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The term \"Smart Classroom\" has evolved over time and nowadays reflects the technological advancements incorporated in educational spaces. The rapid advances in technology, and the need to create more efficient and creative classes that support both in-class and remote activities, have led to the integration of Artificial Intelligence and smart technologies in smart classes. In this paper we discuss the concept of Artificial Intelligence in Education and present a literature review related to smart classroom technology, with an emphasis on emerging technologies such as AI-related technologies. As part of this survey key technologies related to smart classes used for effective class management that enhance the convenience of classroom environments, the use of different types of smart teaching aids during the educational process and the use of automated performance assessment technologies are presented. Apart from discussing a variety of technological accomplishments in each of the aforementioned areas, the role of AI is discussed, allowing the readers to comprehend the importance of AI in key technologies related to smart classes. Furthermore, through a SWOT analysis, the Strengths, Weaknesses, Opportunities, and Threats of adopting AI in smart classes are presented, while the future perspectives and challenges in utilizing AI-based techniques in smart classes are discussed. This survey targets educators and AI professionals so that the former get informed about the potential, and limitations of AI in education, while the latter can get inspiration from the challenges and peculiarities of educational AI-based systems.

Primary school students often find it difficult to understand the differences between two dimensional and three-dimensional geometric shapes. Taking advantage of the ability of virtual and augmented reality to visualize 3D objects, we investigate the potential of using virtual and augmented reality technologies for teaching the lesson of geometric solids to primary school children. As part of the study 30 fourth, fifth and sixth class primary school students were divided into three groups that include a control group and two experimental groups. The first and second experimental groups used dedicated virtual and augmented reality applications to learn about geometric solids, while students from the control group used traditional printed material as part of the learning process. The results indicate that the implementation of new technologies in education of virtual and augmented reality improve interactivity and student interest in mathematics education, contributing to more efficient learning and understanding of mathematical concepts when compared to traditional teaching methods. No significant difference was found between virtual and augmented reality technologies with regard to the efficiency of the methods that contribute to the learning of mathematics, suggesting that both virtual and augmented reality display similar potential for educational activities in Mathematics.

Automatic age-progression is the process of modifying an image showing the face of a person in order to predict his/her future facial appearance. In this paper, we compare the performance of two age-progression methodologies reported in the literature against two novel approaches to the problem. In particular, we compare the performance of a method based on age prototypes, a method based on aging functions defined in a low-dimensional parametric model space, and two methods based on the distributions of samples belonging to different individuals and different age groups. Quantitative comparative results reported in the paper are based on dedicated performance evaluation metrics that assess the ability of each method to produce accurate predictions of the future/previous facial appearance of subjects. The framework proposed in this paper promotes the idea of a standardized performance evaluation protocol for age-progression methodologies, using images from a publicly available image database.

Virtual reality (VR) can be useful in efforts that aim to improve the well-being of older members of society. Within this context, the work presented in this paper aims to provide the elderly with a user-friendly and enjoyable virtual reality application incorporating memory recall and storytelling activities that could promote mental awareness. An important aspect of the proposed VR application is the presence of a virtual audience that listens to the stories presented by elderly users and interacts with them. In an effort to maximize the impact of the VR application, research was conducted to study whether the elderly are willing to use the VR application and whether they believe it can help to improve well-being and reduce the effects of loneliness and social isolation. Self-reported results related to the experience of the users show that elderly users are positive towards the use of such an application in everyday life as a means of improving their overall well-being.

The provision of information encourages people to visit cultural sites more often. Exploiting the great potential of using smartphone cameras and egocentric vision, we describe the development of a robust artwork recognition algorithm to assist users when visiting an art space. The algorithm recognizes artworks under any physical museum conditions, as well as camera point of views, making it suitable for different use scenarios towards an enhanced visiting experience. The algorithm was developed following a multiphase approach, including requirements gathering, experimentation in a virtual environment, development of the algorithm in real environment conditions, implementation of a demonstration smartphone app for artwork recognition and provision of assistive information, and its evaluation. During the algorithm development process, a convolutional neural network (CNN) model was trained for automatic artwork recognition using data collected in an art gallery, followed by extensive evaluations related to the parameters that may affect recognition accuracy, while the optimized algorithm was also evaluated through a dedicated app by a group of volunteers with promising results. The overall algorithm design and evaluation adopted for this work can also be applied in numerous applications, especially in cases where the algorithm performance under varying conditions and end-user satisfaction are critical factors.

