Entertainment Computing最新文献_第10页

Supporting teachers, engaging students: A collaborative model for K-12 computing education 支持教师，吸引学生：K-12计算机教育的协作模式

IF 2.8 3区计算机科学

Entertainment Computing Pub Date : 2025-03-14 DOI: 10.1016/j.entcom.2025.100937

Alberto Monge Roffarello, Juan Pablo Sáenz

{"title":"Supporting teachers, engaging students: A collaborative model for K-12 computing education","authors":"Alberto Monge Roffarello, Juan Pablo Sáenz","doi":"10.1016/j.entcom.2025.100937","DOIUrl":"10.1016/j.entcom.2025.100937","url":null,"abstract":"<div><div>Although the importance of Computational Thinking (CT) for children is increasingly recognized, its adoption in computing education curricula in primary schools is limited by several open challenges, including teachers’ training and curricula development. Seeking to systematize a process that enables primary school teachers to teach CT through computing education in primary schools, we present the design, evaluation, and analysis of an introductory coding course for 4th-grade classes in a large Italian city, utilizing the Scratch platform. The course followed a project-based learning approach, empowering groups of children in designing and implementing simple video games, and explored the adoption of a collaborative strategy through which computing experts, class teachers, and high-school tutors proactively supported the project work. We evaluated and refined the course educational strategies by conducting an observational study and co-designing activities with the involved teachers. Then, we derived an educational model that may allow K-12 teachers and experts to collaborate in designing and implementing computing education courses that are engaging, inclusive, and supportive.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"54 ","pages":"Article 100937"},"PeriodicalIF":2.8,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

In case players were wondering: A topic modelling and sentiment analysis study of community discussions on weapon cases in the CS:GO game 如果玩家想知道：CS:GO游戏中武器案例的社区讨论的主题建模和情感分析研究

IF 2.8 3区计算机科学

Entertainment Computing Pub Date : 2025-03-06 DOI: 10.1016/j.entcom.2025.100936

Zhiyu Chen , Bieke Zaman

引用次数: 0

EnTube: Exploring key video features for advancing YouTube engagement YouTube：探索关键视频功能，以提高YouTube的参与度

IF 2.8 3区计算机科学

Entertainment Computing Pub Date : 2025-03-01 DOI: 10.1016/j.entcom.2025.100934

Truong Le, Minh-Vuong Nguyen-Thi, Minh-Tu Le, Hien-Vi Nguyen-Thi, Tung Le, Huy Tien Nguyen

{"title":"EnTube: Exploring key video features for advancing YouTube engagement","authors":"Truong Le, Minh-Vuong Nguyen-Thi, Minh-Tu Le, Hien-Vi Nguyen-Thi, Tung Le, Huy Tien Nguyen","doi":"10.1016/j.entcom.2025.100934","DOIUrl":"10.1016/j.entcom.2025.100934","url":null,"abstract":"<div><div>The proliferation of video sharing on platforms like YouTube has highlighted the importance of accurately predicting video engagement. Existing models for predicting video appeal face challenges in transparency and accuracy. This study proposes a multi-modal deep learning approach to forecast video engagement on YouTube. We utilize a multi-modal deep learning model that integrates video titles, audio, thumbnails, content, and tags for engagement prediction, classifying videos into three engagement categories: Engage, Neutral, and Not Engage. A unique dataset, the EnTube dataset, was compiled, featuring 23,738 videos from various genres and 72 Vietnamese YouTube channels. This dataset aids in overcoming the obstacles of data collection and analysis for video engagement. Our approach demonstrates the potential of multi-modal features in enhancing prediction accuracy beyond single-feature models. Explainable Artificial Intelligence techniques are employed to interpret the factors influencing video engagement, offering insights for content optimization. The study’s findings hold promise for applications in video recommendation systems and content strategy adjustments.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"53 ","pages":"Article 100934"},"PeriodicalIF":2.8,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143519648","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

Why gamers use multitasking and how it works on satisfaction and reuse intention 游戏玩家为何使用多任务处理，它如何影响满意度和重复使用意向

