Abstract The application of virtual reality (VR) technology for immersive training shows promise in a variety of tasks, including cycling. However, methods that use head mounted displays (HMDs) are bulky, expensive and difficult to work with for larger groups of students. In this paper, we explore the utility of common and ubiquitous mobile devices in semi-immersive cycle training. We present the development of a technical architecture for synchronised semi-immersive training, featuring centralised 360 $$^{\circ }$$ video playback controls for instructors. We conducted interviews with four groups of students aged 9-11 and three instructors. Furthermore, we collected survey data from 67 students across three different groups. We report that students and instructors alike, find this approach to be effective, immersive and highly accessible.

Alternative text (alt text) is one of the most prevalent Web accessibility barriers affecting a wide range of media. Despite manifold efforts addressing its absence, recent work highlighted that unsuitable alt text is equally problematic and is underpinned by a lack of understanding and guidelines on what constitutes suitable alt text. In this work, we present an empirical exploratory study that investigates perceptions of Web content creators and visually impaired users on suitable alt text to bridge the functional gap between experiences and best available practice. Following a qualitative approach, 11 Web content creators and 11 visually impaired users were interviewed, and findings are reported on Web accessibility via screen readers and reasons for its deprioritization, WCAG conformance, and perceptions on alt text authorship, and suitability. The first much-needed trainability and suitability recommendations for alt text suitability are further proposed, and avenues for future work are discussed.

Generative systems for graphical assets have the potential to provide users with high quality assets at the push of a button. However, there are many forms of assets, and many approaches for producing them. Quantitative evaluation of these methods is necessary if practitioners wish to validate or compare their implementations. Furthermore, providing benchmarks for new methods to strive for or surpass. While most methods are validated using tried-and-tested metrics within their own domains, there is no unified method of finding the most appropriate. We present a framework based on a literature pool of close to 200 papers, that provides guidance in selecting metrics to evaluate the validity and quality of artefacts produced, and the operational capabilities of the method.

Decision making is a core cognitive process of human behaviour that is often affected by stress. Whilst we make several decisions on a daily basis, firefighters in particular are called to make important decisions in a split second and within life-threatening settings. Stress can therefore impact their ability to perform and carry out their job. The implications of stress are similarly important in other settings requiring high-vigilance. In this paper, we aim to contribute to efforts to better train firefighters in decision making in stressful situations through a serious game solution. The game was designed based on the Stress Exposure Training (SET) approach and in accordance with typical stressors identified in the literature. Those were then mapped to relevant game mechanics. The evaluation of the resulting game was twofold: A. to assess its ability to increase participants’ stress level, and B. to investigate whether decision making performance would be improved for participants under stress. The proposed framework and the prototype were evaluated through empirical research that consisted of the participants’ self-reported stress levels using the State-Trait Anxiety Inventory for Adults (STAI) and the participants’ physiological measurements, namely galvanic skin response (GSR) and heart rate (HR). Our results demonstrate the potential of serious games to assist towards training of firefighters to make better decisions under stressful situations. Our findings are of wider importance as they contribute to ongoing efforts to improve decision making under stress in a variety of settings and scenarios.

Designers are often faced with the challenge of following web accessibility guidelines that are complex and ambiguous, and therefore hard to use. This is evidenced by the low percentage of public websites that comply fully with web accessibility standards worldwide. Lack of engagement among designers to follow established web accessibility guidelines is often accounted for this issue. In this paper, we address designers’ lack of engagement through a serious game called GATE which is based on the Web Content Accessibility Guidelines (WCAG). We followed a User-Centred approach by identifying user types of designers through an online survey. We then mapped these user types and the WCAG to relevant game mechanics. The resulting game was evaluated with designers for its perceived effectiveness, user engagement, and user satisfaction using a mixed methods approach. Our results demonstrate the potential of GATE which offers designers an innovative and engaging solution towards the wider adoption of web accessibility guidelines.

Abstract Presentations are the most successful and popular form of communication in business. However, the formats of presentations in business have not changed much for past few decades. The emergent and disruptive technologies such as Augmented Reality and Animated Infographics have provided potential for enhancing communications in businesses to increase engagement and therefore increasing the effectiveness of such communications. This paper focuses on the impact and effectiveness of using interactive AR in business presentations. The paper presents the design and development of our AR presentation application. Followed by a presentation of an empirical study into the usability and effectiveness of using Augmented Reality and Animated Infographics in business presentation and compares the results against the traditional slideware slides presentation approach. The results of the experiment with 94 participants are presented and analysed. The results demonstrate that the AR approach out performs the traditional methods in terms of usability, audience engagement and effectiveness of communication.

This article focuses on using deep reinforcement learning, specifically proximity policy optimization, to train agents in a social dilemma game, modified dictator game, in order to investigate the effect of selfishness and altruism on the believability of the game agents. We present the design and implementation of the training environment, including the reward functions which are based on the findings of established empirical research, with three agent profiles mapped to the three standard constant elasticity of substitution (CES) utility functions, i.e., selfish, perfect substitutes, and Leontief, which measure different levels of selfishness/altruism. The trained models are validated and then used in a sample game, which is used to evaluate the believability of the three agent profiles using the agent believability metrics. The results indicate that players find altruistic behaviour more believable and consider selfishness less so. Analysis of the results indicates that human-like behavior resulting from the application of artificial intelligence evolves from perceived human behavior rather than the observed. The analysis also indicates that selfishness/altruism may be considered as an extra dimension to be included in the believability metrics.

Harnessing the power of Web communities, the effort on creating metadata can be greatly reduced. Collaborative communities can create, update and maintain content models for multimedia resources more effectively than single users working alone. This paper presents MC2, a framework for MPEG-7 content-modelling communities. MC2 is based on the challenges to collaborative multimedia content modelling reported in the research literature and the results of an experiment undertaken to investigate user behaviour in collaborative content modelling. An MC2 service has also been implemented as a proof of concept for this framework, which is evaluated with a population of users and against the challenges.