Search Results (213)

Gamified recommender systems, which mix game design with recommendation frameworks, are a new way to increase user involvement and satisfaction. Even though they have a lot of potential, there has not been any systematic research on how their design affects how people use them. This study introduces a fuzzy DEMATEL-based framework for the assessment and enhancement of gamified recommender systems. Four theoretically grounded gamified recommender system prototypes were developed as a novel contribution, as no readily available systems exist for these designs. The assessment utilized nine user-centric criteria—Effectiveness, Transparency, Persuasiveness, Satisfaction, Trust, Usefulness, Ease of Use, Efficiency, and Education—systematically derived from a PRISMA-guided literature review. This study integrates gamification theory, systematic review, and fuzzy decision-making to formulate a comprehensive framework for identifying the key factors influencing adoption. The fuzzy DEMATEL was applied to evaluate feedback from 25 end-users, and it was found that usefulness and ease of use were the most essential factors for satisfaction and system effectiveness. Analysis of design showed that competition in Points, Badges, and Leaderboards (PBL) design boosts short-term motivation, Acknowledgments, Objectives, and Progression (AOP) boosts progress and openness, Acknowledgments, Competition, and Time Pressure (ACT) boosts efficiency in competitive situations but might lower satisfaction, and Acknowledgments, Objectives, and Social Pressure (AOS) depends on social influence and accountability. Full article

The demands of modern society regarding academic training have placed the focus of education on active methodologies. Their proven success also presents challenges for the innovation they entail. In this regard, methodological strategies such as gamification are currently focusing their analyses on design to ensure the effectiveness of their outcomes. With this in mind, we aim to analyse a gamification experience in higher education from the perspective of the various stakeholders involved. Using a qualitative methodology, data from an open-ended survey and the learning journals of 73 students were triangulated with the teaching journals of four lecturers. The category-based data analysis indicates that escape room-type games and digital boards are the most highly valued as innovative educational tools that promote active learning. Conflict resolution, cooperative work, and understanding of theoretical knowledge stood out as achieved objectives. The overall positive view, the classroom atmosphere of excitement and fun, and the impact on learning due to increased motivation were highlighted in participants’ opinions. From the lecturers’ perspective, the outcome is shown to be worthwhile in terms of effort and benefit. Full article

Background: Prolonged sedentary behavior and associated obesity are recognized risk factors for poor health across the lifespan. Globally, data show that many children and adolescents aged 5 to 17 significantly increased their sedentary behaviors during the COVID-19 pandemic, failing to meet recommended physical activity levels and reporting increased smartphone use. While mobile devices and video games have been traditionally linked to physical inactivity, formats like exergaming, which combine gameplay with gross motor activity, offer potential to promote physical activity. However, many digital health tools for children are developed without incorporating feedback from key stakeholders and end-users (e.g., children, teachers, and guardians). Therefore, this paper, within the Walk around the Earth (E-Walk) project, describes a prospective study that aims (1) to identify the most influential factors or characteristics affecting engagement with and usability of a mobile application promoting physical activity among primary school students; (2) to develop a mobile application for children based on the identified factors and characteristics. Methods: This project will use a group concept mapping approach to identify the most influential features/factors/characteristics affecting engagement with and usability of an app. By involving primary stakeholders (e.g., children, teachers, guardians, and physical activity experts), the project seeks to align the app’s features with primary end-user needs and motivations. Following the app’s development, its effectiveness in increasing physical activity levels and reducing sedentary behaviors will be evaluated through a mixed-method design, incorporating anthropometric data, validated physical activity questionnaires (Physical Activity Questionnaire for Older Children (PAQ-C) and International Physical Activity Questionnaire (IPAQ)), and engagement metrics. Conclusions: The E-Walk project integrates participatory design with educational content and activity-based challenges, representing a multidimensional strategy for promoting health and learning in primary school students. Ultimately, this study contributes to the development of user-informed digital interventions that support sustainable behavioral changes, in line with broader goals of child well-being and digital health promotion. Full article

