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In this article, we introduce how eye-tracking technology might become a promising tool to teach programming skills, such as debugging with ‘Eye Movement Modeling Examples’ (EMME). EMME are tutorial videos that visualize an expert's (e.g., a programming teacher's) eye movements during task performance to guide students’ attention, e.g., as a moving dot or circle. We first introduce the general idea behind the EMME method and present studies that showed first promising results regarding the benefits of EMME to support programming education. However, we argue that the instructional design of EMME varies notably across them, as evidence-based guidelines on how to create effective EMME are often lacking. As an example, we present our ongoing research on the effects of different ways to instruct the EMME model prior to video creation. Finally, we highlight open questions for future investigations that could help improving the design of EMME for (programming) education.
The sandfish (Scincus scincus) is a lizard having the remarkable ability to move through desert sand for significant distances. It is well adapted to living in loose sand by virtue of a combination of morphological and behavioural specializations. We investigated the bodyform of the sandfish using 3D-laserscanning and explored its locomotion in loose desert sand using fast nuclear magnetic resonance (NMR) imaging. The sandfish exhibits an in-plane meandering motion with a frequency of about 3 Hz and an amplitude of about half its body length accompanied by swimming-like (or trotting) movements of its limbs. No torsion of the body was observed, a movement required for a digging-behaviour. Simple calculations based on the Janssen model for granular material related to our findings on bodyform and locomotor behaviour render a local decompaction of the sand surrounding the moving sandfish very likely. Thus the sand locally behaves as a viscous fluid and not as a solid material. In this fluidised sand the sandfish is able to “swim” using its limbs.
This study has been performed to design the combination of the new ClearPET (ClearPET is a trademark of the Crystal Clear Collaboration), a small animal positron emission tomography (PET) system, with a micro-computed tomography (microCT) scanner. The properties of different microCT systems have been determined by simulations based on GEANT4. We will demonstrate the influence of the detector material and the X-ray spectrum on the obtained contrast. Four different detector materials (selenium, cadmium zinc telluride, cesium iodide and gadolinium oxysulfide) and two X-ray spectra (a molybdenum and a tungsten source) have been considered. The spectra have also been modified by aluminum filters of varying thickness. The contrast between different tissue types (water, air, brain, bone and fat) has been simulated by using a suitable phantom. The results indicate the possibility to improve the image contrast in microCT by an optimized combination of the X-ray source and detector material.
This study has been performed to design the combination of the new ClearPET TM (ClearPET is a trademark of the Crystal Clear Collaboration), a small animal Positron Emission Tomography (PET) system, with a microComputed Tomography (microCT) scanner. The properties of different microCT systems have been determined by simulations based on GEANT4. We demonstrate the influence of the detector material and the X-ray spectrum on the obtained contrast. Four different detector materials (selenium, cadmium zinc telluride, cesium iodide and gadolinium oxysulfide) and two X-ray spectra (a molybdenum and a tungsten source) have been considered. The spectra have also been modified by aluminum filters of varying thickness. The contrast between different tissue types (water, air, brain, bone and fat) has been simulated by using a suitable phantom. The results indicate the possibility to improve the image contrast in microCT by an optimized combination of the X-ray source and detector material.