Search Results (760)

This study presents the validation of the Player Personality and Dynamics Scale (PPDS), designed to identify player profiles in educational gamification contexts with narrative elements. Through a sample of 635 participants, a questionnaire was developed and applied, covering sociodemographic data, lifestyle habits, gaming practices, and a classification system of 40 items on a six-point Likert scale. The results of the factorial analysis confirm a structure of five factors: Toxic Profile, Joker Profile, Tryhard Profile, Aesthetic Profile, and Coacher Profile, with high fit and reliability indices (RMSEA = 0.06; CFI = 0.95; TLI = 0.91). The resulting classification enables the design of personalized gamified experiences that enhance learning and interaction in the classroom, highlighting the importance of understanding players’ motivations to better adapt educational dynamics. Applying this scale fosters meaningful learning through the creation of narratives tailored to students’ individual preferences. Full article

Background and Objectives: Depression is a leading cause of disability globally, with treatment challenges including limited access, stigma, and poor adherence. Gamification, which applies game elements such as points, levels, and storytelling into non-game contexts, offers a promising strategy to enhance engagement and augment traditional treatments. Our research is the first study designed to explore the implementation of gamification within the Malaysian context. The objective was to explore the feasibility of implementation of gamification as an adjunctive treatment for adults with depression. Materials and Methods: Focus group discussions were held with five mental health professionals and ten patients diagnosed with moderate depression. The qualitative component assessed perceptions of gamified interventions, while quantitative measures evaluated participants’ depressive and anxiety symptomatology. Results: Three key themes were identified: (1) understanding of gamification as a treatment option, (2) factors influencing its acceptance, and (3) characteristics of a practical and feasible intervention. Clinicians saw potential in gamification to boost motivation, support psychoeducation, and encourage self-paced learning, but they expressed concerns about possible addiction, stigma, and the complexity of gameplay for some patients. Patients spoke of gaming as a source of comfort, escapism, and social connection. Acceptance was shaped by engaging storylines, intuitive design, balanced difficulty, therapist guidance, and clear safety measures. Both groups agreed that gamification should be used in conjunction with standard treatments, be culturally sensitive, and be presented as a meaningful therapeutic approach rather than merely as entertainment. Conclusions: Gamification emerges as an acceptable and feasible supplementary approach for managing depression in Malaysia. Its success depends on culturally sensitive design, robust clinical oversight, and seamless integration with existing care pathways. Future studies should investigate long-term outcomes and establish guidelines for the safe and effective implementation of this approach. We recommend targeted investment into culturally adapted gamified tools, including training, policy development, and collaboration with key stakeholders to realistically implement gamification as a mental health intervention in Malaysia. Full article

Achieving the construction sector’s dual carbon objectives necessitates scaling green energy adoption in new residential buildings. The current literature critically overlooks four unresolved problems: oversimplified penalty mechanisms, ignoring escalating regulatory costs; static subsidies misaligned with market maturity evolution; systematic exclusion of innovation feedback from energy suppliers; and underexplored behavioral evolution of building owners. This study establishes a government–suppliers–owners evolutionary game framework with dynamically calibrated policies, simulated using MATLAB multi-scenario analysis. Novel findings demonstrate: (1) A dual-threshold penalty effect where excessive fines diminish policy returns due to regulatory costs, requiring dynamic calibration distinct from fixed-penalty approaches; (2) Market-maturity-phased subsidies increasing owner adoption probability by 30% through staged progression; (3) Energy suppliers’ cost-reducing innovations as pivotal feedback drivers resolving coordination failures, overlooked in prior tripartite models; (4) Owners’ adoption motivation shifts from short-term economic incentives to environmentally driven decisions under policy guidance. The framework resolves these gaps through integrated dynamic mechanisms, providing policymakers with evidence-based regulatory thresholds, energy suppliers with cost-reduction targets, and academia with replicable modeling tools. Full article

Children are not only concerned about fairness but also care for others. This study examined how experimentally induced empathic concern influences children’s responses to inequity, particularly when fairness considerations may conflict with empathy-driven motivations. A sample of 10- to 12-year-old children (N = 111, 62 boys, 49 girls) from China were randomly assigned to an empathic or non-empathic condition and completed multiple rounds of ultimatum and dictator games, acting as recipients and proposers. The results showed that children in the empathic concern condition were more likely to accept disadvantageous offers (F (1, 109) = 10.723, p = 0.001) and reject advantageous offers (F (1, 109) = 11.200, p = 0.001) than those in the non-empathic condition. Furthermore, in the dictator game, children in the empathic condition shared significantly more resources with the same protagonist (F (1, 109) = 110.740, p < 0.001). These findings suggest that empathic concern affects children’s inequity aversion and that empathic concern takes priority in guiding children’s inequity aversion when it conflicts with the fairness criterion. Moreover, our findings suggest that altruistic motivations potentially play a role in children’s responses to their inequity aversion. Full article

