Publications
2023
Journal: Smart Learning Environments
Authors: Eleni Dimitriadou, Andreas Lanitis
Published: 2023
Abstract: 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.
Conference: 17th annual International Conference of Education, Research and Innovation (INTED23)
Authors: Eleni Dimitriadou, Andreas Lanitis
Published: 2023
Abstract: In recent years many schools adopted tele-education during the COVID-19 pandemic. However, in several cases the use of cameras is not permitted during tele-education, and as a result student participation may be affected. This work aims to improve the active participation of students during tele-education by employing a privacy preserving human action recognition methodology, so that the educator is informed about student activity during on-line classes without having access to visual input showing the students. The aim of our work aims to evaluate the acceptance of using the proposed action recognition system for monitoring student activity in tele-education. Based on the preliminary results, teachers find it feasible to use the action recognition application, while they believe that it could improve the performance of students during distance learning.
2022
Conference: 17th International Joint Conference on Computer Vision, Theory and Applications (VISAPP)
Authors: Eleni Dimitriadou, Andreas Lanitis
Published: 2022
Abstract: Due to the COVID-19 pandemic, many schools worldwide are using tele-education for class delivery. However, this causes a problem related to students’ active class participation. We propose to address the problem with a system that recognizes student’s actions and informs the teacher accordingly, while preserving the privacy of students. In the proposed action recognition system, seven typical actions performed by students attending online courses, are recognized using Convolutional Neural Network (CNN) architectures. The actions considered were defined by considering the relevant literature and educator’s views, and ensure that they provide information about the physical presence, active participation, and distraction of students, that constitute important pedagogical aspects of class delivery. The action recognition process is performed locally on the device of each student, thus it is imperative to use classification methods that require minimal computational load and memory requirements. Initial experimental results indicate that the proposed action recognition system provides promising classification results, when dealing with new instances of previously enrolled students or when dealing with previously unseen students.
Conference: IEEE 21st Mediterranean Electrotechnical Conference (MELECON)
Authors: Eleni Dimitriadou, Andreas Lanitis
Published: 2022
Abstract:
During the years, the concept of “Smart Classroom” evolved to reflect technological advances. This survey provides a review of research work on smart classroom technologies, with a focus on emerging and Artificial Intelligence(AI)-related technologies. Smart classroom technologies related to the effective class management that enhance the convenience of classroom environments, the use of teaching aids during the educational process and the use of performance assessment technologies are presented. Apart from discussing the range of technological achievements in each of the aforementioned areas, the role of AI is thoroughly discussed allowing researchers and developers in AI to realize the existing uses of AI in smart classes and get informed about future perspectives and challenges in adopting AI-based techniques in smart classes.
Conference: 14th Cyprus Workshop on Signal Processing and Informatics (CWSPI)
Authors: Michalis Kontos, Eleni Dimitriadou, Andreas Lanitis
Published: 2022
Abstract: Distance learning became extremely popular during the COVID-19 pandemic, with many people working and attending classes from home. Due to privacy issues, in many countries the use of webcams is forbidden during tele-education. However, when the educator has no optical contact with his/her class, students tend to lose their concentration, and the overall teaching process is jeopardised. The aim of our work is to provide a system that will allow teachers to get informed about student activities during tele-education but without having access to video input from students. In the proposed system, images of students captured by webcams are processed locally at a students’ personal machine, in order to identify the student actions. The relevant information is send to a server at the teacher’s side. The server side contains a 3D visualization of the class where each student is represented by an avatar, animated to reflect student actions. This method will keep the teacher informed of the students actions without violating privacy barriers.
A Systematic Approach for Developing a Robust Artwork Recognition Framework Using Smartphone Cameras
Journal: Algorithms
Authors: Zenonas Theodosiou, Marios Thoma, Harris Partaourides, Andreas Lanitis
Published: 2022
Abstract: 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.
DOI: 10.3390/a15090305
Conference: Proceedings of the 31st ACM International Conference on Information & Knowledge Management
Authors: Periklis Perikleous, Andreas Kafkalias, Zenonas Theodosiou, Pinar Barlas, Evgenia Christoforou, Jahna Otterbacher, Gianluca Demartini and Andreas Lanitis
Published: 2022
Abstract:
It is increasingly easy for interested parties to play a role in the development of predictive algorithms, with a range of available tools and platforms for building datasets, as well as for training and evaluating machine learning (ML) models. For this reason, it is essential to create awareness among practitioners on the ethical challenges, such as the presence of social bias in training data. We present RECANT (Raising Awareness of Social Bias in Crowdsourced Training Data), a tool that allows users to explore the behaviors of four biometric models — predicting the gender and race, as well as the perceived attractiveness and trustworthiness, of the person depicted in an input image. These models have been trained on a crowdsourced dataset of passport-style people images, where crowd annotators described attributes of the images, and reported their own demographic characteristics. With RECANT, users can explore the correct and wrong predictions made by each model, when using different subsets of the data in training, based on annotator attributes. We present its features, along with sample exercises, as a hands-on tool for raising awareness of potential pitfalls in data practices surrounding ML.
