This paper describes a demo for the Persuasive Conference 2014 (21-23 May, Padua, Italy) which shows the result of a design project in the edutainment field. The tries to raise safety awareness among construction site workers. The purpose of the demo is to raise safety awareness amongst construction site workers via an immersive serious game. The demo has been made by students of the Art and Technology bachelor course at Saxion University of Applied Sciences and students Human Media Interaction at the University of Twente.
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Virtual, Augmented and Mixed Reality technologies are embraced by designers, scholars and charities alike, some primarily for their entertaining properties, others also for the opportunities in education, motivation or persuasion. Applications with the latter objective, that of persuasion, are designed not only to be entertaining, but are also designed (or framed) to shape how players think and feel about issues in reality. However, despite the growing interest in the persuasive opportunities of these immersive technologies, we still lack the design strategies and best-practices that could support in the design of these ‘immersive persuasive games’. To address this still-unexplored and fragmented design space, we organize a design-oriented workshop that brings together academia and industry. The workshop is informed by a Research through Design approach in which the primary focus is to generate knowledge through designing. Participants design and evaluate ideas on-the-spot in an iterative manner using low-fidelity, life-size, prototyping and role-playing techniques, thereby mimicking an embodied interactive immersive environment. By reflecting on design practices and player experiences, we construct a body of knowledge, built exemplar work and distil best-practices to formulate design strategies for the design of immersive persuasive games.
Background: Although physical activity (PA) has positive effects on health and well-being, physical inactivity is a worldwide problem. Mobile health interventions have been shown to be effective in promoting PA. Personalizing persuasive strategies improves intervention success and can be conducted using machine learning (ML). For PA, several studies have addressed personalized persuasive strategies without ML, whereas others have included personalization using ML without focusing on persuasive strategies. An overview of studies discussing ML to personalize persuasive strategies in PA-promoting interventions and corresponding categorizations could be helpful for such interventions to be designed in the future but is still missing. Objective: First, we aimed to provide an overview of implemented ML techniques to personalize persuasive strategies in mobile health interventions promoting PA. Moreover, we aimed to present a categorization overview as a starting point for applying ML techniques in this field. Methods: A scoping review was conducted based on the framework by Arksey and O’Malley and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) criteria. Scopus, Web of Science, and PubMed were searched for studies that included ML to personalize persuasive strategies in interventions promoting PA. Papers were screened using the ASReview software. From the included papers, categorized by the research project they belonged to, we extracted data regarding general study information, target group, PA intervention, implemented technology, and study details. On the basis of the analysis of these data, a categorization overview was given. Results: In total, 40 papers belonging to 27 different projects were included. These papers could be categorized in 4 groups based on their dimension of personalization. Then, for each dimension, 1 or 2 persuasive strategy categories were found together with a type of ML. The overview resulted in a categorization consisting of 3 levels: dimension of personalization, persuasive strategy, and type of ML. When personalizing the timing of the messages, most projects implemented reinforcement learning to personalize the timing of reminders and supervised learning (SL) to personalize the timing of feedback, monitoring, and goal-setting messages. Regarding the content of the messages, most projects implemented SL to personalize PA suggestions and feedback or educational messages. For personalizing PA suggestions, SL can be implemented either alone or combined with a recommender system. Finally, reinforcement learning was mostly used to personalize the type of feedback messages. Conclusions: The overview of all implemented persuasive strategies and their corresponding ML methods is insightful for this interdisciplinary field. Moreover, it led to a categorization overview that provides insights into the design and development of personalized persuasive strategies to promote PA. In future papers, the categorization overview might be expanded with additional layers to specify ML methods or additional dimensions of personalization and persuasive strategies.
Measuring and designing user experience in retail and gaming virtual reality using a CAVE set-up In this project we designed and measured user experiences in a CAVE virtual reality set-up. Virtually all studies have taken the form of experiment studies and have been conducted among consumers (in total more than 1500 consumers) who had to visit the virtual world with assignments based on which behaviour has been observed and after which a survey was conducted afterwards. The studies were carried out within the three lines of inquiry: a. Branded games / in-game advertising, revealing (positive) effects of in-game advertising on attention and attitude based on logos and faces incorporated into the games. Various applications (prototypes) have been developed that stimulate the shopping experience and the interaction between shop and consumer. (b) FMCG: studies answered the question which factors influence search and choice behaviour in the supermarket. On the basis of the studies, the clients have designed new packaging and adapted existing designs, deployed new shelf layouts, developed and implemented new Retail strategies, optimized instore communication and (e) the knowledge about consumer behaviour in the supermarket within the organization has been increased. (c) Location Based Advertising: recommendations have been made for the partners concerned and the field of work on (a) development of non-intrusive pervasive/ubiquitous advertising concepts (2nd screen, LBA, gaze-based advertising etc.), (b) development of virtual test environments and associated interaction methods and (c) exploration and review of theoretical models for persuasive communication and behavioural influence. Partners: Heinz, Nokia, DVJ-Insights, Radboud University, Brand Loyalty, IRI, Talpa, TU/e, Philips
