Entertainment Computing最新文献

Beyond pre-scripted interactions: mapping the integration of LLMs in digital game-based learning – a scoping review 超越预先编写的互动：绘制法学硕士在基于数字游戏的学习中的整合-范围审查

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2026-01-01 DOI: 10.1016/j.entcom.2026.101082

Yu-lin Gong , Min-kai Wang , Yun-Fang Tu , Chang-qin Huang , Di Zhang

Digital Game-Based Learning (DGBL) has demonstrated effectiveness in fostering engagement and academic achievement but faces challenges in adaptability, real-time feedback, and personalized scaffolding. Large Language Models (LLMs) offer promising solutions by enabling interactive learning experiences, dynamic assessments, and adaptive instructional support. This scoping review systematically examines the integration of LLMs in DGBL, assessing their impact on student engagement, learning outcomes, and pedagogical effectiveness. Following PRISMA-ScR guidelines, seven peer-reviewed studies published between 2024 and 2025 were identified from Web of Science, Scopus, ERIC, and PubMed. Thematic analysis revealed that LLM-enhanced DGBL primarily supports three functional roles: (1) conversational AI for interactive scaffolding, facilitating real-time student-NPC interactions; (2) adaptive learning support, personalizing feedback and guiding problem-solving strategies; and (3) automated assessment, evaluating student performance and providing instructional interventions. Findings indicate that LLM-driven DGBL enhances student motivation, cognitive engagement, and academic performance while reducing cognitive load. However, key challenges persist, including AI over-reliance, transparency concerns, and the need for ethical safeguards. Future research should explore longitudinal effects, interdisciplinary applications, and AI literacy strategies to ensure responsible and effective integration of LLMs in game-based learning.

数字游戏学习（Digital Game-Based Learning， DGBL）在促进参与和学术成就方面已经证明了有效性，但在适应性、实时反馈和个性化框架方面面临挑战。大型语言模型（llm）通过实现交互式学习体验、动态评估和适应性教学支持，提供了有前途的解决方案。这一范围审查系统地检查了法学硕士在DGBL中的整合，评估了他们对学生参与、学习成果和教学效率的影响。遵循PRISMA-ScR指南，从Web of Science、Scopus、ERIC和PubMed中确定了2024年至2025年间发表的7项同行评议研究。专题分析显示，llm增强的DGBL主要支持三个功能角色：(1)用于交互式脚手架的会话AI，促进实时学生与npc的交互；(2)自适应学习支持、个性化反馈和指导性问题解决策略；(3)自动评估，评估学生表现并提供教学干预。研究结果表明，llm驱动的DGBL提高了学生的学习动机、认知投入和学习成绩，同时减少了认知负荷。然而，关键挑战依然存在，包括对人工智能的过度依赖、对透明度的担忧以及对道德保障的需求。未来的研究应该探索纵向效应、跨学科应用和人工智能素养策略，以确保法学硕士在基于游戏的学习中负责任和有效地整合。

{"title":"Beyond pre-scripted interactions: mapping the integration of LLMs in digital game-based learning – a scoping review","authors":"Yu-lin Gong , Min-kai Wang , Yun-Fang Tu , Chang-qin Huang , Di Zhang","doi":"10.1016/j.entcom.2026.101082","DOIUrl":"10.1016/j.entcom.2026.101082","url":null,"abstract":"<div><div>Digital Game-Based Learning (DGBL) has demonstrated effectiveness in fostering engagement and academic achievement but faces challenges in adaptability, real-time feedback, and personalized scaffolding. Large Language Models (LLMs) offer promising solutions by enabling interactive learning experiences, dynamic assessments, and adaptive instructional support. This scoping review systematically examines the integration of LLMs in DGBL, assessing their impact on student engagement, learning outcomes, and pedagogical effectiveness. Following PRISMA-ScR guidelines, seven peer-reviewed studies published between 2024 and 2025 were identified from Web of Science, Scopus, ERIC, and PubMed. Thematic analysis revealed that LLM-enhanced DGBL primarily supports three functional roles: (1) conversational AI for interactive scaffolding, facilitating real-time student-NPC interactions; (2) adaptive learning support, personalizing feedback and guiding problem-solving strategies; and (3) automated assessment, evaluating student performance and providing instructional interventions. Findings indicate that LLM-driven DGBL enhances student motivation, cognitive engagement, and academic performance while reducing cognitive load. However, key challenges persist, including AI over-reliance, transparency concerns, and the need for ethical safeguards. Future research should explore longitudinal effects, interdisciplinary applications, and AI literacy strategies to ensure responsible and effective integration of LLMs in game-based learning.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"56 ","pages":"Article 101082"},"PeriodicalIF":2.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deceptive algorithms in games: A systematic literature review 游戏中的欺骗性算法：系统性文献综述

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2026-01-01 DOI: 10.1016/j.entcom.2025.101078