Bias in Face Image Classification Machine Learning Models: The Impact of Annotator’s Gender and Race
Conference: 18th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI2022)
Authors: Andreas Kafkalias, Stylianos Herodotou, Zenonas Theodosiou, Andreas Lanitis
Published: 2022
Abstract:
An important factor that ensures the correct operation of Machine Learning models is the quality of data used during the model training process. Quite often, training data is annotated by humans, and as a result, annotation bias may be introduced. In this study, we focus on face image classification and aim to quantify the effect of annotation bias introduced by different groups of annotators, allowing in that way the understanding of the problems that arise due to annotation bias. The results of the experiments indicate that the performance of Machine Learning models in several face image interpretation tasks is correlated to the self-reported demographic characteristics of the annotators. In particular, we found significant correlation to annotator race, while correlation to gender is less profound. Furthermore, experimental results show that it is possible to determine the group of annotators involved in the annotation process by considering the annotation data provided by previously unseen annotators. The results emphasize the risks of annotation bias in Machine Learning models.
Conference: Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2020. Communications in Computer and Information Science, vol 1474. Springer, Cham, 2022
Authors: Zenonas Theodosiou, Harris Partaourides, Simoni Panayi, Andreas Kitsis, Andreas Lanitis
Published: 2022
Abstract:
The impact of walking in modern cities has proven to be quite significant with many advantages especially in the fields of environment and citizens’ health. Although society is trying to promote it as the cheapest and most sustainable means of transportation, many road accidents have involved pedestrians and cyclists in the recent years. The frequent presence of various obstacles on urban sidewalks puts the lives of citizens in danger. Their immediate detection and removal are of great importance for maintaining clean and safe access to infrastructure of urban environments. Following the great success of egocentric applications that take advantage of the uninterrupted use of smartphone devices to address serious problems that concern humanity, we aim to develop methodologies for detecting barriers and other dangerous obstacles encountered by pedestrians on urban sidewalks. For this purpose a dedicated image dataset is generated and used as the basis for analyzing the performance of different methods in detecting and recognizing different types of obstacle using three different architectures of deep learning algorithms. The high accuracy of the experimental results shows that the development of egocentric applications can successfully help to maintain the safety and cleanliness of sidewalks and at the same time to reduce pedestrian accidents.
2021
Journal: Safety Science
Authors: Achilleas Mina, Antreas Lanitis, Pavlos Alexandros Dimitrioua, Harris Partaourides, Pericles Pericleous
Published: January 2021
Abstract: The proper use of high-visibility safety apparel (HVSA) increases conspicuity and reduces accident rates. The main factor affecting daytime conspicuity is the color contrast between HVSA and the ambient background environment. Selecting HVSA without considering their contrast to the worksite environment may result in unsafe situations where HVSA not only fail to provide the desired conspicuity but also act as camouflage. One such situation is the use of red HVSA on oil tankers with brown decks. This paper presents a methodology for selecting the most effective HVSA color for a particular worksite. Using image analysis techniques, we can assess the contrast between a set of high-visibility colors and the colors present at a worksite in order to determine the most effective HVSA color for the particular site. The methodology was experimentally validated with the help of 50 volunteers and the use of a purpose-built validation software. Results showed a 27% reduction in the time required to detect workers when the color of their HVSA was changed to match the color determined as per the proposed methodology.
Conference:14th annual International Conference of Education, Research and Innovation
Authors: Eleni Dimitriadou, Andreas Lanitis
Published: 2021
Abstract:
Due to the COVID-19 pandemic, many schools worldwide are using tele-education for class delivery. However, this causes a problem related to students’ active class participation, especially in the cases that due to privacy issues no videos of students are available to the teacher. We propose to address the problem with a system that recognizes student’s actions and informs the teacher accordingly, while preserving the privacy of students. The development of the proposed system was based on the opinions of teachers, parents, and students as well as on the existing literature that relates student actions to student participation. Initial experimental results of a pilot study involving primary school students indicate that the proposed action recognition system provides promising classification results, while the opinions of educators, students and parents are positive towards the adoption of this technology.
