Company-university collaboration in applying gamification to learning about insurance

Incorporating gamification into training–learning at universities is hampered by a shortage of quality, adapted educational video games. Large companies are leading in the creation of educational video games for their internal training or to enhance their public image and universities can benefit from collaborating. The aim of this research is to evaluate, both objectively and subjectively, the potential of the simulation game BugaMAP (developed by the MAPFRE Foundation) for university teaching about insurance. To this end, we have assessed both the game itself and the experience of using the game as perceived by 142 economics students from various degree plans and courses at the University of Seville during the 2017–2018 academic year. As a methodology, a checklist of gamification components is used for the objective evaluation, and an opinion questionnaire on the game experience is used for the subjective evaluation. Among the results several findings stand out. One is the high satisfaction of the students with the knowledge acquired using fun and social interaction. Another is that the role of the university professors and the company monitors turns out to be very active and necessary during the game-learning sessions. Finally, in addition to the benefits to the university of occasionally available quality games to accelerate student skills training, the company–university collaboration serves as a trial and refinement of innovative tools for game-based learning

Generating Instructions in a 3D Game Environment: Efficiency or Entertainment?

The GIVE Challenge was designed for the evaluation of natural language generation (NLG) systems. It involved the automatic generation of instructions for users in a 3D environment. In this paper we introduce two NLG systems that we developed for this challenge. One system focused on generating optimally helpful instructions while the other focused on entertainment. We used the data gathered in the Challenge to compare the efficiency and entertainment value of both systems. We found a clear difference in efficiency, but were unable to prove that one system was more entertaining than the other. This could be explained by the fact that the set-up and evaluation methods of the GIVE Challenge were not aimed at entertainment

Development of a Coding Instrument to Assess the Quality and Content of Anti-Tobacco Video Games

Previous research has shown the use of electronic video games as an effective method for increasing content knowledge about the risks of drugs and alcohol use for adolescents. Although best practice suggests that theory, health communication strategies, and game appeal are important characteristics for developing games, no instruments are currently available to examine the quality and content of tobacco prevention and cessation electronic games. This study presents the systematic development of a coding instrument to measure the quality, use of theory, and health communication strategies of tobacco cessation and prevention electronic games. Using previous research and expert review, a content analysis coding instrument measuring 67 characteristics was developed with three overarching categories: type and quality of games, theory and approach, and type and format of messages. Two trained coders applied the instrument to 88 games on four platforms (personal computer, Nintendo DS, iPhone, and Android phone) to field test the instrument. Cohen's kappa for each item ranged from 0.66 to 1.00, with an average kappa value of 0.97. Future research can adapt this coding instrument to games addressing other health issues. In addition, the instrument questions can serve as a useful guide for evidence-based game development.Food and Drug Administration (FDA) Center for Tobacco ProductsNational Cancer Institute (NCI) Office of Communication and EducationCommunication Studie

Challenge in Digital Games: Towards Developing a Measurement Tool

Challenge is arguably the most important experience that players seek in digital games. However, without a measure of how challenged players feel during the act of play, it is hard to design games that are neither too easy nor too hard and, therefore, truly enjoyable. Especially in industry, challenge is dominantly assessed by means of manual play testing in ad-hoc trials. The aim of this research is to create a more systematic, complete, and reliable instrument to evaluate the level of players' experienced challenge in games in the form of a questionnaire. This paper presents the key results from an extensive literature survey which will inform further development. We survey definitions of challenge, challenge types, and their relation to player experience based on the observations of game designers. We furthermore draw from empirical findings in a diverse range of fields such as game studies, human-computer interaction (HCI) and artificial intelligence (AI)

The Challenge of Believability in Video Games: Definitions, Agents Models and Imitation Learning

In this paper, we address the problem of creating believable agents (virtual characters) in video games. We consider only one meaning of believability, ``giving the feeling of being controlled by a player'', and outline the problem of its evaluation. We present several models for agents in games which can produce believable behaviours, both from industry and research. For high level of believability, learning and especially imitation learning seems to be the way to go. We make a quick overview of different approaches to make video games' agents learn from players. To conclude we propose a two-step method to develop new models for believable agents. First we must find the criteria for believability for our application and define an evaluation method. Then the model and the learning algorithm can be designed

Enhancing video game performance through an individualized biocybernetic system

Biocybernetic systems are physiological software systems that explicitly utilize physiological signals to control or adapt software functionality (Pope et al., 1995.) These systems have tremendous potential for innovation in human computer interaction by using physiological signals to infer a user\u27s emotional and mental states (Allanson & Fairclough, 2004; Fairclough, 2008). Nevertheless, development of these systems has been ultimately hindered by two fundamental challenges. First, these systems make generalizations about physiological indicators of cognitive states across populations when, in fact, relationships between physiological responses and cognitive states are specific to each individual (Andreassi, 2006). Second, they often employ largely inconsistent retrospective techniques to subjectively infer user\u27s mental state (Fairclough, 2008). An individualized biocybernetic system was developed to address the fundamental challenges of biocybernetic research. This system was used to adapt video game difficulty through real-time classifications of physiological responses to subjective appraisals. A study was conducted to determine the system\u27s ability to improve player\u27s performance. The results provide evidence of significant task performance increase and higher attained task difficulty when players interacted with the game using the system than without. This work offers researchers with an alternative method for software adaptation by conforming to the individual characteristics of each user