This paper presents a qualitative case study on the design, implementation, and validation of the Art Nouveau Path, a mobile augmented reality game developed to foster sustainability competences through engagement with Aveiro’s Art Nouveau built heritage. Grounded in the GreenComp framework and developed through a Design-Based Research approach, the game integrates location-based interaction, narrative storytelling, and multimodal augmented reality and multimedia content to activate key competences such as systems thinking, futures literacy, and sustainability-oriented action. The game was validated with 33 in-service schoolteachers, both through a simulation-based training workshop and a curricular review of the game. A mixed-methods strategy was used, combining structured questionnaires, open-ended reflections, and curricular review. The findings revealed strong emotional and motivational engagement, interdisciplinary relevance, and alignment with formal education goals. Teachers emphasized the game’s capacity to connect local identity with global sustainability challenges through immersive and reflective experiences. Limitations pointed to the need for enhanced pedagogical scaffolding, clearer integration into STEAM subjects, and broader accessibility across technological contexts. This study demonstrates that these games, when grounded in competence-based frameworks and inclusive design, can meaningfully support multimodal, situated learning for sustainability and offer valuable contributions to pedagogical innovation in Education for Sustainable Development. Full article

The contemporary digital era has fundamentally reshaped pupil education. It has transformed learning into a dynamic environment with enhanced access to information. The focus shifts to the educator, who must employ teaching strategies, practices, and methods to engage and motivate the pupils. New possibilities are emerging for adopting active pedagogical approaches. One example is the use of educational online escape games. In the theoretical part of this paper, we present online escape games as a tool that broadens pedagogical opportunities for schools in primary school chemistry education. These activities are known to foster pupils’ transversal or soft skills. We investigate the practical dimension of implementing escape games in education. This pilot study aims to analyse primary school teachers’ perceptions of online escape games. We collected data using Q methodology and conducted the Q-sort through digital technology. Data analysis utilised both the PQMethod programme and ChatGPT 4-o, with a subsequent comparison of their respective outputs. Although some numerical differences appeared between the ChatGPT and PQMethod analyses, both methods yielded the same factor saturation and overall results. Full article

The Sustainable Development Goals (SDGs), launched by the United Nations in 2015, outline 17 interconnected objectives designed to promote human well-being and sustainable development worldwide. Education is recognized by the United Nations as a key factor in promoting sustainable development. To cultivate students with both global perspectives and local engagement, it is essential to integrate sustainability education into elementary curricula. Accordingly, this study aimed to enhance elementary school students’ understanding of the SDGs by designing a structured instructional activity and developing a hybrid digital-physical board game. The game was implemented as a supplementary review tool to traditional classroom teaching, leveraging the motivational and knowledge-retention benefits of physical board games while incorporating digital features to support learning process monitoring. To address the limitations of conventional review approaches—such as reduced student engagement and increased cognitive load—the instructional model incorporated the board game during review sessions following formal instruction. This was intended to maintain student attention and reduce unnecessary cognitive effort, thereby supporting learning in sustainability-related content. A quasi-experimental design was employed to evaluate the effectiveness of the instructional intervention and the board game system, focusing on three outcome variables: learning motivation, cognitive load, and learning achievement. The results indicated that students in the game-based Sustainable Development Goals group achieved significantly higher delayed posttest scores (M = 72.91, SD = 15.17) than the traditional review group (M = 61.30, SD = 22.82; p < 0.05). In addition, they reported significantly higher learning motivation (M = 4.40, SD = 0.64) compared to the traditional group (M = 3.99, SD = 0.69; p < 0.05) and lower cognitive load (M = 1.84, SD = 1.39) compared to the traditional group (M = 2.66, SD = 1.30; p < 0.05), suggesting that the proposed approach effectively supported student learning in sustainability education at the elementary level. Full article

Stroke often leads to severe motor impairment, especially in the upper limbs, greatly reducing a patient’s ability to perform daily tasks. Effective rehabilitation is essential to restore function and improve quality of life. Traditional therapies, while useful, may lack engagement, leading to low motivation and poor adherence. Gamification—using game-like elements in non-game contexts—offers a promising way to make rehabilitation more engaging. The authors explore a gamified rehabilitation system designed in Unity 3D using a Kinect V2 camera. The game includes key features such as adjustable difficulty, real-time and predominantly positive feedback, user friendliness, and data tracking for progress. The evaluations were conducted with 18 healthy participants, most of whom had prior virtual reality experience. About 77% found the application highly motivating. While the gameplay was well received, the visual design was noted as lacking engagement. Importantly, all users agreed that the game offers a broad range of difficulty levels, making it accessible to various users. The results suggest that the system has strong potential to improve rehabilitation outcomes and encourage long-term use through enhanced motivation and interactivity. Full article

