Measuring the impact of virtual reality on a serious game for improving oral presentation skill

Background and Objectives: Oral presentation is a key competence for success in the diverse work environments that academics need. It is recommended as part of a higher education curriculum. The role of technology in improving oral presentation skills and especially facilitating feedback, is significant. In particular, the combination of serious game and virtual reality is a new area of ​​research that is a modern alternative to traditional skills training. The interactive digital environment, real-time feedback, the realism of the learning scenario, the direct experience, and the persistence of the knowledge gained are some of the virtual reality opportunities for skills training. It should not be overlooked that insufficient budget, negative attitude of users about their physical and psychological condition after experiencing virtual reality, and poor technological design of virtual reality environments are also among the limitations of this technology. However, recent meta-analyzes confirm the influence of virtual reality in learning environments. Accordingly, the purpose of this study was to measure the impact of virtual reality on a serious game with the serious purpose of oral presentation training. Methods: We designed and developed an SG and conducted a quasi-experimental study with a post-test on 32 graduate students. The research question we sought to answer was “to what extent can VR impact the effectiveness of SGs in oral presentation training?” The authors also analyzed the cost-effectiveness of incorporating VR elements. The game focused on three key skills, eye contact, walking around while presenting, and time management. The experimental group played the game with the HTC Vive VR system and the control group played the same game with an HD display, a keyboard, and a mouse. In addition to that, we collected in-game data while players were playing the game. Mann-Whitney U test and Student's t-test were used to compare the two groups. Findings: Results revealed that VR elements did not have a significant impact on the demonstration of the players' eye contact skills but they increased players' tendency to walk around the virtual environment. Analysis of players’ performance regarding time management skills showed no significant difference between the two groups. Conclusion: It is concluded that even though playing the serious game with an HD display, a keyboard, and a mouse can be effective, turning the game into a VR experience would result in further improvement in the demonstration of some of the presentation key skills (walking around while presenting). However, creating a VR experience requires developers to spend more time and resources into developing the game. According to researchers, creating a VR SG for improving oral presentation skills allows for training to be done in the context that it occurs within. Moreover, the VR SG can be effectively used to overcome public presentation nerves. Also, due to the challenging economic situations outside the university and the need to benefit from communication skills and oral presentation, a serious game based on virtual reality can improve the indicators of oral presentation. Achieving this requires higher education attention to interactive technologies such as virtual reality.   ===================================================================================== COPYRIGHTS  ©2020 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.  ====================================================================================

Development and evaluation of an interactive virtual audience for a public speaking training application