Conference: Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection: 8th International Conference, EuroMed 2020, Virtual Event
Authors: Andreas Lanitis, Zenonas Theodosiou, Harris Partaourides
Published: 2021
Abstract:
The ability to identify the artworks that a museum visitor is looking at, using first-person images seamlessly captured by wearable cameras can be used as a means for invoking applications that provide information about the exhibits, and provide information about visitors’ activities. As part of our efforts to optimize the artwork recognition accuracy of an artwork identification system under development, an investigation aiming to determine the effect of different conditions on the artwork recognition accuracy in a gallery/exhibition environment is presented. Through the controlled introduction of different distractors in a virtual museum environment, it is feasible to assess the effect on the recognition performance of different conditions. The results of the experiment are important for improving the robustness of artwork recognition systems, and at the same time the conclusions of this work can provide specific guidelines to curators, museum professionals and visitors, that will enable the efficient identification of artworks, using images captured with wearable cameras in a museum environment.
Conference: Science and Technologies for Smart Cities: 6th EAI International Conference, SmartCity360°, Virtual Event, December 2-4, 2020, Proceedings
Authors: Marios Thoma, Zenonas Theodosiou, Harris Partaourides, Charalambos Tylliros, Demetris Antoniades & Andreas Lanitis
Published: 2021
Abstract:
Encouraging people to walk rather than using other means of transportation is an important factor towards personal health and environmental sustainability. However, given the large number of pedestrian accidents recorded every year, the need for safe urban environments is increasing. Taking advantage of the potential of citizen-science for crowdsourcing data and creating awareness, we developed a smartphone application for enhancing the safety of pedestrians while walking in cities. Using the application, citizens will monitor the urban sidewalks and update a crowdsourcing platform with the detected barriers and damages that hinder safe walking, along with their location on a city map. To help users assign the correct type of obstacle, and authorities to assess the urgency, a Convolutional Neural Network (CNN) model for barrier and damage recognition is embedded in the application. The results of a user evaluation, based on a group of volunteers who used the application in real conditions, demonstrate the potential of using the application in conjunction with a smart city framework.
2020
Conference: EAI International Conference on Cognitive Computing and Cyber Physical Systems
Authors: M. Thoma, Z. Theodosiou, H. Partaourides, C.Tylliros, D. Antoniades, and A. Lanitis
Published: November 2020
Abstract: 2020
Conference: 8th International Euro-Mediterranean Conference
Authors: E. Ioannou, A. Lanitis, AK.Vionis, G. Papantoniou, N. Savvides
Published: November 2020
Abstract: Landscape studies have evolved into a significant branch of historical archaeological research, by placing emphasis on the ecological, economic, political and cultural values of pre-modern settled and sacred landscapes. The aim of our work is to support the systematic exploration of landscape archaeology in the Xeros River valley in Cyprus, through time, from prehistory to today, through the development of an Augmented Reality (AR) application. The AR application supports the exploration of pre-modern monuments and archaeological sites in the Xeros River valley, serving as a guided tour for visitors of the area. By employing image recognition and utilizing a location-based practice, the application provides the users with an immersive and educational experience, enabling the narration of the historicity of the landscape and the fate of religious and other monuments of the past 1500 years.
Conference: 8th International Euro-Mediterranean Conference
Authors: Andreas Lanitis, Zenonas Theodosiou, Harris Partaourides
Published: November 2020
Abstract: The ability to identify the artifacts that a museum visitor is looking at, using first-person images seamlessly captured by a wearable camera can be used as a means for invoking applications that provide information about the exhibits, and at the same time, it allows the analysis of visitors` activities. In this paper, a system utilizing a deep network for identifying paintings in a museum environment is presented. As part of the efforts to optimize the performance of the system, an investigation aiming to determine the effect of different conditions on the artwork recognition accuracy in a gallery/exhibition environment is presented. Through the controlled introduction of different distractors in the virtual environment, it is feasible that we assess the effect on the recognition performance in different conditions. The results of the experiment are important for improving the robustness of artwork recognition systems, and at the same time the conclusions of this work can provide specific guidelines to curators, museum professionals and visitors, that will enable the efficient use of wearable cameras in museums.