IF 2.8 3区计算机科学

Entertainment Computing Pub Date : 2025-02-21 DOI: 10.1016/j.entcom.2025.100935

Yunshin Bae , Jun Hyuk Cho , Changsok Yoo

{"title":"Why gamers use multitasking and how it works on satisfaction and reuse intention","authors":"Yunshin Bae , Jun Hyuk Cho , Changsok Yoo","doi":"10.1016/j.entcom.2025.100935","DOIUrl":"10.1016/j.entcom.2025.100935","url":null,"abstract":"<div><div>Multitasking has become a common activity in media usage, but there is a significant research gap regarding its influence on media usage patterns. This is particularly true for the rapidly growing field of video games, where various controversies regarding multitasking persist, yet comprehensive studies remain scarce. This study employs the Uses and Gratifications (U&G) theory to investigate how different motivations for both game-related and unrelated multitasking influence these behaviors, and how such multitasking affects cognitive and emotional satisfaction with the media and behavioral intentions. To achieve this, responses from 598 game users in South Korea were collected and analyzed. The analysis, conducted using PLS-SEM, revealed that the choice of multitasking is linked to specific usage motivations. Consistent with U&G theory, game-related multitasking is a choice made by users to maximize their satisfaction with the game. Additionally, we found that multitasking among game users enhances media satisfaction and increases the intention for continued use rather than hindering media usage. This underscores the importance of context in understanding multitasking behaviors.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"53 ","pages":"Article 100935"},"PeriodicalIF":2.8,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488318","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

Representing remote locations with location-based augmented reality game design 用基于位置的增强现实游戏设计代表远程位置

IF 2.8 3区计算机科学

Entertainment Computing Pub Date : 2025-02-18 DOI: 10.1016/j.entcom.2025.100932

Yasas Sri Wickramasinghe , Heide Karen Lukosch , James Everett , Stephan Lukosch

{"title":"Representing remote locations with location-based augmented reality game design","authors":"Yasas Sri Wickramasinghe , Heide Karen Lukosch , James Everett , Stephan Lukosch","doi":"10.1016/j.entcom.2025.100932","DOIUrl":"10.1016/j.entcom.2025.100932","url":null,"abstract":"<div><div>Location-based augmented reality games (LBARGs) allow for interaction with the physical environment of a player. This research study investigates the representation of physically remote locations in LBARGs and the utilization of a location-sharing player’s (LSP) location to engage in gameplay in remote locations. We identified three modes, i.e., tabletop, overlay, and window, to represent a player’s location to another player not at the same location. Based on these modes, we designed a LBARG to study the impact of the different modes on spatial presence and immersion. We recruited 30 participants (n=30) for a within-subjects study. Each participant experienced the different representation modes and we evaluated their experience using quantitative as well as qualitative methods. The results show that the chosen game mode significantly impacts the players’ spatial presence. For the LBARG, we also designed a game mechanic that specifically used the physical properties of the represented remote location. The qualitative findings highlight that utilizing the physical environment helps to connect remote locations and people. Our findings can guide future game designers on how to design for spatial presence and immersion within LBARGs.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"53 ","pages":"Article 100932"},"PeriodicalIF":2.8,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454443","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

Digital gaming during the COVID-19 pandemic: Examining the interplay of psychosocial problems, gaming motivations, and gaming disorder severity COVID-19大流行期间的数字游戏：研究心理社会问题、游戏动机和游戏障碍严重程度的相互作用

