1, measures of disease susceptibility, and other parameters required by the task simulations described in Section 3.2. We give students access to this genetic information through a task that generates the analog of a micro-array image for one or both of the chromosomes. Students can use this task to carry out studies that mirror micro-array techniques in the real world. For example, Bulmer and Meiring describe a student project that looked for evidence of a gene linked to diabetes on the Island. In that study the student obtained micro-array images for 10 Islanders with diabetes and 10 without, giving the results shown in Figure 3.

The question is whether there is any systematic difference between the intensity levels expressed in each set of images. Figure 4 shows a more quantitative summary of the results with side-by-side box plots for each of the 256 genes appearing in the micro-arrays. For convenience we label the positions with B000 at top left, along to B015 at top right and then continuing by rows to B255 at bottom right. The student carried out a two-sample t test to compare the levels between the subjects with diabetes and those without for each of these. The four strongest effects were for genes B116 , B041 , B186 and B118 . Figure 5 shows the box plots for these four comparisons in more detail. For B116 the intensity distribution for non-diabetics seems uniform while it appears systematically lower for diabetics. We now use this student study as an example in class. Of course the p-value for B116 needs to be treated by caution since it arose from a large number of multiple comparisons. In our introductory course we use the very conservative Bonferroni adjustment to the p-values, whereby B116 becomes non-significant, but the overall example illustrates to students the practical issues involved in this kind of screening as well as an area of current research in the discipline of statistics itself. A great advantage of this approach is that new students can replicate the study if they want, or search for other similar genes.Our final example illustrates the open-endedness of the Island through a new measurement devised by a student based on the existing data. The student was interested in possible risk factors for smoking and she wanted to test the hypothesis that major life-changing events could increase the incidence of smoking due to stress. Using a sample of 40 Islanders, she counted the number of life-changing events each of them had experienced. She defined these to be any of illnesses, marriages, child births, loss of spouses and migration between villages. She recorded their current smoking status and then looked for a relationship between the two variables. A logistic model for the relationship is shown in Figure 6. This was an interesting outcome for the student since the conclusion was the opposite of her original hypothesis: there was significant evidence that Islanders with higher numbers of life-changing events were actually less likely to be smokers. However it was also a very interesting outcome for the authors because this relationship was not an explicit part of any of the simulation models.

This emergent phenomenon is most likely an example of survival bias in the results since smokers tend to die younger and so ultimately have less time to experience life-changing events. Future students can replicate this study and try to adjust for age, for example, to confirm whether this is the case. Student feedback to the Island has been very positive. In our context the role of it has been to replace real experiments and this is reflected in many comments such as that “they were interesting and a great way to find results of experiments. It made the experimentation process nice and easy to conduct”. However students were also engaged with the Islanders beyond a basic tool for generating data: “I liked how we were able to see their whole history on their profiles; it was interesting seeing some of their troubled past”. As mentioned earlier, we do have a tension between reality and fantasy in our design and it was interesting to read comments on the reality aspect, such as that “the Islanders were a little too real,vertical farming cost especially as they improved reaction times after repeating the action. We really had to think of them as real people – which I suppose was the whole point”. In contrast there have not been open comments on the ‘unreal’ aspects, such as the Islanders with elven ears or the unusual disease names. We suspect that students are used to these features in computer games and are not surprised by them. This is an interesting area for future studies. The consistent negative feedback has been on the Islanders sleeping each night. While some students were interested in studying sleep, as in the dextroamphetamine example above, for the majority of students the fact that the Islanders go into an uninterruptible sleep each night is often a nuisance. At this stage we are continuing to include this constraint, as part of our general philosophy summarized in the following section. However we have made the Islanders go to bed a bit later each night and have introduced some tasks that can be performed on sleeping Islanders, such as the various blood tests and a simple polysomnography tool, so that students are not completely stuck if they have left their project until the night before it is due. In general it is not surprising that the Island has been successful in engaging students with the task for which it was designed. We are interested now in evaluations from other users of the Island in contexts different from our own. For example, Linden et al.give outcomes of a research grant that has investigated the use of the Island as a tool in teaching clinical trial design and management. Edwards and Crowther give an evaluation of the Island in a health systems management course where the focus was not on statistical reasoning at all. Such projects give insight into the transferability of the tool while also feeding back ideas to further expand the models included in the simulated environment. Bulmer gives more details regarding this collaborative approach. Various preparations of the leaves, flowers and resinous extracts of the Cannabis plant have been consumed for both medical and recreational purposes since antiquity. Extensive research efforts aiming to explain the widespread therapeutic and behavioral effects evoked by Cannabis consumption finally led to the discovery of a new messenger system called the endocannabinoid system. It is composed of the CB1 and CB2 cannabinoid receptors , which are not only targets of the psychoactive compounds of the Cannabis plant, but more importantly, they are also activated by two endogenous lipid molecules produced by most cell types in the body . The mobilization and elimination of these two endocannabinoid molecules called N arachidonoylethanolamine and 2-arachidonoylglycerol are tightly regulated by surprisingly complex networks of metabolic enzymes and pathways in different cell types and tissues .

Following the clinical failure of brain-penetrating CB1 receptor antagonists as therapeutics due to adverse psychiatric effects, the identification of novel molecular players regulating endocannabinoid levels has opened new possibilities, because drugs targeting these enzymes may have more selective actions . The wide spectrum of human neurological and psychiatric diseases in which the endocannabinoid system is implicated suggests a vast therapeutic potential . However, to take advantage of this potential requires full characterization of the enzymes regulating endocannabinoid signaling in the human brain. A conceptual framework describing the major aspects of neuronal endocannabinoid signaling has emerged from the results of numerous animal studies in the last decade. In contrast to conventional neurotransmitters, endocannabinoids are primarily synthesized and released by postsynaptic neurons in an on-demand manner , and subsequently activate presynaptically located CB1 cannabinoid receptors, thereby regulating neurotransmitter release from several types of axon terminals . This retrograde manner of synaptic endocannabinoid signaling is indispensable for various forms of homo- and heterosynaptic plasticity throughout the central nervous system , and probably accounts for the extensive involvement of the endocannabinoid system in brain disorders . Thus, molecular mechanisms regulating synaptic endocannabinoid signaling may be of pivotal importance in the therapeutic exploitation of the endocannabinoid system. Although anandamide is the archetypical endocannabinoid molecule , and may tonically control presynaptic CB1 receptors , most experimental evidence converge on the notion that 2-AG is the crucial retrograde messenger mediating on-demand forms of short- and long-term synaptic depression through CB1 activation. Pharmacological inhibition of diacylglycerol lipase, including its alpha isoform, the enzyme primarily responsible for 2-AG biosynthesis in adult brain , prevents retrograde endocannabinoid signaling in various experimental paradigms throughout the cerebral cortex . Particularly compelling support for this concept also derives from the genetic inactivation of DGL-α, which completely abolishes endocannabinoid-mediated synaptic plasticity, for example in the hippocampus . Conversely, pharmacological blockade of monoacylglycerol lipase , the enzyme responsible for inactivation of the major fraction of 2-AG in the brain , prolongs retrograde endocannabinoid signaling in distinct types of synapses . Widespread distribution of 2-AG in the human brain has recently been revealed with a largely overlapping regional pattern to CB1 receptors based on radioligand binding and in situ hybridization experiments .