Einleitung: Eine der häufigsten sozialen Ängste ist die Angst vor öffentlichem Sprechen. Virtual-Reality- (VR-) Trainingsanwendungen sind ein vielversprechendes Instrument, um die Sprechangst zu reduzieren und die individuellen Sprachfähigkeiten zu verbessern. Grundvoraussetzung hierfür ist die Implementierung eines realistischen und interaktiven Sprecher-Publikum-Verhaltens. Ziel: Die Studie zielte darauf ab, ein realistisches und interaktives Publikum für eine VR-Anwendung zu entwickeln und zu bewerten, welches für die Trainingsanwendung von öffentlichem Sprechen angewendet wird. Zunächst wurde eine Beobachtungsstudie zu den Verhaltensmustern von Sprecher und Publikum durchgeführt. Anschließend wurden die identifizierten Muster in eine VR-Anwendung implementiert. Die Wahrnehmung der implementierten Interaktionsmuster wurde in einer weiteren Studie aus Sicht der Nutzer evaluiert. Beobachtungsstudie (1): Aufgrund der nicht ausreichenden Datengrundlage zum realen interaktiven Verhalten zwischen Sprecher und Publikum lautet die erste Forschungsfrage "Welche Sprecher-Publikums-Interaktionsmuster können im realen Umfeld identifiziert werden?". Es wurde eine strukturierte, nicht teilnehmende, offene Beobachtungsstudie durchgeführt. Ein reales Publikum wurde auf Video aufgezeichnet und die Inhalte analysiert. Die Stichprobe ergab N = 6484 beobachtete Interaktionsmuster. Es wurde festgestellt, dass Sprecher mehr Dialoge als das Publikum initiieren und wie die Zuschauer auf Gesichtsausdrücke und Gesten der Sprecher reagieren. Implementierungsstudie (2): Um effiziente Wege zur Implementierung der Ergebnisse der Beobachtungsstudie in die Trainingsanwendung zu finden, wurde die Forschungsfrage wie folgt formuliert: "Wie können Interaktionsmuster zwischen Sprecher und Publikum in eine virtuelle Anwendung implementiert werden?". Das Hardware-Setup bestand aus einer CAVE, Infitec-Brille und einem ART Head-Tracking. Die Software wurde mit 3D-Excite RTT DeltaGen 12.2 realisiert. Zur Beantwortung der zweiten Forschungsfrage wurden mehrere mögliche technische Lösungen systematisch untersucht, bis effiziente Lösungen gefunden wurden. Infolgedessen wurden die selbst erstellte Audioerkennung, die Kinect-Bewegungserkennung, die Affectiva-Gesichtserkennung und die selbst erstellten Fragen implementiert, um das interaktive Verhalten des Publikums in der Trainingsanwendung für öffentliches Sprechen zu realisieren. Evaluationsstudie (3): Um herauszufinden, ob die Implementierung interaktiver Verhaltensmuster den Erwartungen der Benutzer entsprach, wurde die dritte Forschungsfrage folgendermaßen formuliert: “Wie beeinflusst die Interaktivität einer virtuellen Anwendung für öffentliches Reden die Benutzererfahrung?”. Eine experimentelle Benutzer-Querschnittsstudie wurde mit N = 57 Teilnehmerinnen (65% Männer, 35% Frauen; Durchschnittsalter = 25.98, SD = 4.68) durchgeführt, die entweder der interaktiven oder nicht-interaktiven VR-Anwendung zugewiesen wurden. Die Ergebnisse zeigten, dass, es einen signifikanten Unterschied in der Wahrnehmung zwischen den beiden Anwendungen gab. Allgemeine Schlussfolgerungen: Interaktionsmuster zwischen Sprecher und Publikum, die im wirklichen Leben beobachtet werden können, wurden in eine VR-Anwendung integriert, die Menschen dabei hilft, Angst vor dem öffentlichen Sprechen zu überwinden und ihre öffentlichen Sprechfähigkeiten zu trainieren. Die Ergebnisse zeigten eine hohe Relevanz der VR-Anwendungen für die Simulation öffentlichen Sprechens. Obwohl die Fragen des Publikums manuell gesteuert wurden, konnte das neu gestaltete Publikum mit den Versuchspersonen interagieren. Die vorgestellte VR-Anwendung zeigt daher einen hohen potenziellen Nutzen, Menschen beim Trainieren von Sprechfähigkeiten zu unterstützen. Die Fragen des Publikums wurden immer noch manuell von einem Bediener reguliert und die Studie wurde mit Teilnehmern durchgeführt, die nicht unter einem hohen Grad an Angst vor öffentlichem Sprechen leiden. Bei zukünftigen Studien sollten fortschrittlichere Technologien eingesetzt werden, beispielsweise Spracherkennung, 3D-Aufzeichnungen oder 3D-Livestreams einer realen Person und auch Teilnehmer mit einem hohen Grad an Angst vor öffentlichen Ansprachen beziehungsweise Sprechen in der Öffentlichkeit.Introduction: Fear of public speaking is the most common social fear. Virtual reality (VR) training applications are a promising tool to improve public speaking skills. To be successful, applications should feature a high scenario fidelity. One way to improve it is to implement realistic speaker-audience interactive behavior. Objective: The study aimed to develop and evaluate a realistic and interactive audience for a VR public speaking training application. First, an observation study on real speaker-audience interactive behavior patterns was conducted. Second, identified patterns were implemented in the VR application. Finally, an evaluation study identified users’ perceptions of the training application. Observation Study (1): Because of the lack of data on real speaker-audience interactive behavior, the first research question to be answered was “What speaker-audience interaction patterns can be identified in real life?”. A structured, non-participant, overt observation study was conducted. A real audience was video recorded, and content analyzed. The sample resulted in N = 6,484 observed interaction patterns. It was found that speakers, more often than audience members, initiate dialogues and how audience members react to speakers’ facial expressions and gestures. Implementation Study (2): To find efficient ways of implementing the results of the observation study in the training application, the second research question was formulated as: “How can speaker-audience interaction patterns be implemented into the virtual public speaking application?”. The hardware setup comprised a CAVE, Infitec glasses, and ART head tracking. The software was realized with 3D-Excite RTT DeltaGen 12.2. To answer the second research question, several possible technical solutions were explored systematically, until efficient solutions were found. As a result, self-created audio recognition, Kinect motion recognition, Affectiva facial recognition, and manual question generation were implemented to provide interactive audience behavior in the public speaking training application. Evaluation Study (3): To find out if implementing interactive behavior patterns met users’ expectations, the third research question was formulated as “How does interactivity of a virtual public speaking application affect user experience?”. An experimental, cross-sectional user study was conducted with (N = 57) participants (65% men, 35% women; Mage = 25.98, SD = 4.68) who used either an interactive or a non-interactive VR application condition. Results revealed that there was a significant difference in users’ perception of the two conditions. General Conclusions: Speaker-audience interaction patterns that can be observed in real life were incorporated into a VR application that helps people to overcome the fear of public speaking and train their public speaking skills. The findings showed a high relevance of interactivity for VR public speaking applications. Although questions from the audience were still regulated manually, the newly designed audience could interact with the speakers. Thus, the presented VR application is of potential value in helping people to train their public speaking skills. The questions from the audience were still regulated manually by an operator and we conducted the study with participants not suffering from high degrees of public speaking fear. Future work may use more advanced technology, such as speech recognition, 3D-records, or live 3D-streams of an actual person and include participants with high degrees of public speaking fear

