Reality-based interaction affecting mental workload in virtual reality mental arithmetic training

ABSTRACT

The concept of digital game-based learning (DGBL) evolves rapidly together with technological enhancements of virtual reality (VR) and smart phones. However, the mental workload (MWL) that VR-training applications demand and motivational qualities originating from user experience (UX) should be identified in order to create effective and enjoyable training/learning challenges that fit with individual users’ capabilities. This study examined the effects of reality-based interaction (RBI) and VR on measures of student motivation and MWL, in a mental arithmetic game for secondary school pupils. In a randomised controlled trial with sixty school children, a mental arithmetic game was tested with three different interaction and two different presentation methods – VR RBI, VR head-mounted-display tapping and tablet flick-gesture. Results found a significant effect of RBI on MWL but no differences in enjoyment of training were found between VR-experience and tablet training-experience. In fact, adding the gaming-context to the mental arithmetic task created an enjoyable, motivating experience regardless of presentation or interaction-style.     

Irreversible deformation and the superplasticity of a TN-1 alloy during thermal cycling through the martensitic transformations ranges under loading

The influence of the thermal cycling conditions on the thermal-cycling creep of a TN-1 alloy and the related irreversible deformations is studied. The conditions under which an anomalous increase in the irreversible deformations begins are determined. The structural mechanism of the irreversible deformations of an equiatomic alloy is shown to be analogous to the structural mechanism of metal creep at high temperatures: it predominantly has a dislocation character. It is proposed to use the effect of anomalous increase in the deformation of materials with reversible martensitic transformations for forming parts made of these materials at low temperatures.     

A conceptualization of intended learning outcomes supporting self‐regulated learners in indicating learning paths

Intended learning outcomes (ILOs) indicate what learners will be able to achieve after they are taught. Traditionally, ILOs are expressed as plain text or unstructured documents. What if all ILOs of a specific course of study can be conceptualized through a structured diagrammatic technique? It was hypothesized that learners can benefit from this conceptualization in learning, especially in self‐regulated learning. The aim of this study was to investigate whether the ILOs represented in unstructured or structured formats can facilitate learners to identify learning paths. The results revealed that the mean ratings of all learning paths were statistically significantly higher with structured ILOs.     

Context-Based Path Prediction for Targets with Switching Dynamics

International Journal of Computer Vision - Anticipating future situations from streaming sensor data is a key perception challenge for mobile robotics and automated vehicles. We address the problem...