Affective educational games and the evolving teaching experience

Teaching methods must adapt to learners’ expectations. Computer game-based learning environments enable learning through experimentation and are inherently motivational. However, for identifying when learners achieve learning goals and providing suitable feedback, Intelligent Tutoring Systems must be used. Recognizing the learner’s affective state enables educational games to improve the learner’s experience or to distinguish relevant emotions. This chapter discusses the creation of an affective student model that infers the learner’s emotions from cognitive and motivational variables through observable behavior. The control-value theory of ‘achievement emotions’ provides a basis for this work. A Probabilistic Relational Models (PRMs) approach for affective student modeling, which is based on Dynamic Bayesian Networks, is discussed. The approach is tested through a prototyping study based on Wizard-of-Oz experiments and preliminary results are presented. The affective student model will be incorporated into PlayPhysics, an emotional game-based learning environment for teaching Physics. PRMs facilitate the design of student models with Bayesian Networks. The effectiveness of PlayPhysics will be evaluated by comparing the students’ learning gains and learning efficiencies.</jats:p

Affective games:a multimodal classification system

Affective gaming is a relatively new field of research that exploits human emotions to influence gameplay for an enhanced player experience. Changes in player’s psychology reflect on their behaviour and physiology, hence recognition of such variation is a core element in affective games. Complementary sources of affect offer more reliable recognition, especially in contexts where one modality is partial or unavailable. As a multimodal recognition system, affect-aware games are subject to the practical difficulties met by traditional trained classifiers. In addition, inherited game-related challenges in terms of data collection and performance arise while attempting to sustain an acceptable level of immersion. Most existing scenarios employ sensors that offer limited freedom of movement resulting in less realistic experiences. Recent advances now offer technology that allows players to communicate more freely and naturally with the game, and furthermore, control it without the use of input devices. However, the affective game industry is still in its infancy and definitely needs to catch up with the current life-like level of adaptation provided by graphics and animation

D3.1 – First Bundle of Core Social Agency Assets

This deliverable presents and describes the first delivery of assets that are part of the core social agency bundle. In total, the bundle includes 16 assets, divided into 4 main categories. Each category is related to a type of challenge that developers of applied games are typically faced with and the aim of the included assets is to provide solutions to those challenges. The main goal of this document is to provide the reader with a description for each included asset, accompanied by links to their source code, distributable versions, demonstrations and documentation. A short discussion of what are the future steps for each asset is also given. The primary audience for the contents of this deliverable are the game developers, both inside and outside of the project, which can use this document as an official list of the current social agency assets and their associated resources. Note that the information about which RAGE use cases are using which of these assets is described in Deliverable 4.2.This study is part of the RAGE project. The RAGE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains

Player agency in interactive narrative: audience, actor & author

The question motivating this review paper is, how can computer-based interactive narrative be used as a constructivist learn- ing activity? The paper proposes that player agency can be used to link interactive narrative to learner agency in constructivist theory, and to classify approaches to interactive narrative. The traditional question driving research in interactive narrative is, ‘how can an in- teractive narrative deal with a high degree of player agency, while maintaining a coherent and well-formed narrative?’ This question derives from an Aristotelian approach to interactive narrative that, as the question shows, is inherently antagonistic to player agency. Within this approach, player agency must be restricted and manip- ulated to maintain the narrative. Two alternative approaches based on Brecht’s Epic Theatre and Boal’s Theatre of the Oppressed are reviewed. If a Boalian approach to interactive narrative is taken the conflict between narrative and player agency dissolves. The question that emerges from this approach is quite different from the traditional question above, and presents a more useful approach to applying in- teractive narrative as a constructivist learning activity

AEINS: Interactive Narrative Role in Fostering Character Education

Promoting ethical, responsible, and caring young people is a perennial aim of education. Efforts have been done to find other teaching ways other than traditional ones such as games and role play. Narrative-based computer games have found their way as engaging learning platforms that allow collaboration of humans and computers in the creation of innovative experiences. In this paper, we focus on the design of an adaptive, interactive narrative model that makes use of a student model to provide an individualized story-path and an individualized learning process. In other words, we aim to have strong learning objectives underpinned by effective story telling. The adaptive narrative model has been deployed in the educational game environment, AEINS, along with the use of the Socratic Method and pedagogical agents to help teaching in the ethics domain. Evaluation results indicate the usefulness of the design and provide evidence on the development of moral reasoning and the transfer of moral virtues to its users