This mixed-methods study investigated how a personalized, narrative-integrated digital gamification framework (with FantasyClass) was associated with motivation and presence among preservice elementary teachers in a science education course. The intervention combined HEXAD-informed personalization (aligning game elements with player types) with a branching storyworld, teacher-directed AI-generated narrative emails, and multimodal cues (visuals, music, scent) to scaffold presence alongside autonomy, competence, and relatedness. Thirty-four students participated in a one-group posttest design, completing an adapted 21-item PENS questionnaire and responding to two open-ended prompts. Results, which are exploratory and not intended for broad generalization or causal inference, indicated high self-reported competence and autonomy, positive but more variable relatedness, and strong presence/immersion. Subscale correlations showed that Competence covaried with Autonomy and Relatedness, while Presence/Immersion was positively associated with all other subscales, suggesting that presence may act as a motivational conduit. Thematic analysis portrayed students as active decision-makers within the narrative, linking consequential choices, visible progress, and team-based goals to agency, effectiveness, and social connection. Additional themes included coherence and organization, fun and enjoyment, novelty, extrinsic incentives, and perceived professional transferability. Overall, findings suggest that narrative presence, when coupled with player-aligned game elements, can foster engagement and motivation in STEM-oriented teacher education. Full article

The automated analysis of pool game videos presents significant challenges due to complex object interactions, precise rule requirements, and event-driven game dynamics that traditional computer vision approaches struggle to address effectively. This research introduces TCGA-Pool, a novel video analytics framework specifically designed for comprehensive 9-ball pool game understanding through advanced object attention mechanisms and temporal context modeling. Our approach addresses the critical gap in automated cue sports analysis by focusing on three essential classification tasks: Clear shot detection (successful ball potting without fouls), win condition identification (game-ending scenarios), and potted balls counting (accurate enumeration of successfully pocketed balls). The proposed framework leverages a Temporal Context Gated Attention (TCGA) mechanism that dynamically focuses on salient game elements while incorporating sequential dependencies inherent in pool game sequences. Through comprehensive evaluation on a dataset comprising 58,078 annotated video frames from diverse 9-ball pool scenarios, our TCGA-Pool framework demonstrates substantial improvements over existing video analysis methods, achieving accuracy gains of 4.7%, 3.2%, and 6.2% for clear shot detection, win condition identification, and potted ball counting tasks, respectively. The framework maintains computational efficiency with only 27.3 M parameters and 13.9 G FLOPs, making it suitable for real-time applications. Our contributions include the introduction of domain-specific object attention mechanisms, the development of adaptive temporal modeling strategies for cue sports, and the implementation of a practical real-time system for automated pool game monitoring. This work establishes a foundation for intelligent sports analytics in precision-based games and demonstrates the effectiveness of specialized deep learning approaches for complex temporal video understanding tasks. Full article

Gamified virtual reality (VR) environments are increasingly used to enhance engagement and learning, yet most designs still adopt a one-size-fits-all approach that overlooks motivational diversity. The HEXAD framework, which classifies users into six player types, provides a promising lens for addressing this gap, but its predictive validity in immersive VR remains contested. This study investigates how HEXAD profiles shape navigation, time allocation, and engagement dynamics in an open-ended gamified VR environment. Thirty-two undergraduate participants, all regular gamers, completed the HEXAD scale before exploring a VR setting with five thematic islands without predefined tasks. System logs and screen recordings captured first island choices, sequential visit patterns, and time spent, and data were analyzed using qualitative pattern analysis alongside nonparametric statistics. The results showed significant associations between player type and initial choices, with Players favoring Game Island, Socialisers choosing Social Island, Philanthropists engaging most with Library, and Achievers and Free Spirits drawn to Experience. Kruskal–Wallis tests of exploration breadth revealed moderate effect sizes across types, though significance was limited by sample size. Three emergent strategies, Focused Explorers, Wanderers, and Strategic Switchers, captured motivational orientations beyond single metrics, while heat map visualizations highlighted clustering around Game and Experience Islands. By situating these findings within flow theory and inclusive–adaptive design principles, this study demonstrates how behavioral traces can link motivational typologies with embodied interaction. Overall, the results advance debates on HEXAD’s robustness and contribute practical pathways for developing adaptive, motivation-sensitive VR environments that support sustained engagement and inclusivity. Full article