Jason Starace, Jennie Tafoya, Anmol Singh, Terence Soule

This systematic literature review examines the evolving landscape of deception in video games and artificial intelligence (AI). The integration of deceptive strategies in AI, particularly within gaming environments, represents a growing area of interest with significant implications for both gameplay and broader applications, such as cybersecurity. Through a systematic review of 97 papers, 79 were excluded after introduction analysis revealed focus on deception outside gaming contexts (e.g., advertising, propaganda, movement detection), leaving 18 papers directly applicable to game-based deception. Of these 18, 61% provided formal or contextual definitions while 39% relied on assumed understanding. The review categorizes the current body of research into three primary areas: definitions of deception, methods for implementing and mitigating deception, and the frameworks used to analyze these strategies. The review highlights the diversity in the conceptualization of deception, ranging from formal definitions grounded in game theory, to more context-specific operational definitions. Key models such as signaling games (information asymmetry scenarios), Stackelberg games (leader–follower dynamics), and hypergames (perception-based interactions) are explored alongside AI-driven approaches like reinforcement learning (trial-and-error learning) and generative neural networks, which simulate and detect deception in complex environments. The review identifies significant gaps in the standardization of definitions and the practical implementation of deceptive strategies, calling for further interdisciplinary research to address these challenges. The ethical implications of deploying deceptive AI systems are discussed, emphasizing the need for comprehensive frameworks that balance innovation with responsible usage. Future research must prioritize the standardized definitions and interdisciplinary collaboration across ethics, law, and social sciences to address the expanding applications and ethical implications of deceptive AI technologies.

这篇系统的文献综述研究了电子游戏和人工智能（AI）中欺骗的演变图景。人工智能中欺骗策略的整合，特别是在游戏环境中，代表了一个日益增长的兴趣领域，对游戏玩法和更广泛的应用（如网络安全）都有重大影响。通过对97篇论文的系统回顾，79篇论文在引入分析后被排除在外，揭示了对游戏环境之外的欺骗（例如，广告、宣传、运动检测）的关注，剩下18篇论文直接适用于基于游戏的欺骗。在这18个中，61%提供了正式或上下文定义，而39%依赖于假定的理解。该综述将目前的研究分为三个主要领域：欺骗的定义，实施和减轻欺骗的方法，以及用于分析这些策略的框架。这篇综述强调了欺骗概念化的多样性，从基于博弈论的正式定义到更具体的具体操作定义。关键模型，如信号游戏（信息不对称场景），Stackelberg游戏（领导者-追随者动态）和超级游戏（基于感知的互动）与人工智能驱动的方法一起探索，如强化学习（试错学习）和生成神经网络，模拟和检测复杂环境中的欺骗。该审查确定了在定义标准化和欺骗策略的实际实施方面的重大差距，呼吁进一步开展跨学科研究以应对这些挑战。讨论了部署欺骗性人工智能系统的伦理影响，强调需要建立全面的框架来平衡创新与负责任的使用。未来的研究必须优先考虑伦理、法律和社会科学的标准化定义和跨学科合作，以解决欺骗性人工智能技术的扩大应用和伦理影响。

{"title":"Deceptive algorithms in games: A systematic literature review","authors":"Jason Starace, Jennie Tafoya, Anmol Singh, Terence Soule","doi":"10.1016/j.entcom.2025.101078","DOIUrl":"10.1016/j.entcom.2025.101078","url":null,"abstract":"<div><div>This systematic literature review examines the evolving landscape of deception in video games and artificial intelligence (AI). The integration of deceptive strategies in AI, particularly within gaming environments, represents a growing area of interest with significant implications for both gameplay and broader applications, such as cybersecurity. Through a systematic review of 97 papers, 79 were excluded after introduction analysis revealed focus on deception outside gaming contexts (e.g., advertising, propaganda, movement detection), leaving 18 papers directly applicable to game-based deception. Of these 18, 61% provided formal or contextual definitions while 39% relied on assumed understanding. The review categorizes the current body of research into three primary areas: definitions of deception, methods for implementing and mitigating deception, and the frameworks used to analyze these strategies. The review highlights the diversity in the conceptualization of deception, ranging from formal definitions grounded in game theory, to more context-specific operational definitions. Key models such as signaling games (information asymmetry scenarios), Stackelberg games (leader–follower dynamics), and hypergames (perception-based interactions) are explored alongside AI-driven approaches like reinforcement learning (trial-and-error learning) and generative neural networks, which simulate and detect deception in complex environments. The review identifies significant gaps in the standardization of definitions and the practical implementation of deceptive strategies, calling for further interdisciplinary research to address these challenges. The ethical implications of deploying deceptive AI systems are discussed, emphasizing the need for comprehensive frameworks that balance innovation with responsible usage. Future research must prioritize the standardized definitions and interdisciplinary collaboration across ethics, law, and social sciences to address the expanding applications and ethical implications of deceptive AI technologies.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"56 ","pages":"Article 101078"},"PeriodicalIF":2.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving group navigation for VR-based entertainment applications 改进基于vr的娱乐应用的群组导航