The need to improve medical diagnosis is of utmost importance in medical research, consisting of the optimization of accurate classification models able to assist clinical decisions. To minimize the errors that can be caused by using a single classifier, the voting ensemble technique can be used, combining the classification results of different classifiers to improve the final classification performance. This paper aims to compare the existing voting ensemble techniques with a new game-theory-derived approach based on Shapley values. We extended this method, originally developed for binary tasks, to the multi-class setting in order to capture complementary information provided by different classifiers. In heterogeneous clinical scenarios such as thyroid nodule diagnosis, where distinct models may be better suited to identify specific subtypes (e.g., benign, malignant, or inflammatory lesions), ensemble strategies capable of leveraging these strengths are particularly valuable. The motivating application focuses on the classification of thyroid cancer nodules whose cytopathological clinical diagnosis is typically characterized by a high number of false positive cases that may result in unnecessary thyroidectomy. We apply and compare the performance of seven individual classifiers, along with four ensemble voting techniques (including Shapley values), in a real-world study focused on classifying thyroid cancer nodules using proteomic features obtained through mass spectrometry. Our results indicate a slight improvement in the classification accuracy for ensemble systems compared to the performance of single classifiers. Although the Shapley value-based voting method remains comparable to the other voting methods, we envision this new ensemble approach could be effective in improving the performance of single classifiers in further applications, especially when complementary algorithms are considered in the ensemble. The application of these techniques can lead to the development of new tools to assist clinicians in diagnosing thyroid cancer using proteomic features derived from mass spectrometry. Full article

Reinforcement learning (RL), a branch of artificial intelligence (AI), is becoming more popular in a variety of application fields such as games, workplaces, and behavioral analysis, due to its ability to model complex decision-making through interaction and feedback. Traditional systems for personality and behavior assessment often rely on self-reported questionnaires, which are prone to bias and manipulation. RL offers a compelling alternative by generating diverse, objective behavioral data through agent–environment interactions. In this paper, we propose a Reinforcement Learning-based framework in a game environment, where agents simulate personality-driven behavior using context-aware policies and exhibit a wide range of realistic actions. Our method, which is based on the OCEAN Five personality model—openness, conscientiousness, extroversion, agreeableness, and neuroticism—relates psychological profiles to in-game decision-making patterns. The agents are allowed to operate in numerous environments, observe behaviors that were modeled using another simulation system (HiDAC) and develop the skills needed to navigate and complete tasks. As a result, we are able to identify the personality types and team configurations that have the greatest effects on task performance and collaboration effectiveness. Using interaction data derived from self-play, we investigate the relationships between behaviors motivated by the personalities of the agents, communication styles, and team outcomes. The results demonstrate that in addition to having an effect on performance, personality-aware agents provide a solid methodology for producing realistic behavioral data, developing adaptive NPCs, and evaluating team-based scenarios in challenging settings. Full article

As health and well-being become central concerns in the post-pandemic tourism landscape, health tourism is evolving to prioritize not only physical recovery but also psychological engagement and emotional value. This study explores how gamified design can enhance tourist participation and experience quality within health-related tourism contexts. By integrating theories from tourism psychology and game-based experience design, a structural equation model is proposed to examine the relationships among memorable tourism experiences, tourist motivation, game design elements, flow experience, and perceived value, and their joint influence on behavioral intention. Data collected from tourists who engaged in gamified experiences were analyzed using structural equation modeling (SEM) techniques. The results identify a dynamic “participation–immersion–value” mechanism, in which gameful design fosters flow and perceived value, thereby mediating gamification’s impact on behavioral intention. These findings offer valuable insights for health tourism developers and experience designers seeking to create emotionally engaging, motivating, and sustainable visitor experiences in the context of health and well-being. Full article