Conference: 13th Cyprus Workshop on Signal Processing and Informatics
Authors: Marios Thoma, Zenonas Theodosiou, Harris Partaourides, Charalambos Tylliros, Demetris Antoniades, Andreas Lanitis
Published: September 2020
Conference: Encyclopedia of Cryptography, Security and Privacy
Authors: Andreas Lanitis
Published: 2020
Conference: International Conference on Emerging Technologies and the Digital Transformation of Museums and Heritage Sites
Authors: A. Papadopoulou, C. Englezou, G. Neonakis, N. Mavrou, A. Lanitis.
Published: 2020
Conference: International Conference on Emerging Technologies and the Digital Transformation of Museums and Heritage Sites
Authors: Z. Theodosiou, H. Partaourides, A. Lanitis
Published: 2020
Journal: Safety Science
Authors: Zenonas Theodosiou, Nicolas Tsapatsoulis
Published: March 2020
Abstract: Image annotation is the process of assigning metadata to images, allowing effective retrieval by text-based search techniques. Despite the lots of efforts in automatic multimedia analysis, automatic semantic annotation of multimedia is still inefficient due to the problems in modeling high-level semantic terms. In this paper, we examine the factors affecting the quality of annotations collected through crowdsourcing platforms. An image dataset was manually annotated utilizing: (1) a vocabulary consists of preselected set of keywords, (2) an hierarchical vocabulary and (3) free keywords. The results show that the annotation quality is affected by the image content itself and the used lexicon. As we expected while annotation using the hierarchical vocabulary is more representative, the use of free keywords leads to increased invalid annotation. Finally, it is shown that images requiring annotations that are not directly related to their content (i.e., annotation using abstract concepts) lead to accrue annotator inconsistency revealing in that way the difficulty in annotating such kind of images is not limited to automatic annotation, but it is a generic problem of annotation.
Conference: Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Authors: Zenonas Theodosiou, Harris Partaourides, Tolga Atun, Simoni Panayi, Andreas Lanitis
Published: January 2020
Abstract: Image annotation is the process of assigning metadata to images, allowing effective retrieval by text-based search techniques. Despite the lots of efforts in automatic multimedia analysis, automatic semantic annotation of multimedia is still inefficient due to the problems in modeling high-level semantic terms. In this paper, we examine the factors affecting the quality of annotations collected through crowdsourcing platforms. An image dataset was manually annotated utilizing: (1) a vocabulary consists of preselected set of keywords, (2) an hierarchical vocabulary and (3) free keywords. The results show that the annotation quality is affected by the image content itself and the used lexicon. As we expected while annotation using the hierarchical vocabulary is more representative, the use of free keywords leads to increased invalid annotation. Finally, it is shown that images requiring annotations that are not directly related to their content (i.e., annotation using abstract concepts) lead to accrue annotator inconsistency revealing in that way the difficulty in annotating such kind of images is not limited to automatic annotation, but it is a generic problem of annotation.
2019
Conference: 11th International Conference on Education and New Learning Technologies
Authors: Eleni Demitriadou, Andreas Lanitis
Published: July 2019
Abstract: Young students often find it difficult to understand the three-dimensional structure of solids. New technologies that support three-dimensional representations, such as Virtual and Augmented Reality, can provide the basis for implementing teaching tools that will allow students to better understand topics in mathematics involving three-dimensional structures. In this paper we present the methodology used as part of an investigation that aims to evaluate the potential and compare Virtual and Augmented Reality technologies for teaching the lesson of geometric solids to primary school children. Emphasis is given on the development of dedicated tools used as part of the evaluation. Early results indicate that as far as the learning outcomes and the student satisfaction are concerned, both VR and AR technologies show similar promise.
Journal: Education and Information Technologies
Authors: Eleni Demitriadou, Kalliopi-Evangelia Stavroulia, Andreas Lanitis
Published: July 2019
Abstract: 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.
Conference: Advances in Intelligent Systems and Computing
Authors: Christina Zavlanou, Andreas Lanitis
Published: July 2019
Abstract: Age-related changes significantly affect elderly users’ interaction with specific products and services. Nevertheless, the challenges experienced by elderly users are difficult to be perceived and understood, especially by younger people. Inspired by the concept of aging suits, we propose a Virtual Reality-based approach, where age-related visual impairments are simulated in virtual environments. The aim is to provide an approximation of the experience of viewing and interacting with a product, from the perspective of elderly persons with specific age-related visual problems. The effectiveness of the proposed approach is examined through an experiment involving package design evaluation. The experimental results demonstrate that Virtual Reality can play an important role on understanding the challenges that elderly users face, thus support the design of elderly-friendly products.