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2026-01-01 DOI: 10.1016/j.entcom.2026.101086

Jalal Safari Bazargani, Jong-min Jeon, Abolghasem Sadeghi-Niaraki, Soo-Mi Choi

Various aspects of shared virtual environments have been explored to improve communication, collaboration, and entertainment among users. However, one crucial element, group navigation, remains in its early stages of development. The research gap suggests investigating different approaches to achieve suitable group navigation approaches within virtual reality environments. The employment of customized avatars that provide gestures and voice chat communication, along with controlled transitions between individual and group navigations, has not yet been fully studied. In this regard, this paper proposes a new approach for examining the aforementioned unexplored features of group navigation along with other modifications to current techniques. Moreover, features such as animated paths, transparent materials, switching between first-person view and third-person distant view, and preview avatars were incorporated into this approach. As the locomotion technique of the proposed solution varies noticeably with existing ones, the solution was evaluated in a user study comparing with teleportation and steering methods in terms of human behavior and psychology from usability, immersion, efficiency, safety, attention-guiding mechanism, and entertainment perspectives. The findings revealed that our approach outperformed teleportation and steering, providing promising insights into developing more interactive, entertaining, and socially immersive group navigation techniques in VR.

已经探索了共享虚拟环境的各个方面，以改善用户之间的通信、协作和娱乐。然而，一个关键的元素，组导航，仍处于发展的早期阶段。研究差距建议研究不同的方法，以实现在虚拟现实环境中合适的群体导航方法。使用提供手势和语音聊天交流的定制头像，以及个人和群体导航之间的受控转换，尚未得到充分研究。在这方面，本文提出了一种新的方法来检查前面提到的未开发的组导航功能以及对当前技术的其他修改。此外，动画路径、透明材料、第一人称视角和第三人称视角之间的切换以及预览头像等功能也被纳入该方法。由于该解决方案的移动技术与现有解决方案存在明显差异，因此从可用性、沉浸感、效率、安全性、注意力引导机制和娱乐角度对该解决方案进行了用户研究，并与隐形传态和转向方法从人类行为和心理方面进行了比较。研究结果表明，我们的方法优于瞬间移动和转向，为在VR中开发更具互动性、娱乐性和社交沉浸式的群体导航技术提供了有希望的见解。

{"title":"Improving group navigation for VR-based entertainment applications","authors":"Jalal Safari Bazargani, Jong-min Jeon, Abolghasem Sadeghi-Niaraki, Soo-Mi Choi","doi":"10.1016/j.entcom.2026.101086","DOIUrl":"10.1016/j.entcom.2026.101086","url":null,"abstract":"<div><div>Various aspects of shared virtual environments have been explored to improve communication, collaboration, and entertainment among users. However, one crucial element, group navigation, remains in its early stages of development. The research gap suggests investigating different approaches to achieve suitable group navigation approaches within virtual reality environments. The employment of customized avatars that provide gestures and voice chat communication, along with controlled transitions between individual and group navigations, has not yet been fully studied. In this regard, this paper proposes a new approach for examining the aforementioned unexplored features of group navigation along with other modifications to current techniques. Moreover, features such as animated paths, transparent materials, switching between first-person view and third-person distant view, and preview avatars were incorporated into this approach. As the locomotion technique of the proposed solution varies noticeably with existing ones, the solution was evaluated in a user study comparing with teleportation and steering methods in terms of human behavior and psychology from usability, immersion, efficiency, safety, attention-guiding mechanism, and entertainment perspectives. The findings revealed that our approach outperformed teleportation and steering, providing promising insights into developing more interactive, entertaining, and socially immersive group navigation techniques in VR.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"56 ","pages":"Article 101086"},"PeriodicalIF":2.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A systematic review for 2019–2025 on deep learning models in the film production industry 2019-2025年电影制作行业深度学习模型系统回顾

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2026-01-01 DOI: 10.1016/j.entcom.2025.101076

Behnam Yousefimehr , Mehdi Ghatee , Shervin Ghaffari , Arash Arasteh , Parsa Ahmadi , Amirhossein Ghane , Sina Esnaasharieh

The integration of artificial intelligence (AI) into film production is fundamentally reshaping cinematic creation. This survey presents a systematic review of deep learning applications in the film industry from 2019 to 2025, analyzing their impact across four core pillars: Scriptwriting, Video Generation, Video Editing, and Music Generation. To overcome the limitations of subjective qualitative reviews, we introduce the Intelligent Multi-Dimensional Paper Scoring Framework (IMPSF), a novel methodology for the quantitative and reproducible evaluation of scholarly literature. The IMPSF employs a multi-agent system to assess papers across four key dimensions: Technical Innovation, Empirical Rigor, Cinematic Applicability, and Methodological Soundness. A critical innovation is our empirically grounded weighting scheme for these dimensions, optimized on a targeted subset of the S2ORC corpus to reflect performance in cinematic AI workflows. Applied to a curated corpus of 129 publications, the IMPSF identifies and ranks the most significant contributions. Our analysis reveals that AI serves primarily as a powerful augmentative tool, with substantial advancements in each domain driven by technologies like diffusion models, large language models (LLMs), and generative adversarial networks (GANs). This review not only synthesizes the current state of the art but also provides a structured taxonomy, a research roadmap, and a foundational framework for future innovation at the intersection of computational creativity and cinematic artistry.