An Overview of Self-Adaptive Technologies Within Virtual Reality Training

This overview presents the current state-of-the-art of self-adaptive technologies within virtual reality (VR) training. Virtual reality training and assessment is increasingly used for five key areas: medical, industrial & commercial training, serious games, rehabilitation and remote training such as Massive Open Online Courses (MOOCs). Adaptation can be applied to five core technologies of VR including haptic devices, stereo graphics, adaptive content, assessment and autonomous agents. Automation of VR training can contribute to automation of actual procedures including remote and robotic assisted surgery which reduces injury and improves accuracy of the procedure. Automated haptic interaction can enable tele-presence and virtual artefact tactile interaction from either remote or simulated environments. Automation, machine learning and data driven features play an important role in providing trainee-specific individual adaptive training content. Data from trainee assessment can form an input to autonomous systems for customised training and automated difficulty levels to match individual requirements. Self-adaptive technology has been developed previously within individual technologies of VR training. One of the conclusions of this research is that while it does not exist, an enhanced portable framework is needed and it would be beneficial to combine automation of core technologies, producing a reusable automation framework for VR training

An Interactive Virtual Audience Platform for Public Speaking Training

We have developed an interactive virtual audience platform for public speaking training. Users' public speaking behavior is automatically analyzed using audiovisual sensors. The virtual characters display indirect feedback depending on user's behavior descriptors correlated with public speaking performance. We used the system to collect a dataset of public speaking performances in different training conditions

Gesture Assessment of Teachers in an Immersive Rehearsal Environment

Interactive training environments typically include feedback mechanisms designed to help trainees improve their performance through either guided- or self-reflection. When the training system deals with human-to-human communications, as one would find in a teacher, counselor, enterprise culture or cross-cultural trainer, such feedback needs to focus on all aspects of human communication. This means that, in addition to verbal communication, nonverbal messages must be captured and analyzed for semantic meaning. The goal of this dissertation is to employ machine-learning algorithms that semi-automate and, where supported, automate event tagging in training systems developed to improve human-to-human interaction. The specific context in which we prototype and validate these models is the TeachLivE teacher rehearsal environment developed at the University of Central Florida. The choice of this environment was governed by its availability, large user population, extensibility and existing reflection tools found within the AMITIES framework underlying the TeachLivE system. Our contribution includes accuracy improvement of the existing data-driven gesture recognition utility from Microsoft; called Visual Gesture Builder. Using this proposed methodology and tracking sensors, we created a gesture database and used it for the implementation of our proposed online gesture recognition and feedback application. We also investigated multiple methods of feedback provision, including visual and haptics. The results from the conducted user studies indicate the positive impact of the proposed feedback applications and informed body language in teaching competency. In this dissertation, we describe the context in which the algorithms have been developed, the importance of recognizing nonverbal communication in this context, the means of providing semi- and fully-automated feedback associated with nonverbal messaging, and a series of preliminary studies developed to inform the research. Furthermore, we outline future research directions on new case studies, and multimodal annotation and analysis, in order to understand the synchrony of acoustic features and gestures in teaching context

An Interactive Virtual Audience Platform for Public Speaking Training (Demonstration)

International audienceWe have developed an interactive virtual audience platform for public speaking training. Users' public speaking behavior is automatically analyzed using audiovisual sensors. The virtual characters display indirect feedback depending on user's behavior descriptors correlated with public speaking performance. We used the system to collect a dataset of public speaking performances in different training conditions

Public Speaking Training with a Multimodal Interactive Virtual Audience Framework

International audienceWe have developed an interactive virtual audience platform for public speaking training. Users' public speaking behavior is automatically analyzed using multimodal sensors, and ultimodal feedback is produced by virtual characters and generic visual widgets depending on the user's behavior. The flexibility of our system allows to compare different interaction mediums (e.g. virtual reality vs normal interaction), social situations (e.g. one-on-one meetings vs large audiences) and trained behaviors (e.g. general public speaking performance vs specific behaviors)