Mastering client-side Web programming is essential for the development of responsive and interactive Web applications. To support novice students’ self-study, in this paper, we propose a novel exercise format called the phrase fill-in-blank problem (PFP) in the Web Programming Learning Assistant System (WPLAS). A PFP instance presents a source code with blanked phrases (a set of elements) and corresponding Web page screenshots. Then, it requests the user to fill in the blanks, and the answers are automatically evaluated through string matching with predefined correct answers. By increasing blanks, PFP can come close to writing a code from scratch. To facilitate scalable and context-aware question creation, we implemented the PFP instance generation algorithm in Python using regular expressions. This approach targets meaningful code segments in HTML, CSS, and JavaScript that reflect the interactive behavior of front-end development. For evaluations, we generated 10 PFP instances for basic Web programming topics and 5 instances for video games and assigned them to students at Okayama University, Japan, and the State Polytechnic of Malang, Indonesia. Their solution results show that most students could solve them correctly, indicating the effectiveness and accessibility of the generated instances. In addition, we investigated the ability of generative AI, specifically ChatGPT, to solve the PFP instances. The results show 86.7% accuracy for basic-topic PFP instances. Although it still cannot fully find answers, we must monitor progress carefully. In future work, we will enhance PFP in WPLAS to handle non-unique answers by improving answer validation for flexible recognition of equivalent responses. Full article

Wireless Sensor Networks are composed of a set of sensors distributed within an area that monitor physical variables of the environment and send back information to a central node. Nodes cannot always remain active since they would swiftly drain the system’s energy. As such, some works have proposed the use of different on/off schemes to monitor the phenomena of interest efficiently but also to conserve energy as much as possible. To this end, the use of on/off protocols has been used before, but has no relation to the characteristics of the monitored events. However, in scenarios where the phenomena to monitor occur in a certain pattern or specific region, the use of more suited techniques to activate the nodes can yield better results. In this sense, we propose the use of cellular automata (CA), based on the Game of Life (GoL), in order to turn the nodes on and off, according to the patterns described by the automata. Cellular automata are discrete models consisting of a lattice or grid of cells in a finite number of states that remain or change into another state following pre-established rules commonly associated with the states of their neighbors. As such, we propose to activate/deactivate the nodes following the natural behavior of the GoL scheme. Since the initial state of the cellular automata directly modifies the pattern evolution of the GoL, we consider several possible patterns that can occur in practical systems in order to prove the effectiveness of our proposal. We evaluate the system performance in terms of successful event report probability and energy consumption, comparing our results to the conventional on/off schemes with a certain probability of nodes being in the on state. With this premise, we think CA is a good alternative to determine the on/off process in WSNs. We compared the system performance of the GoL patterns compared to the classical approach and found the cases where the GoL scheme performs better. Full article

Serious games that integrate educational content with engaging gameplay mechanics hold promise for reducing cognitive load and increasing student motivation in STEM and health science education. This preliminary study presents the development and evaluation of the Medimon NASA Demo, a game-based learning prototype designed to teach undergraduate students about the musculoskeletal and visual systems—two critical domains in space medicine. Participants (n = 23) engaged with the game over a two-week self-regulated learning period. The game employed mnemonic-based characters, visual storytelling, and turn-based battle mechanics to reinforce medical concepts. Quantitative results demonstrated significant learning gains, with posttest scores increasing by an average of 23% and a normalized change of c = 0.4. Engagement levels were high across multiple dimensions of situational interest, and 74% of participants preferred the game over traditional formats. Qualitative analysis of open-ended responses revealed themes related to intrinsic appeal, perceived learning efficacy, interaction design, and cognitive resource management. While the game had minimal impact on short-term STEM career interest, its educational potential was clearly supported. These findings suggest that mnemonic-driven serious games like Medimon can effectively enhance engagement and learning in health science education, especially when aligned with real-world contexts such as space medicine. Full article