人工智能（AI）与电影制作的融合正在从根本上重塑电影创作。本调查系统回顾了2019年至2025年深度学习在电影行业的应用，分析了它们在四个核心支柱上的影响：编剧、视频生成、视频编辑和音乐生成。为了克服主观定性评价的局限性，我们引入了智能多维论文评分框架（IMPSF），这是一种对学术文献进行定量和可重复评估的新方法。IMPSF采用多主体系统从四个关键维度评估论文：技术创新、经验严谨性、电影适用性和方法合理性。一个关键的创新是我们基于经验的这些维度的加权方案，在S2ORC语料库的目标子集上进行优化，以反映电影AI工作流程中的性能。应用于129个出版物的策划语料库，IMPSF确定并排名最重要的贡献。我们的分析表明，人工智能主要作为一种强大的辅助工具，在扩散模型、大型语言模型（LLMs）和生成对抗网络（gan）等技术的推动下，人工智能在每个领域都取得了实质性进展。这篇综述不仅综合了当前的艺术状态，而且还提供了一个结构化的分类，一个研究路线图，以及一个基础框架，用于未来在计算创造力和电影艺术的交叉点上的创新。

{"title":"A systematic review for 2019–2025 on deep learning models in the film production industry","authors":"Behnam Yousefimehr , Mehdi Ghatee , Shervin Ghaffari , Arash Arasteh , Parsa Ahmadi , Amirhossein Ghane , Sina Esnaasharieh","doi":"10.1016/j.entcom.2025.101076","DOIUrl":"10.1016/j.entcom.2025.101076","url":null,"abstract":"<div><div>The integration of artificial intelligence (AI) into film production is fundamentally reshaping cinematic creation. This survey presents a systematic review of deep learning applications in the film industry from 2019 to 2025, analyzing their impact across four core pillars: Scriptwriting, Video Generation, Video Editing, and Music Generation. To overcome the limitations of subjective qualitative reviews, we introduce the <em>Intelligent Multi-Dimensional Paper Scoring Framework (IMPSF)</em>, a novel methodology for the quantitative and reproducible evaluation of scholarly literature. The IMPSF employs a multi-agent system to assess papers across four key dimensions: Technical Innovation, Empirical Rigor, Cinematic Applicability, and Methodological Soundness. A critical innovation is our empirically grounded weighting scheme for these dimensions, optimized on a targeted subset of the S2ORC corpus to reflect performance in cinematic AI workflows. Applied to a curated corpus of 129 publications, the IMPSF identifies and ranks the most significant contributions. Our analysis reveals that AI serves primarily as a powerful augmentative tool, with substantial advancements in each domain driven by technologies like diffusion models, large language models (LLMs), and generative adversarial networks (GANs). This review not only synthesizes the current state of the art but also provides a structured taxonomy, a research roadmap, and a foundational framework for future innovation at the intersection of computational creativity and cinematic artistry.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"56 ","pages":"Article 101076"},"PeriodicalIF":2.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Social signals and visibility on digital platforms: interpretable evidence from steam on what drives player activity 数字平台上的社交信号和可见性：steam关于驱动玩家活动的可解释证据

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2026-01-01 DOI: 10.1016/j.entcom.2026.101080

Haoran Sun, Mingxi Bie, Zhaoyu Li, Zhaotong Lian

We study how public social signals and platform visibility cues—review volume and sentiment, pricing/discounts, and release recency—are associated with concurrent player activity on a large digital game distribution platform (Steam). Using a fully reproducible pipeline, we quantify standardized associations via logistic-regression odds ratios with confidence intervals and complement them with model-agnostic permutation importance and partial dependence profiles. Evaluation uses 5 × 10 repeated stratified cross-validation with out-of-fold predictions, reporting PR-AUC and calibration alongside ROC-AUC to reflect class imbalance and probability reliability. We also derive precision–recall operating thresholds that clarify targeting trade-offs. Across both endpoints, review volume is the strongest correlate; the early post-release window exhibits the largest marginal lift; and pricing shows a non-linear pattern with diminishing returns. Taken together, these results link social proof and visibility-related signals to measurable engagement patterns and yield actionable, testable hypotheses for discovery and promotion timing that can be validated through platform or publisher experimentation. All data/code, the AppID list, and the exact environment file are provided in the supplementary package to enable full reproduction.