The integration of digital serious games into speech learning (rehabilitation) has demonstrated significant potential in enhancing accessibility and inclusivity for children with speech disabilities. This review of the state of the art examines the role of serious games, Artificial Intelligence (AI), and Natural Language Processing (NLP) in speech rehabilitation, with a particular focus on interaction modalities, engagement autonomy, and motivation. We have reviewed 45 selected studies. Our key findings show how intelligent tutoring systems, adaptive voice-based interfaces, and gamified speech interventions can empower children to engage in self-directed speech learning, reducing dependence on therapists and caregivers. The diversity of interaction modalities, including speech recognition, phoneme-based exercises, and multimodal feedback, demonstrates how AI and Assistive Technology (AT) can personalise learning experiences to accommodate diverse needs. Furthermore, the incorporation of gamification strategies, such as reward systems and adaptive difficulty levels, has been shown to enhance children’s motivation and long-term participation in speech rehabilitation. The gaps identified show that despite advancements, challenges remain in achieving universal accessibility, particularly regarding speech recognition accuracy, multilingual support, and accessibility for users with multiple disabilities. This review advocates for interdisciplinary collaboration across educational technology, special education, cognitive science, and human–computer interaction (HCI). Our work contributes to the ongoing discourse on lifelong inclusive education, reinforcing the potential of AI-driven serious games as transformative tools for bridging learning gaps and promoting speech rehabilitation beyond clinical environments. Full article

This study explores strategic deception and counter-deception in multi-agent reinforcement learning environments for a police officer–robber game. The research is motivated by real-world scenarios where agents must operate with partial observability and adversarial intent. We develop a suite of progressively complex grid-based environments featuring dynamic goals, fake targets, and navigational obstacles. Agents are trained using deep Q-networks (DQNs) with game-theoretic reward shaping to encourage deceptive behavior in the robber and intent inference in the police officer. The robber learns to reach the true goal while misleading the police officer, and the police officer adapts to infer the robber’s intent and allocate resources effectively. The environments include fixed and dynamic layouts with varying numbers of goals and obstacles, allowing us to evaluate scalability and generalization. Experimental results demonstrate that the agents converge to equilibrium-like behaviors across all settings. The inclusion of obstacles increases complexity but also strengthens learned policies when guided by reward shaping. We conclude that integrating game theory with deep reinforcement learning enables the emergence of robust, deceptive strategies and effective counter-strategies, even in dynamic, high-dimensional environments. This work advances the design of intelligent agents capable of strategic reasoning under uncertainty and adversarial conditions. Full article

Gamification has emerged as a powerful strategy in digital education, enhancing engagement, motivation, and learning outcomes. However, most research lacks theoretical grounding and often applies multiple and uncontextualized game elements, limiting its impact and replicability. To address these gaps, this study introduces a Systemic Gamification Theory (SGT)—a comprehensive, human-centered model for designing and evaluating inclusive and effective gamified educational environments. Sustained in Education, Human–Computer Interaction, and Psychology, SGT is structured around four core principles, emphasizing the importance of integrating game elements (1—Integration) into cohesive systems that generate emergent outcomes (2—Emergence) aligned synergistically (3—Synergy) with contextual needs (4—Context). The theory supports inclusivity by accounting for individual traits, situational dynamics, spatial settings, and cultural diversity. To operationalize SGT, we developed two tools: i. a set of 10 Heuristics to guide and analyze effective and inclusive gamification; and ii. a Framework for designing and evaluating gamified systems, as well as comparing research methods and outcomes across different contexts. These tools demonstrated how SGT enables robust, adaptive, and equitable gamified learning experiences. By advancing theoretical and practical development, SGT fosters a transformative approach to gamification, enriching multimedia learning through thoughtful system design and reflective evaluation practices. Full article

Classical epidemic models treat vaccine uptake as an exogenous parameter, yet real-world coverage emerges from strategic choices made by individuals facing uncertain risks. During the last two decades, vaccination games, which combine epidemic dynamics with game theory, behavioural economics, and network science, have become a very important tool for analysing this problem. Here, we synthesise more than 80 theoretical, computational, and empirical studies to clarify how population structure, psychological perception, pathogen complexity, and policy incentives interact to determine vaccination equilibria and epidemic outcomes. Papers are organised along five methodological axes: (i) population topology (well-mixed, static and evolving networks, multilayer systems); (ii) decision heuristics (risk assessment, imitation, prospect theory, memory); (iii) additional processes (information diffusion, non-pharmacological interventions, treatment, quarantine); (iv) policy levers (subsidies, penalties, mandates, communication); and (v) pathogen complexity (multi-strain, zoonotic reservoirs). Common findings across these studies are that voluntary vaccination is almost always sub-optimal; feedback between incidence and behaviour can generate oscillatory outbreaks; local network correlations amplify free-riding but enable cost-effective targeted mandates; psychological distortions such as probability weighting and omission bias materially shift equilibria; and mixed interventions (e.g., quarantine + vaccination) create dual dilemmas that may offset one another. Moreover, empirical work surveys, laboratory games, and field data confirm peer influence and prosocial motives, yet comprehensive model validation remains rare. Bridging the gap between stylised theory and operational policy will require data-driven calibration, scalable multilayer solvers, and explicit modelling of economic and psychological heterogeneity. This review offers a structured roadmap for future research on adaptive vaccination strategies in an increasingly connected and information-rich world. Full article