With the explosive growth of Internet of Things (IoT) devices, massive amounts of heterogeneous data are continuously generated. However, IoT data transactions and sharing face multiple challenges such as limited device resources, untrustworthy network environment, highly sensitive user privacy, and serious data silos. How to achieve fine-grained access control and privacy protection for massive devices while ensuring secure and reliable data circulation has become a key issue that needs to be urgently addressed in the current IoT field. To address the above challenges, this paper proposes a blockchain-based data transaction and privacy protection framework. First, the framework builds a multi-layer security architecture that integrates blockchain and IPFS and adapts to the “end–edge–cloud” collaborative characteristics of IoT. Secondly, a data sharing mechanism that takes into account both access control and interest balance is designed. On the one hand, the mechanism uses attribute-based encryption (ABE) technology to achieve dynamic and fine-grained access control for massive heterogeneous IoT devices; on the other hand, it introduces a game theory-driven dynamic pricing model to effectively balance the interests of both data supply and demand. Finally, in response to the needs of confidential analysis of IoT data, a secure computing scheme based on CKKS fully homomorphic encryption is proposed, which supports efficient statistical analysis of encrypted sensor data without leaking privacy. Security analysis and experimental results show that this scheme is secure under standard cryptographic assumptions and can effectively resist common attacks in the IoT environment. Prototype system testing verifies the functional completeness and performance feasibility of the scheme, providing a complete and effective technical solution to address the challenges of data integrity, verifiable transactions, and fine-grained access control, while mitigating the reliance on a trusted central authority in IoT data sharing. Full article

Background: This study aimed to compare the immediate effects of small-sided games (SSGs) and running-based high-intensity interval training (HIITrb) on serum brain-derived neurotrophic factor (BDNF) levels, cognitive performance, and enjoyment in young, male soccer players. Methods: Twenty-four soccer players [age: 19.2 ± 0.8 years] completed one session each of four-a-side SSG or HIITrb in a randomized, counterbalanced, and crossover design, with a one-week washout period. Blood samples and Trail Making Tests (TMTs) A and B were measured before and after exercise. Heart rate (HR) was monitored throughout the games, and ratings of perceived exertion (RPE) and enjoyment were collected at the end of the measurements. Results: The results show no significant effects of time (p > 0.775), group (p > 0.276) or time × group interaction (p > 0.199) on BDNF levels. For TMT-A, the time effect (p = 0.866) and group effect (p = 0.057) were not significant; however, the time × group interaction was significant (p < 0.019), indicating a superior performance in the SSG compared to HIITrb. In the TMT-B, significant effects were observed for both time (p < 0.001) and group (p < 0.001), while the time × group interaction effect was not statistically significant (p > 0.061). Furthermore, enjoyment levels did not differ significantly between conditions (p = 0.976). Conclusions: These findings suggest that four-a-side SSG may enhance processing speed compared to HIITrb without changes in serum BDNF levels. Coaches may consider using 4v4 SSG formats in early training sessions or warm-ups to stimulate processing speed and mental readiness in young soccer players. Full article

The growing integration of renewable energy sources (RESs) into modern power systems calls for enhanced flexibility and control mechanisms. Conventional demand response (DR) strategies, such as price-based and incentive-driven methods, often encounter challenges that limit their effectiveness. This paper proposes a novel DR approach grounded in Customer Directrix Load (CDL) and formulated through Stackelberg game theory. A bilevel optimization framework is established, with air conditioning (AC) systems and electric vehicles (EVs) serving as the main DR participants. The problem is addressed using a genetic algorithm. Simulation studies on a modified IEEE 33-bus distribution system reveal that the proposed strategy significantly improves RES accommodation, reduces power curtailment, and yields mutual benefits for both system operators and end users. The findings highlight the potential of the CDL-based DR mechanism in enhancing operational efficiency and encouraging proactive consumer involvement. Full article