The body language of an educator during a class can affect student’s level of interest and concentration. As an attempt to assist educators to improve their body language and speaking characteristics, a pilot body language analysis system that assesses the body language of educators was developed. The proposed application makes use of specific biometric features for determining body language quality during class delivery. The aim of the current study is to examine whether the proposed application can contribute to improving the teachers’ body language, whether the application can provide satisfactory feedback related to the teachers’ body language, and whether the use of the application in real classroom conditions is acceptable. As part of this effort the pilot application has been assessed by teachers of primary, secondary and university education. The experimental investigation involved two phases. In the first phase participants delivered a short lecture that was evaluated using the automated body language analysis application. After the lecture participants were informed about the operation of the application and they were presented with the feedback generated by the body language analysis. During the second phase participants delivered a second short lecture. By comparing the body language quality between the two phases, conclusions related to the impact of the application in improving body language were derived. Experimental results demonstrate that the application provides satisfactory feedback, it is acceptable to use the application in real class conditions, and the feedback provided can be used for self-assessment, reflection and improvement regarding educator’s body language.

Purpose The purpose of this paper is to propose the use of a virtual reality (VR)-based approach to improve teacher education and life-long professional development. Through constant training in real-life based situations but within a safe three-dimensional virtual school environment, teachers are given the opportunity to experience and learn how to react to different types of incidents that may take place in a school environment. Design/methodology/approach The current paper presents the design cycle that was followed for the implementation of the VR teacher training system. The effectiveness of the proposed approach is demonstrated with a case study that aimed to promote teachers’ understanding of student’s problematic situations related to substance use. As part of the experimental investigation, the impact of the VR system on participants’ emotions and mood states is evaluated through Electroencephalogram (EEG) measurements, heart rate (HR) recordings and self-reported data. Findings Results indicate significant changes to participant’s negative emotional and mood states, suggesting that the scenario and the VR experience had a strong impact on them. Moreover, participants’ HR was increased during the experiment, while the analysis of the EEG signal indicated that the participants experienced a stressful situation that could justify the change in their negative emotions and mood states. Originality/value The proposed VR-based approach aims to provide an innovative framework to teacher education and the related training methodology. In the long-term, the proposed VR system aims to form a new paradigm of teacher training, an alternative safe method that will allow user-teachers to learn through trial and error techniques that reflect real-life situations within a three-dimensional school space and without the risk of harming real students. To the best of our knowledge this is one of the first systematic attempts to use a VR-based methodology to address real teachers’ needs. The development of the VR application is linked to both strong theoretical foundations in education derived from the literature but also from real teachers’ problems and requirements derived from an extensive literature analysis, survey and interviews with experts including teachers, school counselors and psychologists. The VR tool addresses specific teachers’ competences as outcome, after an extensive documentation of existing Teachers’ Competence Models and significant guidance by experts who pointed specific competencies of primary importance to teachers.

The last few years Virtual Reality (VR) based approaches have emerged lately as a new education paradigm. This paper addresses the possibility to cultivate reflection and empathy skills using a VR based framework targeting to maximize the professional development of teachers. Reflection and empathy are skills of paramount importance for teachers and an integral part of their professional development. The current research aims to investigate possible differences in cultivating reflection and empathy skills between participants who used a VR system and the control group who were trained in a real classroom environment. Experimental results indicate that the participants using the virtual classroom environment were able to better reflect and empathize with the students whereas participants from the control group tended to be more undecided. Moreover, the VR system gave the participants the opportunity to enter the students’ virtual body and understand the different perspectives affecting at a higher level the reflection process than the control group.

According to a number of studies, the use of personalized avatars in virtual environments can enhance the immersion experience of users and the effectiveness of communication between different players. The benefits of using personalized avatars in conjunction with recent technological developments in Virtual Reality (VR) prompted an increasing demand for low-cost systems that are capable of fast and easy generation of personal avatars for use in VR applications. In this paper we present a novel model-based technique that is capable of generating personalized full-body 3D avatars from orthogonal photographs. The proposed method utilizes a statistical model of human 3D shape and a multi-view statistical 2D shape model of its corresponding silhouettes. Our technique is automatic, requiring minimal user intervention, and does not need a calibrated camera. Each component of our proposed technique is extensively evaluated and validated, in an attempt to test the geometric accuracy and identifiability of generated avatars. Furthermore, we demonstrate the use of the proposed method for generating and importing animation-ready avatars in collaborative VR environments.