我们研究了公共社交信号和平台可见性线索——评论量和情绪、定价/折扣和发布时间——与大型数字游戏发行平台（Steam）上的并发玩家活动之间的关系。使用完全可重复的管道，我们通过具有置信区间的逻辑回归比值比量化标准化关联，并通过与模型无关的排列重要性和部分依赖概况进行补充。评估使用5 × 10次重复分层交叉验证和叠外预测，报告PR-AUC和校准以及ROC-AUC，以反映类别不平衡和概率可靠性。我们还推导了精确召回操作阈值，以澄清目标权衡。在两个端点上，评论量是最强的相关性；释放后早期窗口的边际升力最大；定价呈现出收益递减的非线性模式。综上所述，这些结果将社交证明和可见性相关信号与可测量的用户粘性模式联系起来，并产生可操作的、可测试的发现和推广时机假设，这些假设可以通过平台或发行商实验来验证。所有数据/代码、AppID列表和确切的环境文件都在补充包中提供，以支持完全复制。

{"title":"Social signals and visibility on digital platforms: interpretable evidence from steam on what drives player activity","authors":"Haoran Sun, Mingxi Bie, Zhaoyu Li, Zhaotong Lian","doi":"10.1016/j.entcom.2026.101080","DOIUrl":"10.1016/j.entcom.2026.101080","url":null,"abstract":"<div><div>We study how public social signals and platform visibility cues—review volume and sentiment, pricing/discounts, and release recency—are associated with concurrent player activity on a large digital game distribution platform (Steam). Using a fully reproducible pipeline, we quantify standardized associations via logistic-regression odds ratios with confidence intervals and complement them with model-agnostic permutation importance and partial dependence profiles. Evaluation uses 5 × 10 repeated stratified cross-validation with out-of-fold predictions, reporting PR-AUC and calibration alongside ROC-AUC to reflect class imbalance and probability reliability. We also derive precision–recall operating thresholds that clarify targeting trade-offs. Across both endpoints, review volume is the strongest correlate; the early post-release window exhibits the largest marginal lift; and pricing shows a non-linear pattern with diminishing returns. Taken together, these results link social proof and visibility-related signals to measurable engagement patterns and yield actionable, testable hypotheses for discovery and promotion timing that can be validated through platform or publisher experimentation. All data/code, the AppID list, and the exact environment file are provided in the <span><span>supplementary</span></span> package to enable full reproduction.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"56 ","pages":"Article 101080"},"PeriodicalIF":2.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The mouse’s effect on performance in “balanced” competitive first-person shooters: case evidence from Halo: The Master Chief Collection 鼠标对“平衡”竞争性第一人称射击游戏表现的影响：来自《光晕：士官长合集》的案例证据

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2026-01-01 DOI: 10.1016/j.entcom.2026.101083

Daniel C. Sivertsen

Studies show that mouse and keyboard (MnK) input controls are superior for aiming tasks in first-person shooter (FPS) games compared to gamepad controls. What remains unclear is whether MnK users demonstrate a performance premium in competitive multiplayer games that use performance balancing mechanics like aim-assistance. This case study approaches this gap with player-level gameplay data from Halo: The Master Chief Collection, a multi-input FPS with aim-assistance mechanics for gamepad users. To account for observed differences between input device groups, propensity scores are estimated to match players across a vector of gameplay characteristics. Performance is assessed with three standard FPS metrics: the kills-to-deaths ratio (K/D), the kills-plus-assists-to-deaths ratio (KDA), and the count of total first-place rankings. The 95% confidence intervals for the MnK users’ expected premium in performance ranges from 0.06 to 0.16 (p-value < 0.01) for K/D, 0.06 to 0.21 (<0.01) for KDA, and 10.99 to 59.73 (<0.05) for first-place rankings. These results provide case evidence that MnK users experience performance advantages despite mechanics like aim-assistance and emphasize the need to refine balance in multi-input or cross-platform FPS game design.

研究表明，在第一人称射击游戏（FPS）中，鼠标和键盘（MnK）输入控制比手柄控制更适合瞄准任务。目前尚不清楚的是，MnK用户是否会在使用瞄准辅助等性能平衡机制的竞争性多人游戏中表现出性能溢价。本案例研究通过《光晕：士官长合集》（面向手柄用户的多输入FPS，带有瞄准辅助机制）的玩家层面游戏玩法数据来解决这一差距。为了解释不同输入设备组之间的差异，倾向得分被估计为在游戏玩法特征向量上匹配玩家。性能评估有三个标准的FPS指标：击杀/死亡比（K/D），击杀+助攻/死亡比（KDA），以及总第一名排名。MnK用户在性能上的预期溢价的95%置信区间为K/D的0.06至0.16 (p值<；0.01)， KDA的0.06至0.21 (<0.01)，第一名排名的10.99至59.73 （<0.05）。这些结果提供了《MnK》用户在瞄准辅助等机制下仍能获得性能优势的案例证据，并强调了在多输入或跨平台FPS游戏设计中优化平衡的必要性。

