Review of Serious Energy Games : Objectives, Approaches, Applications, Data Integration, and Performance Assessment

In recent years, serious energy games (SEGs) garnered increasing attention as an innovative and effective approach to tackling energy-related challenges. This review delves into the multifaceted landscape of SEG, specifically focusing on their wide-ranging applications in various contexts. The study investigates potential enhancements in user engagement achieved through integrating social connections, personalization, and data integration. Among the main challenges identified, previous studies overlooked the full potential of serious games in addressing emerging needs in energy systems, opting for oversimplified approaches. Further, these studies exhibit limited scalability and constrained generalizability, which poses challenges in applying their findings to larger energy systems and diverse scenarios. By incorporating lessons learned from prior experiences, this review aims to propel the development of SEG toward more innovative and impactful directions. It is firmly believed that positive behavior changes among individuals can be effectively encouraged by using SEG

Set-theoretical and Combinatorial Instruments for Problem Space Analysis in Adaptive Serious Games.

The Computerized Adaptive Practice (CAP) system describes a set of algorithms for assessing player’s expertise and difficulties of in-game problems and for adapting the latter to the former. However, an effective use of CAP requires that in-game problems are designed carefully and refined over time to avoid possible barriers to learning. This study proposes a methodology and three different instruments for analyzing the problem set in CAP-enabled games. The instruments include the Guttman scale, a ranked order, and a Hasse diagram that offer analysis at different levels of granularity and complexity. The methodology proposes to use quantified difficulty measures to infer topology of the problem set. It is well-suited for serious games that emphasize practice and repetitive play. The emphasis is put on the simplicity of use and visualization of the problem space to maximally support teachers and game developers in designing and refining CAP-enabled games. Two case studies demonstrate practical applications of the proposed instruments on empirical data. Future research directions are proposed to address potential drawbacks.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

Constructing delta realities; Joint Fact Finding challenges in Serious Game Design

__Abstract__ This paper addresses the challenges of Joint Fact Finding (JFF) in spatial planning and design. JFF is an important component of a deliberative planning practice: The construction of (problematic) realities is fundamental for the formulation of challenges and solutions. Information is often contested in complex planning processes due to different interests, values and perspectives. Carefully designed interaction procedures are needed to negotiate the relevance and validity of information sources. Particularly promising procedures for this are Serious Games: Facilitating joint reality construction through immersive simulations, they are appealing ways to engage not only knowledge-oriented researchers, but also practice-oriented stakeholders and professionals. Their concreteness speaks to spatial planning and design as crafts. Still, the development of such games is not without its challenges and trade-offs. As procedures for reality construction, they cannot escape the power-laden nature of knowledge. We present a case study on developing a spatial design-oriented game, and analyze it in the tradition of the sociology of translations, aided by literature on serious game development. As indicated, Serious Games could function as JFF procedures in spatial planning and design. Moreover, their architecture can be considered a ‘boundary object’ providing actors an environment that accommodates information sharing, learning and joint reality construction. In this way the game facilitates the building of capacity to generate and integrate knowledge for spatial planning and design. In our project on integrative planning in delta areas, the game architecture accommodated researchers and practitioners in governance, spatial design and geo-information. Striving for interdisciplinary synergies, the game architecture was to be accordingly polyvalent. Its main innovative features would be its generative and integrative capacity, i.e. its capacity to both co-produce and integrate a diversity of information sources and to co-develop/generate spatial designs on this basis. How can joint fact finding in spatial planning and design be organized through a serious game in such a way that it develops integrative and generative capacity, and which challenges and trade-offs are faced in realizing this goal? In this paper we describe and discuss the practical sh

A dynamic difficulty adjustment model for dysphonia therapy games

CMUP-ERI/TIC/0033/2014Studies on childhood dysphonia have revealed considerable rates for voice disorders in 4 – 12 year-old children. The sustained vowel exercise is widely used as a technique in the vocal (re)education process. However this exercise can become tedious after a short practice. Here, we propose a novel dynamic difficulty adjustment model to be used in a serious game with the sustained vowel exercise to motivate children on practicing this exercise often. The model automatically adapts the difficulty of the challenges in response to the child’s performance. The model is not exclusive to this game and can be used in other games for dysphonia treatment. In order to measure the child’s performance, the model uses parameters that are relevant to the therapy treatment. The proposed model is based on the flow model in order to balance the difficulty of the challenges with the child’s skills.publishersversionpublishe

Using genetic algorithms for real-time dynamic difficulty adjustment in games

Dynamic Difficulty Adjustment is the area of research that seeks ways to balance game difficulty with challenge, making it an engaging experience for all types of players, from novice to veteran, without making it frustrating or boring. In this dissertation we propose an approach that aims to evolve agents, in this case predators, as a group and in real time, in a way that they adapt to a changing environment. We showcase our approach after using a generic genetic algorithm in two scenarios, pitting the predators vs passive prey in one scenario and pitting the predators vs aggressive prey in another, this is done to create a basis for our approach and then test our algorithm in four different scenarios, the first two are the same as the generic genetic algorithm and in the next two we switch prey in the middle of the experience progressively from passive to aggressive or vice versa.Adaptação Dinâmica de Dificuldade é a área de pesquisa que procura formas de equilibrar a dificuldade do jogo com o desafio, tornando-o uma experiência envolvente para todos os tipos de jogadores, desde principiantes a veteranos, sem o tornar frustrante ou aborrecido. Nesta dissertação propomos uma abordagem que visa evoluir os agentes, neste caso predadores, como um grupo e em tempo real, de forma a que estes se adaptem a um ambiente em mudança. Nós mostramos a nossa abordagem depois de usar um algoritmo genético genérico em dois cenários, colocando os predadores versus presas passivas num cenário e colocando os predadores versus presas agressivas noutro, isto é feito para criar uma base para a nossa abordagem e depois testamos o nosso algoritmo em quatro cenários diferentes, os dois primeiros são os mesmos que o algoritmo genético genérico e nos dois seguintes trocamos as presas a meio da experiência progressivamente de passivas para agressivas ou vice-versa