Conference: 14th International Workshop on Semantic and Social Media Adaptation and Personalization
Authors: Kalliopi-Evangelia Stavroulia, Maria Cheistofi, Telmo Zarraonandia, Despina Michael-Grigoriou, Andreas Lanitis
Published: June 2019
Abstract: The use of wearable cameras covers several areas of application nowadays, where the need for developing smart applications providing the sustainability and well-being of citizens it is more necessary than ever before. The tremendous amount of lifelogging data to extract valuable knowledge about the every day life of the wearers requires state of the art retrieval techniques to efficiently store, access, search and retrieve useful information. Several works have been proposed combining computer vision and machine learning techniques to analyze the content of the data captured from visual wearable devices on a daily basis. This paper presents an overview of the progress in visual lifelogging retrieval and indicates the current advances and future challenges, highlighting the prospects of incorporating visual lifelogging retrieval in social computing applications.
Journal: Smart Computing and Intelligence
Authors: Kalliopi-Evangelia Stavroulia, Maria Cheistofi, Telmo Zarraonandia, Despina Michael-Grigoriou, Andreas Lanitis
Published: June 2019
Abstract: VR technologies are gaining momentum in the field of education and particularly in the use of Virtual Reality (VR)-based learning. Within Virtual Reality Environments (VREs) realistic world situations are simulated, facilitating the transfer of the knowledge and skills gained within the virtual world to the real one. In this chapter, we provide a review of several advantages of using VR technology in education and training. In addition, we examine different challenges and potential problems that need to be considered in order to successfully integrate VR in training activities. We also exemplify the promising prospect of this technology in education by describing two novel VR applications. The first one aims to support educators in improving their teaching practice. Using VR technology, the teacher is given the opportunity to experience the student’s point of view during a classic room and cultivate their empathy skills. The second one aims to support teachers in creating VR serious games by lowering the difficulty of developing this type of educational artefact through intuitive interaction and eliminating the need for learning new design language.
Journal: International Journal of Information and Learning Technology
Authors: Kalliopi Evangelia Stavroulia, Maria Christofi, Evangelia Baka, Despina Michael-Grigoriou, Nadia Magnenat-Thalmann, Andreas Lanitis
Published: June 2019
Abstract: 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.
Journal: International Journal of Emerging Technologies in Learning
Authors: Kalliopi Evangelia Stavroulia, Andreas Lanitis
Published: April 2019
Abstract: 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.
Journal: s
Authors: Fernando Loizides, Andreas Lanitis, Giorgos Papantoniou, Demetrios Michaelides
Published: s
Abstract: s
DOI: s
2018
Conference: International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments
Authors: Christofi, Maria and Baka, Evangelia and Stavroulia, Kalliopi Evangelia and Michael-Grigoriou, Despina and Lanitis, Andreas, Thalmann, Nadia-Magnenat
Published: November 2019
Abstract: This paper studies the aspect of presence in a Virtual Reality (VR) environment that can be used for training purposes in the education sector and more specifically for teacher training and professional development. During the VR experience trainees had the chance to view the world from different perspectives through the eyes of different characters appearing in the scene. The experimental evaluation conducted aims to examine the effect of viewing the experience from different perspectives and viewpoints in relation to the overall user experience and the level of presence achieved. To accomplish these objectives an experiment was performed investigating presence and the correlation between presence and different viewpoints/perspectives. To measure presence a combination of methods were used including two different questionnaires, the use of an eeg device, EMOTIV EPOC+ and the analysis of heart rates. The results indicate that high levels of presence were recorded and that increased levels of presence are associated with viewing the VE from a student rather than a teacher perspective.
Conference: Lecture Notes in Computer Science
Authors: Christos Hadjipanayi, Eleni Demitriadou, Haris Frangou, Maria Papageorgiou, Christina Zavlanou, Andreas Lanitis
Published: October 2018
Abstract: The aim of our work is to investigate the applicability of Virtual Reality (VR) in raising awareness of users in relation to the destruction of important monuments. The proposed methodology involves the exposure of users to three virtual environments displaying the original state of a monument, the current state and the predicted future state of the same monument in the case that the monument is not maintained. The exposure to the three states of the same building allows the user to experience the “glorious days” of a monument and compare them to the current and future states in an attempt to realize the level of destruction that could occur to the building if the monument is not maintained properly. As part of a pilot case study, a number of volunteers were asked to navigate in virtual environments depicting the three chronological states of a landmark building. Preliminary results indicate a significant increase of the intensity of negative emotions of the users, indicating the applicability of VR in alerting the society toward the destruction of important monuments.