{"title":"The mouse’s effect on performance in “balanced” competitive first-person shooters: case evidence from Halo: The Master Chief Collection","authors":"Daniel C. Sivertsen","doi":"10.1016/j.entcom.2026.101083","DOIUrl":"10.1016/j.entcom.2026.101083","url":null,"abstract":"<div><div>Studies show that mouse and keyboard (MnK) input controls are superior for aiming tasks in first-person shooter (FPS) games compared to gamepad controls. What remains unclear is whether MnK users demonstrate a performance premium in competitive multiplayer games that use performance balancing mechanics like aim-assistance. This case study approaches this gap with player-level gameplay data from <em>Halo: The Master Chief Collection</em>, a multi-input FPS with aim-assistance mechanics for gamepad users. To account for observed differences between input device groups, propensity scores are estimated to match players across a vector of gameplay characteristics. Performance is assessed with three standard FPS metrics: the kills-to-deaths ratio (K/D), the kills-plus-assists-to-deaths ratio (KDA), and the count of total first-place rankings. The 95% confidence intervals for the MnK users’ expected premium in performance ranges from 0.06 to 0.16 (<em>p</em>-value < 0.01) for K/D, 0.06 to 0.21 (<0.01) for KDA, and 10.99 to 59.73 (<0.05) for first-place rankings. These results provide case evidence that MnK users experience performance advantages despite mechanics like aim-assistance and emphasize the need to refine balance in multi-input or cross-platform FPS game design.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"56 ","pages":"Article 101083"},"PeriodicalIF":2.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145975915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring the differentiated formation mechanism across diverse populations for the use of e-health 探索不同人群使用电子医疗的差异化形成机制

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2026-01-01 DOI: 10.1016/j.entcom.2026.101079

Jiayao Zhu, Sufen Wang

Objective

This study aims to provide a differentiated formation mechanism of e-health usage across diverse populations.

Method

Based on the formation and influence mechanism of the digital divide, the UTAUT (Unified Theory of Acceptance and Use of Technology) model is expanded from exogenous, endogenous, moderating and mediating mechanism. It introduces five moderating variables, namely gender, age, experience, education level, and health status. A total of 477 online questionnaires are collected.

Results

The model explains 86.2 % of the variance in behavioral intention, with performance expectancy, social influence, habit, and digital divide identified as key predictors. Habit, digital divide, and behavioral intention account for 80.6 % of the variance in usage behavior. Furthermore, health interest and perceived security are key external factors influencing the formation of the digital divide within internet healthcare. Moderating effects of age, gender, experience, health status, and education level are also evident in both the formation of the digital divide and the system usage behaviors.

Conclusions

This research has developed a comprehensive model of Internet medical system use with strong predictability, and provides theoretical guidance for improving patients’ acceptance and use of the Internet medical system (especially according to the characteristics of different populations).

目的探讨不同人群电子医疗使用的差异形成机制。方法基于数字鸿沟的形成和影响机制，从外生机制、内生机制、调节机制和中介机制等方面对UTAUT （Unified Theory of Acceptance and Use of Technology）模型进行扩展。它引入了五个调节变量，即性别、年龄、经验、教育水平和健康状况。共收集了477份在线问卷。结果该模型解释了86.2%的行为意向差异，其中表现预期、社会影响、习惯和数字鸿沟被确定为关键预测因素。习惯、数字鸿沟和行为意向占使用行为差异的80.6%。此外，健康利益和感知安全是影响互联网医疗中数字鸿沟形成的关键外部因素。年龄、性别、经验、健康状况和受教育程度对数字鸿沟的形成和系统使用行为的调节作用也很明显。本研究建立了互联网医疗系统使用的综合模型，具有较强的可预见性，为提高患者对互联网医疗系统的接受和使用（特别是根据不同人群的特点）提供了理论指导。

{"title":"Exploring the differentiated formation mechanism across diverse populations for the use of e-health","authors":"Jiayao Zhu, Sufen Wang","doi":"10.1016/j.entcom.2026.101079","DOIUrl":"10.1016/j.entcom.2026.101079","url":null,"abstract":"<div><h3>Objective</h3><div>This study aims to provide a differentiated formation mechanism of e-health usage across diverse populations.</div></div><div><h3>Method</h3><div>Based on the formation and influence mechanism of the digital divide, the UTAUT (Unified Theory of Acceptance and Use of Technology) model is expanded from exogenous, endogenous, moderating and mediating mechanism. It introduces five moderating variables, namely gender, age, experience, education level, and health status. A total of 477 online questionnaires are collected.</div></div><div><h3>Results</h3><div>The model explains 86.2 % of the variance in behavioral intention, with performance expectancy, social influence, habit, and digital divide identified as key predictors. Habit, digital divide, and behavioral intention account for 80.6 % of the variance in usage behavior. Furthermore, health interest and perceived security are key external factors influencing the formation of the digital divide within internet healthcare. Moderating effects of age, gender, experience, health status, and education level are also evident in both the formation of the digital divide and the system usage behaviors.</div></div><div><h3>Conclusions</h3><div>This research has developed a comprehensive model of Internet medical system use with strong predictability, and provides theoretical guidance for improving patients’ acceptance and use of the Internet medical system (especially according to the characteristics of different populations).</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"56 ","pages":"Article 101079"},"PeriodicalIF":2.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A computational approach to screenplay structure via multi-agent systems 基于多智能体系统的剧本结构计算方法