IF 2.8 3区计算机科学

Entertainment Computing Pub Date : 2025-02-18 DOI: 10.1016/j.entcom.2025.100933

Felix Reer

{"title":"Digital gaming during the COVID-19 pandemic: Examining the interplay of psychosocial problems, gaming motivations, and gaming disorder severity","authors":"Felix Reer","doi":"10.1016/j.entcom.2025.100933","DOIUrl":"10.1016/j.entcom.2025.100933","url":null,"abstract":"<div><div>The current study aimed to provide a deeper understanding of the factors underlying the development of addictive gaming (‘gaming disorder’, GD) during the COVID-19 pandemic. A path model was designed to examine the interplay of COVID-19-related fears, negative daily life impacts experienced during the pandemic, psychosocial problems (stress, depression/anxiety, loneliness), gaming motivations (escapism, coping, fantasy, and social motivations), and GD severity. The model was tested using an online survey administered to 504 German game users. It was found that gaming behaviors changed to a certain degree during the pandemic. Path modeling indicated that fear of COVID-19 and perceived negative daily life impacts may have played roles in the development of GD during the pandemic: they were associated with increased feelings of stress, depression/anxiety, and loneliness experienced during the pandemic, which, in turn, were (directly or indirectly) related to increased levels of GD severity. Gaming driven by escapism motives was identified as a significant predictor of GD severity and was found to mediate the relationship between stress and depression/anxiety and GD severity.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"54 ","pages":"Article 100933"},"PeriodicalIF":2.8,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143931807","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

Child computer interactions: Cognitive development and segmenting unsafe video contents: A review 儿童电脑互动：认知发展与分割不安全视讯内容：综述

IF 2.8 3区计算机科学

Entertainment Computing Pub Date : 2025-02-16 DOI: 10.1016/j.entcom.2025.100931

Irwa Zahoor, Sajaad Ahmed Lone

{"title":"Child computer interactions: Cognitive development and segmenting unsafe video contents: A review","authors":"Irwa Zahoor, Sajaad Ahmed Lone","doi":"10.1016/j.entcom.2025.100931","DOIUrl":"10.1016/j.entcom.2025.100931","url":null,"abstract":"<div><div>Computer Technology (CT) is now an integral part of our daily lives, influencing various aspects of human activity, particularly those of children. Child Computer Interactions a specialized area within CT, focuses on enhancing children’s physical activities, psychology, education, and communication through diverse computer applications. CCI is a steadily growing field that focuses on children as a prominent and emergent user group. This review article highlights the lack of research regarding the effective use of CCI technologies to promote cognitive development while reducing the risks linked to harmful digital content. The paper systematically examines the influence of CCI technologies on the cognitive development of children aged 0 to 12 years, addressing the research problem of inadequate filtering methods for unsafe video content that children are exposed to in today’s screen-dominated environment. It highlights how technological innovations, particularly in gaming, artificial intelligence, and media applications, are designed to enhance children’s skills while safeguarding their digital environment. A critical aspect of this review is the assessment of methods to filter and mitigate exposure to unsafe video content, a growing concern in today’s screen-dominated environment. The findings reveal that CCI programs significantly enhance children’s knowledge and skills with high accuracy. Moreover, the review underscores the importance of machine ethics in guiding the moral behavior of machines and ensuring the usability and safety of these technologies. This comprehensive analysis provides valuable insights into the role of CCI in fostering cognitive development and protecting children from inappropriate content.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"53 ","pages":"Article 100931"},"PeriodicalIF":2.8,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454444","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

Using search algorithm statistics for assessing maze and puzzle difficulty 使用搜索算法统计评估迷宫和谜题难度

IF 2.8 3区计算机科学

Entertainment Computing Pub Date : 2025-02-15 DOI: 10.1016/j.entcom.2025.100925

Elio Valenzuela , Hans Schaa , Nicolas A. Barriga , Gustavo Patow

{"title":"Using search algorithm statistics for assessing maze and puzzle difficulty","authors":"Elio Valenzuela , Hans Schaa , Nicolas A. Barriga , Gustavo Patow","doi":"10.1016/j.entcom.2025.100925","DOIUrl":"10.1016/j.entcom.2025.100925","url":null,"abstract":"<div><div>A video game’s difficulty has a large impact on player engagement. For instance, it is crucial in some genres to give the players a challenge difficult enough without frustrating them. We propose a simple method for assessing game-level difficulty as a precursor to adapting it to a specific player. In particular, we propose using simple performance metrics of algorithms such as <span><math><msup><mrow><mi>A</mi></mrow><mrow><mo>∗</mo></mrow></msup></math></span> and Breadth-First Search (BFS) as a proxy for the difficulty of puzzles. We performed user studies using a 2D maze simulator and a Sokoban game implementation; both built into the Unity game engine. We show that, for 2D mazes generated by Binary Space Partitioning, the number of nodes expanded by BFS highly correlates with the number of steps a human player takes to reach the goal. For Sokoban puzzles, the closed list length of an A* search is highly correlated to perceived difficulty and the number of movements a human player takes to solve the puzzle. These results show that simple metrics are probably good enough to assess a given level’s difficulty, which is a first step towards being able to personalize the difficulty of a maze or a puzzle to a particular player.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"53 ","pages":"Article 100925"},"PeriodicalIF":2.8,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429767","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