Background: The aim of this review was to analyze training interventions used and their effectiveness in improving pelvic floor muscle function related to urinary continence in postmenopausal women. We then characterized the recommended pelvic floor muscle training programs used in experimental studies based on four training components: frequency, intensity, duration, and type of pelvic floor muscle exercise. Methods: For this purpose, we conducted a literature review of works published up until the end of 2024, available in the Web of Science, PubMed, MEDLINE, and SPORTDiscus with Full Text databases. We used the keywords “pelvic floor muscle”, “training”, and “postmenopausal women”. Initially, we identified 205 articles published between 1997 and 2024. Then, based on specific criteria, we qualified 15 for analysis. Results: Thirteen studies included only PFMT, while three of them combined PFMT with other physical activity. In two studies, training was conducted in the form of a virtual video game using a pressure platform. We have noted that researchers most often use a 1 h pad test, digital palpation, and surface electromyography to assess the function of pelvic floor muscles. In improving pelvic floor muscle function related to urinary incontinence, 14 out of the 15 analyzed studies showed improvement. In only eight of the fifteen articles, researchers characterized all components of the implemented PFMT that enable full replication of the training intervention. In four of the studies, only one of the required components, namely intensity, was missing. The recommended number of training sessions was 2 to 7 per week, on average 3 ± 2 (M ± SD). Training interventions lasted from 2 to 24 weeks, on average 10 ± 6 weeks. Conclusions: Regardless of the chosen form of training intervention, PFMT is an effective method in improving the function of pelvic floor muscles in postmenopausal women. Full article

As the demand for expansive back-end systems in online applications continues to grow, novel frameworks are necessitated to address the escalating operational demands, energy consumption, and associated costs. Traditional Client–Server models, while offering centralized security and reliability, are characterized by their high deployment and maintenance expenses. Conversely, Peer-to-Peer (P2P) models, despite being cost-effective and scalable, are hindered by inherent security and data integrity challenges. Moreover, the lack of a central authority in P2P systems complicates a definitive resolution of scenarios involving stakes, where users cannot withdraw without incurring a tangible loss. In this research work, a hybrid back-end framework is introduced, combining the advantages of both models through the utilization of cryptographic algorithms and Secure Multi-Party Computation (MPC) protocols. The baseline solution is lightweight and fully composable, making it capable of utilizing different more complex slot-in MPC techniques. The proposed framework’s effectiveness is demonstrated through a simplified two-player Spades game, although it is fully generalizable to any application. Evaluations across multiple case studies reveal substantial performance enhancements compared to conventional approaches, particularly post-initialization, highlighting the scheme’s potential as a cost-effective, energy-efficient, and secure solution for modern online applications. Full article

Background: The ageing process is associated with a decline in cognitive functions, including eye–hand coordination, attention concentration, and psychomotor reaction time. This study aimed to assess the effectiveness of virtual reality–based therapy in enhancing cognitive functions in seniors. Methods: This study was conducted on 38 cases (29 women and 9 men) with a mean age of 87.2 years, who were divided into two groups: a VR group (with a 4-week, three-time-week training program using the game “Beat Saber”) and a control group (with a standard 4-week exercise program). Assessments of eye–hand coordination and attentional concentration were conducted at the beginning (T₀) and the end (T₁) of the training. Results: Analysis of eye–hand coordination and attentional concentration showed significant improvement in both groups (T₀ vs. T₁: p = 0.0002 for the intervention group and p = 0.007 for the control group). However, the effect in the VR group was almost three times greater than in the control group (1.689 vs. 0.615 in D effect). Moreover, in the VR group, an analysis of “good cuts” indicated improvements in both parameters after 4 weeks of VR training. The percentage of correctly received stimuli increased significantly across sessions (p < 0.00001). Furthermore, 84.3% of participants experienced a twofold improvement in performance over the 12 VR sessions (42% vs. 80% accuracy in successful hits). The distribution of results also suggests a positive subjective impact of VR therapy in maintaining mental activity. Conclusions: The findings indicate that VR-related training can support elderly individuals in recovering cognitive function, potentially enhancing their independence and life quality. Full article