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2026-01-01 DOI: 10.1016/j.entcom.2025.101077

Mei-Hua Hsu , Yi-Fan Wang , Max Yue-Feng Wang , Wei-Zhi Su

Evaluating screenplay structure is challenging because manual reviews are subjective and costly, while automated methods often focus on surface features rather than the deeper architecture of storytelling. This study introduces a multi-agent analytical framework grounded explicitly in screenplay structure theory, operationalizing Syd Field’s three-act structure and Blake Snyder’s fifteen-beat model. By converting structural principles into computable rules and assigning specialized analytical roles to agents, the framework identifies acts, detects beats, assesses structural coherence, and resolves interpretive conflicts.

Tested on multiple screenplays, the framework outperformed a single-LLM baseline, achieving higher beat detection accuracy (87.2 % vs. 72.4 %), stronger semantic alignment, and greater interpretability. Agent disagreements highlighted structurally ambiguous segments, such as Midpoints and thematic beats, providing valuable diagnostic insights.

Theoretically, the study advances computational narratology by transforming narrative theory into explainable, rule-based collaboration. Practically, it offers a transparent, AI-assisted diagnostic tool for screenwriters and producers, complementing current industry systems. While limited by corpus size and non-traditional scripts, the framework establishes a foundation for integrating multimodal cues, adaptive learning, and professional validation in future research.

评估剧本结构是具有挑战性的，因为人工审查是主观的，而且成本很高，而自动化方法通常关注的是表面特征，而不是故事情节的深层架构。本研究引入了一个明确基于剧本结构理论的多主体分析框架，将西德·菲尔德的三幕结构和布莱克·斯奈德的十五拍模型付诸实践。通过将结构原则转换为可计算的规则，并为代理分配专门的分析角色，该框架识别行为，检测节拍，评估结构一致性，并解决解释冲突。在多个剧本测试中，该框架优于单一llm基线，实现了更高的节拍检测准确率（87.2% vs. 72.4%），更强的语义一致性和更强的可解释性。Agent分歧突出了结构上模糊的部分，如中点和主题节拍，提供了有价值的诊断见解。从理论上讲，该研究通过将叙事理论转化为可解释的、基于规则的协作来推进计算叙事学。实际上，它为编剧和制片人提供了一个透明的、人工智能辅助的诊断工具，补充了现有的行业体系。尽管受语料库大小和非传统脚本的限制，该框架为未来研究中整合多模态线索、自适应学习和专业验证奠定了基础。

{"title":"A computational approach to screenplay structure via multi-agent systems","authors":"Mei-Hua Hsu , Yi-Fan Wang , Max Yue-Feng Wang , Wei-Zhi Su","doi":"10.1016/j.entcom.2025.101077","DOIUrl":"10.1016/j.entcom.2025.101077","url":null,"abstract":"<div><div>Evaluating screenplay structure is challenging because manual reviews are subjective and costly, while automated methods often focus on surface features rather than the deeper architecture of storytelling. This study introduces a multi-agent analytical framework grounded explicitly in screenplay structure theory, operationalizing Syd Field’s three-act structure and Blake Snyder’s fifteen-beat model. By converting structural principles into computable rules and assigning specialized analytical roles to agents, the framework identifies acts, detects beats, assesses structural coherence, and resolves interpretive conflicts.</div><div>Tested on multiple screenplays, the framework outperformed a single-LLM baseline, achieving higher beat detection accuracy (87.2 % vs. 72.4 %), stronger semantic alignment, and greater interpretability. Agent disagreements highlighted structurally ambiguous segments, such as Midpoints and thematic beats, providing valuable diagnostic insights.</div><div>Theoretically, the study advances computational narratology by transforming narrative theory into explainable, rule-based collaboration. Practically, it offers a transparent, AI-assisted diagnostic tool for screenwriters and producers, complementing current industry systems. While limited by corpus size and non-traditional scripts, the framework establishes a foundation for integrating multimodal cues, adaptive learning, and professional validation in future research.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"56 ","pages":"Article 101077"},"PeriodicalIF":2.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of fuzzy decision support system in flipped classroom teaching mode of physical training theoretical 模糊决策支持系统在体育理论翻转课堂教学模式中的应用

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2026-01-01 DOI: 10.1016/j.entcom.2025.101071

Guiling Yan

Flipped classroom approaches in physical education training (PET) enhance student engagement by integrating theoretical and practical instruction through diverse teaching modes. To effectively evaluate and optimize these hybrid methods, this study introduces a fuzzy-based decision support system that assesses engagement levels across instructional modules. The system analyzes participation patterns before and after instructional blending, incorporating attendance and activity records to identify the most effective strategies. Through fuzzy inference and defuzzification, the model refines less effective methods and reinforces successful ones. Ultimately, this approach enables instructors to make data-driven adjustments that enhance overall learning effectiveness and sustain higher student participation in future PET sessions.

