In the education process, students face problems with understanding due to the complexity, necessity of abstract thinking and concepts. More and more educational centres around the world have started to introduce powerful new technology-based tools that help meet the needs of the diverse student population. Over the last several years, virtual reality (VR) has moved from being the purview of gaming to professional development. It plays an important role in teaching process, providing an interesting and engaging way of acquiring information. What follows is an overview of the big trend, opportunities and concerns associated with VR in education. We present new opportunities in VR and put together the most interesting, recent virtual reality applications used in education in relation to several education areas such as general, engineering and health-related education. Additionally, this survey contributes by presenting methods for creating scenarios and different approaches for testing and validation. Lastly, we conclude and discuss future directions of VR and its potential to improve the learning experience.Information 2019, 10, 318 2 of 20 must be carried out under supervision; therefore, students cannot self-configure lab equipment, experience states of emergency or effects of misconfiguration which may lead to equipment damage. Moreover, there is no possibility to practice and catch up outside the laboratory schedule. Currently, the solutions are modern technologies such as online courses [8,9], blended learning [10-13], different computer-based platforms [14-18] and many others, which allow the students to repeat several times the same topic, make mistakes and learn from them. Numerous examples of hardware and software which have been successful in educational processes indicate that edtech industry can improve learning outcomes for the majority of students [19]. More and more educational centres around the world are starting to introduce powerful new technology tools that help them to meet the needs of diverse student populations. Traditional books are being replaced by digital instructional content (especially from open educational resources) [20]. Notebooks, tablets or cell phones with dedicated application have replaced classical copybooks [21]. Distance [22] and personalised learning [23] are used to tailor education to each student's academic strengths, weaknesses, preferences and goals.It is well known that the use of information and communication technologies have been found to improve student attitudes towards learning [24][25][26][27]. It is a rapidly growing field of research, continually developing and looking for new technological solutions. Over the last several years, Virtual Reality (VR), which provides an interactive computer-generated environment, has moved from being the purview of the gaming to the professional development such as military, psychology, medicine and teaching applications.In 1987, Jaron Lanier, together with Steve Bryson, formulated the first definition of VR, which they desc...

Over the past few decades human-computer interaction has become more important in our daily lives and research has developed in many directions: memory research, depression detection, and behavioural deficiency detection, lie detection, (hidden) emotion recognition etc. Because of that, the number of generic emotion and face databases or those tailored to specific needs have grown immensely large. Thus, a comprehensive yet compact guide is needed to help researchers find the most suitable database and understand what types of databases already exist. In this paper, different elicitation methods are discussed and the databases are primarily organized into neat and informative tables based on the format.

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.

Abstract-Facial dynamics can be considered as unique signatures for discrimination between people. These have started to become important topic since many devices have the possibility of unlocking using face recognition or verification. In this work, we evaluate the efficacy of the transition frames of video in emotion as compared to the peak emotion frames for identification. For experiments with transition frames we extract features from each frame of the video from a fine-tuned VGG-Face Convolutional Neural Network (CNN) and geometric features from facial landmark points. To model the temporal context of the transition frames we train a Long-Short Term Memory (LSTM) on the geometric and the CNN features. Furthermore, we employ two fusion strategies: first, an early fusion, in which the geometric and the CNN features are stacked and fed to the LSTM. Second, a late fusion, in which the prediction of the LSTMs, trained independently on the two features, are stacked and used with a Support Vector Machine (SVM). Experimental results show that the late fusion strategy gives the best results and the transition frames give better identification results as compared to the peak emotion frames.

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