The educational landscape is an environment prone to change due to the volatile and ever-changing nature of the digital society in which we all live. Although the world moves at different speeds and any generalization is bound to have some exceptions, there is evidence from research conducted in different places and contexts that educational methods are becoming increasingly digitized and driven by technological innovation. Among the technological trends fueled in many cases by the COVID-19 pandemic and the need to stay at home but online, augmented reality solutions received an additional boost as a valid and versatile educational technology worth exploring and eventually integrating into several teaching methods already in use. Although the technology still faces problems related to affordability, accessibility, and the technical skills required of users, some ongoing projects have already provided evidence that using augmented reality solutions as teaching and learning tools can improve teacher and student learning outcomes by increasing engagement and interactivity. The same issues arose when personal computers, tablets, and smartphones were first discussed as valuable tools for education and have now found their way into most classrooms. This paper reviews some of the key concepts related to augmented reality, as well as some current trends, benefits, and concerns related to its integration into educational contexts in areas such as life sciences, engineering, and health. The work conducted and presented in this paper provides an interesting insight into a technology that has given rise to global phenomena such as Pokémon Go, and continues to improve in terms of portability, usability, and overall user experience. Throughout the paper and in the conclusion section, we discuss the relevance of using the best features of augmented reality and how they can contribute to positive educational outcomes.

The need for objective data-driven usability testing of VR applications is becoming more tangible with the rapid development of numerous VR applications and their increased accessibility. Traditional methods of testing are too time and resource consuming and might provide results that are highly subjective. Thus, the aim of this article is to explore the possibility of automation of usability testing of VR applications by using objective features such as HMD built-in head and hands tracking, EEG sensor, video recording, and other measurable parameters in addition to automated analysis of subjective data provided in questionnaires. For this purpose, a simple VR application was created which comprised relatively easy tasks that did not generate stress for the users. Fourteen volunteers took part in the study and their signals were monitored to acquire objective automated data. At the same time the observer was taking notes of subjects’ behaviour, and their subjective opinions about the experience were recorded in a post-experiment questionnaire. The results acquired from signal monitoring and questionnaires were juxtaposed with observation and post-interview results to confirm the validity and efficacy of automated usability testing. The results were very promising, proving that automated usability testing of VR applications is potentially achievable.

This paper investigates the use of an electroencephalogram (EEG) signal to classify a subject’s stress level while using virtual reality (VR). For this purpose, we designed an acquisition protocol based on alternating relaxing and stressful scenes in the form of a VR interactive simulation, accompanied by an EEG headset to monitor the subject’s psycho-physical condition. Relaxation scenes were developed based on scenarios created for psychotherapy treatment utilizing bilateral stimulation, while the Stroop test worked as a stressor. The experiment was conducted on a group of 28 healthy adult volunteers (office workers), participating in a VR session. Subjects’ EEG signal was continuously monitored using the EMOTIV EPOC Flex wireless EEG head cap system. After the session, volunteers were asked to re-fill questionnaires regarding the current stress level and mood. Then, we classified the stress level using a convolutional neural network (CNN) and compared the classification performance with conventional machine learning algorithms. The best results were obtained considering all brain waves (96.42%) with a multilayer perceptron (MLP) and Support Vector Machine (SVM) classifiers.

The goal of this research is to integrate Virtual Reality (VR) with the bilateral stimulation used in EMDR as a tool to relieve stress. We created a 15 minutes relaxation training program for adults in a virtual, relaxing environment in form of a walk in the woods. The target platform for the tool is HTC Vive, however it can be easily ported to other VR platforms. An integral part of this tool is a set of sensors, which serves as physiological measures to evaluate the effectiveness of such system. What is more, the system integrate visual (passing sphere), auditory (surround sound) and tactile signals (vibration of controllers). A pilot treatment programme, incorporating the above mentioned VR system, was carried out. Experimental group consisting of 28 healthy adult volunteers (office workers), participated in three different sessions of relaxation training. Before starting, baseline features such as subjectively perceived stress, mood, heart rate, galvanic skin response and muscle response were registered. The monitoring of physiological indicators is continued during the training session and one minute after its completion. Before and after the session, volunteers were asked to re-fill questionnaires regarding the current stress level and mood. The obtained results were analyzed in terms of variability over time: before, during and after the session.

This paper introduces, explains and illustrates real-life application of virtual training tool for electrical engineering education. The tool gives users the opportunity to interact with and manipulate 3D models of authentic devices. The users have a possibility to compare structural differences between devices, assemble and disassemble the machines and test them under extreme conditions, all of which would not be possible while working with a real device. The 3D devices are fully operational allowing the users to interact with them on every level, including analysis of impact of supply conditions i.e. modify voltage and frequency of a particular motor and monitor changes in performance while still operating. The main goal of this research was to evaluate effectiveness and educational values of the proposed tool. Early studies and feedback from educators and students prove this tool to be a great assistance to process of education, facilitating knowledge acquisition and providing an innovative way to put theory into practice.