翻转课堂在体育训练中的应用，通过多样化的教学模式，将理论教学与实践教学相结合，提高学生的参与度。为了有效地评估和优化这些混合方法，本研究引入了一个基于模糊的决策支持系统来评估教学模块的参与水平。该系统分析教学混合前后的参与模式，结合出勤和活动记录来确定最有效的策略。通过模糊推理和去模糊化，对效果较差的方法进行改进，对效果较好的方法进行强化。最终，这种方法使教师能够进行数据驱动的调整，从而提高整体学习效率，并在未来的PET课程中保持更高的学生参与度。

引用次数: 0

Current serious game genres for stroke neurorehabilitation: A scoping review of randomized controlled trials 当前中风神经康复的严肃游戏类型：随机对照试验的范围审查

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2026-01-01 DOI: 10.1016/j.entcom.2025.101068

Juan J. Sánchez-Gil , Aurora Sáez , Laura Muñoz-Millán , David Cáceres-Gómez , Eduardo Cañete-Carmona

Stroke rehabilitation increasingly leverages serious games to enhance patient motivation and recovery, yet the diversity of genres applied in neurorehabilitation remains poorly systematized. This scoping review, aligned with PRISMA-ScR guidelines, analyzed 87 randomized controlled trials (2019–2025) published in Q1–Q2 journals to map the genres and subgenres of serious games used in post-stroke therapy. Both commercial systems (71%) and custom-made prototypes (29%) were examined, finding that action, puzzle, and simulation were the most prevalent Tier 1 (main) genres. Arcade-style mechanics and instruction-focused contexts were the most common, while cognitive and socio-affective domains were underrepresented. Popular entertainment genres such as Match-3, Tower Defense, and Turn-Based Tactical were absent, underscoring design gaps and opportunities for innovation. A multilayer labeling map was developed to classify narrative and mechanical dimensions, offering a structured lens to align game choice with therapeutic objectives. This review highlights the importance of genre diversity, personalization, and clearer reporting of game mechanics to advance gamified rehabilitation. Future research should explore neglected genres, incorporate multidomain outcomes, and establish standardized descriptors to more effectively connect gameplay features with clinical outcomes.

卒中康复越来越多地利用严肃游戏来增强患者的动力和恢复，但在神经康复中应用的类型多样性仍然缺乏系统化。这项范围审查与PRISMA-ScR指南一致，分析了第一季度至第二季度期刊上发表的87项随机对照试验（2019-2025），以绘制中风后治疗中使用的严肃游戏的类型和亚类型。我们研究了商业系统（71%）和定制原型（29%），发现行动、谜题和模拟是最普遍的第1层（主要）类型。街机风格的机制和以指导为中心的情境是最常见的，而认知和社会情感领域的代表性不足。流行的娱乐类型，如三消、塔防和回合制战术都没有出现，这凸显了设计差距和创新机会。我们开发了一个多层标签地图，将叙事和机制维度进行分类，提供一个结构化的视角，将游戏选择与治疗目标结合起来。这篇综述强调了类型多样性、个性化和更清晰的游戏机制报告对促进游戏化康复的重要性。未来的研究应该探索被忽视的类型，结合多领域的结果，并建立标准化的描述符，以更有效地将游戏功能与临床结果联系起来。

{"title":"Current serious game genres for stroke neurorehabilitation: A scoping review of randomized controlled trials","authors":"Juan J. Sánchez-Gil , Aurora Sáez , Laura Muñoz-Millán , David Cáceres-Gómez , Eduardo Cañete-Carmona","doi":"10.1016/j.entcom.2025.101068","DOIUrl":"10.1016/j.entcom.2025.101068","url":null,"abstract":"<div><div>Stroke rehabilitation increasingly leverages serious games to enhance patient motivation and recovery, yet the diversity of genres applied in neurorehabilitation remains poorly systematized. This scoping review, aligned with PRISMA-ScR guidelines, analyzed 87 randomized controlled trials (2019–2025) published in Q1–Q2 journals to map the genres and subgenres of serious games used in post-stroke therapy. Both commercial systems (71%) and custom-made prototypes (29%) were examined, finding that action, puzzle, and simulation were the most prevalent Tier 1 (main) genres. Arcade-style mechanics and instruction-focused contexts were the most common, while cognitive and socio-affective domains were underrepresented. Popular entertainment genres such as Match-3, Tower Defense, and Turn-Based Tactical were absent, underscoring design gaps and opportunities for innovation. A multilayer labeling map was developed to classify narrative and mechanical dimensions, offering a structured lens to align game choice with therapeutic objectives. This review highlights the importance of genre diversity, personalization, and clearer reporting of game mechanics to advance gamified rehabilitation. Future research should explore neglected genres, incorporate multidomain outcomes, and establish standardized descriptors to more effectively connect gameplay features with clinical outcomes.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"56 ","pages":"Article 101068"},"PeriodicalIF":2.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0