Gaétan Deglorie

Enabling Control of 3D Visuals, Scenarios and Non-linear Gameplay in Serious Game Development Through Model-Driven Authoring

Due to the absence of high-level authoring environments and support for non-technical domain experts to create custom serious games, a model-driven authoring framework is presented in this paper. Through model-driven authoring, non-technical people can manipulate the 3D visuals of their serious game, model the scenarios of the game, and even easily add non-linear narrative to the game. The different tools and methods have been implemented and are currently used to build a serious game for the Friendly ATTAC project in order to help youngsters who are confronted with cyberbullying. The presented model-driven authoring framework enables non-technical domain experts to produce serious games easily and quickly, at a lower cost, and therefore lowers the barriers that hinder the production of serious games.

SERIOUS GAME DEVELOPMENT AND DYNAMIC TAILORING THROUGH MODEL-DRIVEN AUTHORING

This paper presents a model-driven authoring framework and toolset that enables to produce serious games easily and quickly, at lower cost and with the active involvement of (non-IT schooled) domain experts, and therefore lowers the barriers that hinder the production of serious games. Furthermore, the toolset allows for the creation of games with an adaptive narrative that can be played several times without becoming predictable by adapting the gameplay based on the real-time input of the player or post-game feedback. Choices made by the player have an influence on the overarching narrative of the game, which in turn will be used to select appropriate narrative events for the new context. Each narrative event can focus on a different subset of the learning objectives. The authoring framework is used within the Friendly ATTAC project, a project that helps youngsters dealing with cyberbullying issues through an innovative serious game. By using the toolset developed, it was possible for the non-technical people (subject-matter experts) to be actively involved in the development of the serious game, to make the development process much more iterative, and at the same time to shorten the overall development time. The toolbox was successfully used to design levels that are afterwards used to fully automatically create playable adaptive game scenarios.

Psychometric data of a questionnaire to measure cyberbullying bystander behavior and its behavioral determinants among adolescents

.This paper describes the items, scale validity and scale reliability of a self-report questionnaire that measures bystander behavior in cyberbullying incidents among adolescents, and its behavioral determinants. Determinants included behavioral intention, behavioral attitudes, moral disengagement attitudes, outcome expectations, self-efficacy, subjective norm and social skills. Questions also assessed (cyber-)bullying involvement. Validity and reliability information is based on a sample of 238 adolescents (M age=13.52 years, SD=0.57). Construct validity was assessed using Confirmatory Factor Analysis (CFA) or Exploratory Factor Analysis (EFA) in Mplus7 software. Reliability (Cronbach Alpha, α) was assessed in SPSS, version 22. Data and questionnaire are included in this article. Further information can be found in DeSmet et al. (2018) [1].

Extensible multi-domain generation of Virtual Worlds using blackboards

Procedural generation of large virtual worlds remains a challenge, because current procedural methods mainly focus on generating assets for a single content domain, such as height maps, trees or buildings. Furthermore current approaches for multi-domain content generation, i.e. generating complete virtual environments, are often too ad-hoc to allow for varying design constraints from creatives industries such as the development of video games. In this paper, we propose a multi-domain procedural generation method that uses modularized, single-domain generation methods that interact on the data level while operating independently. Our method uses a blackboard architecture specialized to fit the needs of procedural content generation. We show that our approach is extensible to a wide range of use cases of virtual world generation and that manual or procedural editing of the generated content of one generator is automatically communicated to the other generators, which ensures a consistent and coherent virtual world. Furthermore, the blackboard approach automatically reasons about the generation process which allows 52% to 98% of the activations, i.e. executions of the single-domain content generators, to be discarded without compromising the generated content, resulting in better performing large world generation.