DEEP: A model of gaming preferences informed by the hierarchical nature of goal-oriented cognition DEEP：基于目标导向认知的层次属性的游戏偏好模型

IF 2.8 3区计算机科学

Entertainment Computing Pub Date : 2025-02-15 DOI: 10.1016/j.entcom.2025.100930

Edgar Dubourg, Valérian Chambon

{"title":"DEEP: A model of gaming preferences informed by the hierarchical nature of goal-oriented cognition","authors":"Edgar Dubourg, Valérian Chambon","doi":"10.1016/j.entcom.2025.100930","DOIUrl":"10.1016/j.entcom.2025.100930","url":null,"abstract":"<div><div>Video game design and player engagement revolve around the concept of agency, which refers to the ability to shape one’s environment through personal choices and actions. However, different types of agentive experiences can be distinguished according to the nature of the agent’s goal. Recent models of voluntary action suggest that goals are organized hierarchically. In this paper, we test the ability of these models to explain variability in gaming preferences. First, we performed a factor analysis on game-related actions that participants ( N = 750) were asked to rate on an interest scale. We found that game preferences varied along 4 dimensions organized along gradients of goal abstraction and exploration (Discovering, Experimenting, Expanding, Performing, or DEEP dimensions). We then automatically annotated video games ( N = 16,000) on each of these dimensions and tested the hierarchical structure of goal-directed actions in video games. Finally, in a pre-registered study ( N = 1000), we show that the DEEP dimensions predict participants’ preferred video games and correlate with expected psychological factors. We suggest that this research can help improve existing taxonomies of videogame types, better understand player preferences, and refine the relationship between game design and human psychology.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"53 ","pages":"Article 100930"},"PeriodicalIF":2.8,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465048","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

Music genre classification using deep neural networks and data augmentation 基于深度神经网络和数据增强的音乐类型分类

IF 2.8 3区计算机科学

Entertainment Computing Pub Date : 2025-02-13 DOI: 10.1016/j.entcom.2025.100929

Thanh Chu Ba , Thuy Dao Thi Le , Loan Trinh Van

{"title":"Music genre classification using deep neural networks and data augmentation","authors":"Thanh Chu Ba , Thuy Dao Thi Le , Loan Trinh Van","doi":"10.1016/j.entcom.2025.100929","DOIUrl":"10.1016/j.entcom.2025.100929","url":null,"abstract":"<div><div>Music is an indispensable part of spiritual life. Today, humanity’s musical treasure is truly huge and precious, and the number of musical works is constantly increasing. Computers, machine learning, and deep learning have greatly aided in the storing, organizing, searching, and enjoying of musical works in priceless treasures. Many music databases have been built for such music-data processing studies. One operation that needs to be handled automatically for musical works is musical genre classification (MGC). This paper presents new research results on MGC for GTZAN music data. Deep neural networks, such as convolutional neural networks (CNN), long short-term memory (LSTM), gated recurrent units (GRU), and capsule neural networks (CSN), have produced excellent results when combined with data augmentation methods such as splitting audio files, noise addition, and pitch shifting. A classification accuracy of 99.91% for the ten musical genres of GTZAN was achieved using the CSN model with the Mel spectrogram as input features and data enhanced by the aforementioned methods. This classification accuracy outperformed that of all previous GTZAN classification accuracy studies.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"53 ","pages":"Article 100929"},"PeriodicalIF":2.8,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438206","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