LEADER 11013nam 2200517 450 001 996464397503316 005 20220325104352.0 010 $a3-030-77414-7 035 $a(CKB)5590000000523709 035 $a(MiAaPQ)EBC6668465 035 $a(Au-PeEL)EBL6668465 035 $a(OCoLC)1260343874 035 $a(PPN)25735817X 035 $a(EXLCZ)995590000000523709 100 $a20220325d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aHCI in games $eserious and immersive games : third international conference, HCI-games 2021, held as part of the 23rd HCI international conference, HCII 2021, virtual event, July 24-29, 2021, proceedings, part II /$fXiaowen Fang, editor 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource (414 pages) 225 1 $aLecture Notes in Computer Science ;$v12790 311 $a3-030-77413-9 327 $aIntro -- Foreword -- HCI International 2021 Thematic Areas and Affiliated Conferences -- Contents - Part II -- Contents - Part I -- Serious Games -- Mindful Gaming: User Experiences with Headspace and Walden, a Game -- 1 Introduction and Related Literature -- 1.1 Headspace and the Gamification of Mindfulness -- 1.2 Walden and Traditions of Mindful Play -- 1.3 Qualitative Studies on User Experiences and Why They Matter for Studying Mindfulness -- 1.4 Research Questions and Scope of This Study -- 2 Theoretical Framework -- 3 Method: Phenomenological Case Study -- 4 Findings -- 4.1 Mindfulness as Contemplative Self-reflection -- 4.2 Mindfulness as a Long-Term Process -- 4.3 Mindfulness as a Byproduct of Play, and a Third-Order Design Problem -- 4.4 Mindfulness as a Tension Between Exploring vs. Completing Objectives -- 5 Practical Applications of this Research for Iterative, Playcentric Design of Mindfulness Software -- 6 Limitations and Suggestions for Future Research -- 7 Conclusions and Suggestions for How to Develop Mindfulness Software -- References -- Gamification of ERP Training in Local Governments -- 1 Introduction -- 2 Literature Review -- 2.1 Gamification Features -- 2.2 Extrinsic Motivation -- 2.3 Intrinsic Motivation -- 2.4 Retention of Information -- 2.5 The Effectiveness of Traditional ERP Training -- 2.6 Experience of Local Governments in Training for New Technology -- 2.7 Gamification Application in the Enterprise Environment -- 2.8 Gamification Models in Education -- 3 Case Study -- 4 Proposed Research Model -- 5 Conclusion -- Appendix: Proposed Sample of the Gamification Training in One Local Government -- References -- Orpheus: A Voice-Controlled Game to Train Pitch Matching -- 1 Introduction -- 2 Related Works -- 2.1 Basic Concepts in Pitch Matching -- 2.2 Serious Games for Pitch Matching -- 3 Design and Implementation. 327 $a3.1 Game Design -- 3.2 Prototype Implementation -- 4 Pilot Case Study -- 5 Conclusion -- References -- Influence of a Video Game on Children's Attention to Food: Should Games Be Served with a Character During Mealtime? -- 1 Introduction -- 2 Background -- 2.1 Related Work -- 2.2 Literature Review -- 3 Design Concepts -- 3.1 Theoretical Basis -- 3.2 Feedback Design -- 3.3 Character Design -- 4 Materials and Methods -- 4.1 Materials -- 4.2 Pre-survey -- 4.3 Procedure -- 5 Results -- 6 Conclusion and Discussion -- References -- Ludus Magnus - A Serious Game for Learning the Latin Language -- 1 Introduction -- 2 Related Work -- 3 Concept of Ludus Magnus -- 4 Story of Ludus Magnus -- 5 Important Gameplay Mechanics -- 5.1 Game Engine -- 5.2 Quest System -- 5.3 Interactive Objects -- 5.4 Equipment System -- 5.5 Combat System -- 5.6 Vocabulary Trainer -- 5.7 Grammar Exercises -- 5.8 Level Design -- 6 Future Work -- 6.1 Future Game Content -- 6.2 Future Evaluation -- 7 Conclusion -- References -- PLAY for LEARNING: Serious Games to Assist Learning of Basic Didactic Concepts: A Pilot Study -- 1 Introduction -- 2 Background -- 3 Research Methodology -- 4 Solution Design Proposal -- 4.1 Interfaces and Interaction Design -- 4.2 Design Implementation -- 4.3 Preliminary Assessment -- 4.4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Improve Students' Learning Experience in General Chemistry Laboratory Courses -- 1 Introduction -- 2 Literature Review of VR Applications -- 2.1 Virtual Reality -- 2.2 Laboratory Education Methods -- 2.3 VR in Higher Education -- 3 Chemistry Lab and Proposed Design with VR Technology -- 3.1 Current Solution -- 3.2 Concerns of Current Solutions -- 3.3 Expectations of Future Systems -- 3.4 Possible Solutions -- 3.5 Proposed Study -- 4 Conclusions -- References. 327 $aA Study on Serious Game Practice to Improve Children's Global Competence -- 1 Introduction -- 1.1 Literature Review -- 2 Method -- 2.1 Design Concept -- 2.2 The Snake Battle -- 2.3 You Say One, I Say Two -- 2.4 First Meet -- 2.5 Animals Go Home -- 3 Results -- 4 Discussion -- 5 Limitation -- References -- JomGames: Creating a Motivating Learning Environment -- 1 The Behavioural Effects of Games on Students -- 2 Legacy and Related Works of Game Learning and Gamification -- 3 Methodology -- 4 Results and Findings -- 5 Conclusion, Limitation, and Future Work -- References -- Multicraft: A Multimodal Interface for Supporting and Studying Learning in Minecraft -- 1 Introduction -- 2 Prior Literature -- 2.1 Autcraft -- 2.2 Ability Based Design -- 2.3 Multimodal Learning Analytics -- 2.4 Spatial Reasoning Skills -- 2.5 Summary -- 3 Multicraft -- 3.1 Design Principles -- 3.2 System Technical Architecture -- 4 Part 1: User Experiences with Multicraft -- 4.1 Overview -- 4.2 Participants -- 4.3 User Testing Tasks -- 4.4 Data Collection -- 4.5 Data Analysis -- 4.6 Observations and Findings -- 5 Part 2: Multimodal Analyses of Minecraft Gameplay -- 5.1 Overview -- 5.2 Participants -- 5.3 User Testing Tasks -- 5.4 Data Collection -- 5.5 Data Analysis -- 5.6 Observations and Findings -- 6 Discussion -- 7 Limitations -- 8 Conclusion -- References -- Gamification and Learning -- Understanding the Impact on Learners' Reading Performance and Behaviour of Matching E-Learning Material to Dyslexia Type and Reading Skill Level -- 1 Introduction -- 2 Background -- 2.1 Dyslexia in Arabic -- 2.2 Adaptation in the E-Learning Domain -- 2.3 Related Work -- 3 Experiment 1: Dyslexia Type Adaptivity -- 3.1 Data Collection -- 3.2 DysTypeTrain System -- 3.3 Method -- 3.4 Participants -- 3.5 Findings -- 4 Experiment 2: Reading Skill Level Adaptivity. 327 $a4.1 Experiment's Questions and Hypotheses -- 4.2 Measurements and Data Collection -- 4.3 DysSkillTrain System -- 4.4 Method -- 4.5 Participants -- 4.6 Results -- 5 Discussion -- 6 Conclusion and Future Work -- References -- Scaffolding Executive Function in Game-Based Learning to Improve Productive Persistence and Computational Thinking in Neurodiverse Learners -- 1 Computational Thinking (CT) -- 1.1 Engaging Neurodiverse Learners in CT Through Games -- 2 Productive Persistence -- 3 Executive Function -- 3.1 Designing Supports for Neurodiverse Learners in CT through Games -- 4 Overview of INFACT -- 4.1 Example 1: NumberFactory -- 4.2 Example 2: Zoombinis -- 5 Discussion -- 6 Conclusion -- References -- A Framework of Gamified Learning Design Targeting Behavior Change and Design of a Gamificated Time Management Training Manual -- 1 Introduction -- 2 Behavior Change Model -- 2.1 TTM and SNAP Model -- 3 Design -- 3.1 Background of Design -- 3.2 Content of Design -- 3.3 Gamification of Design -- 4 Application -- 4.1 Environment -- 4.2 Application of the Manual -- 4.3 Discussion -- 5 Experiment -- 5.1 Questions and Hypothesis -- 5.2 Method -- 5.3 Results -- 5.4 Discussion -- 6 Conclusion -- References -- Can Games and Gamification Improve Online Learners' Outcomes and Satisfaction on the Madrasati Platform in Saudi Arabia? -- 1 Introduction -- 2 Background -- 2.1 Games and Gamification Elements -- 3 The Madrasati Platform -- 3.1 Teachers and the Madrasati Platform -- 3.2 The Effect on Learners of Integrating Games and Gamification into Learning -- 4 Discussion -- 5 Conclusion -- References -- Methodological Considerations for Understanding Students' Problem Solving Processes and Affective Trajectories During Game-Based Learning: A Data Fusion Approach -- 1 Introduction -- 2 Research Context and Purpose -- 2.1 Data Sources and Participants. 327 $a3 Approaches to Multimodal Data Collection and Analysis -- 3.1 Emotion from Facial Expression -- 3.2 Emotion from Gameplay Sequence -- 3.3 Multimodal Data Fusion Between Facial Expression and Gameplay Data -- 4 Multimodal Data Fusion of Zoombinis Gameplay Data -- 4.1 Data Wrangling Procedure -- 4.2 Modeling Students' Problem Solving Process with Hidden Markov Models -- 5 Discussion and Implications -- References -- Using Eye Tracking for Research on Learning and Computational Thinking -- 1 Introduction -- 2 Theoretical Constructs and Perspectives -- 2.1 Eye-Mind Assumption (EMA) and Visual Attention -- 2.2 Engagement -- 2.3 Inferring Cognitive Processes, States, and Traits via Eye Tracking -- 2.4 Cognitive Load and Effort -- 3 Prior Eye-Tracking Reviews -- 3.1 Summary -- 4 A Survey and Evaluation of Existing Eye-Tracking Technologies -- 4.1 Introduction -- 4.2 Evaluation of Freeware Eye-Trackers -- 5 Conclusion and Implication -- References -- Evaluating the Use of Visual Prompts in Online Meeting Applications for Kindergarteners -- 1 Introduction -- 2 Literature Review -- 3 Methods -- 3.1 Participants -- 3.2 Equipment -- 3.3 Tasks -- 3.4 Procedures -- 3.5 Design Implementation -- 3.6 Evaluation -- 4 Results -- 4.1 Accuracy Rate -- 4.2 Completion Time -- 4.3 Optimum Visual Prompt -- 5 Discussion -- 6 Conclusion -- References -- Gamification Design Predicaments for E-learning -- 1 Introduction -- 2 Related Work -- 3 Game Theory: Background -- 4 Gamification Design Predicaments -- 5 Discussion -- 6 Conclusion -- References -- Game Design, Creativity and e-Learning: The Challenges of Beginner Level Immersive Language Learning Games -- 1 Introduction: Remote Learning for Language Acquisition -- 2 Games as Learning Facilitators -- 3 Case Study: Portuguese as Foreign Language Course -- 3.1 Research Methods. 327 $a3.2 First Results and Discussion: Challenges and Opportunities. 410 0$aLecture notes in computer science ;$v12790. 606 $aComputer games$vCongresses 606 $aHuman-computer interaction$vCongresses 615 0$aComputer games 615 0$aHuman-computer interaction 676 $a794.8 702 $aFang$b Xiaowen 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996464397503316 996 $aHCI in Games$91997587 997 $aUNISA LEADER 05507nam 2200685 a 450 001 9910830464603321 005 20230721030236.0 010 $a1-281-31911-2 010 $a9786611319113 010 $a0-470-72420-X 010 $a0-470-72419-6 035 $a(CKB)1000000000376958 035 $a(EBL)351037 035 $a(OCoLC)476170259 035 $a(SSID)ssj0000130426 035 $a(PQKBManifestationID)11159706 035 $a(PQKBTitleCode)TC0000130426 035 $a(PQKBWorkID)10080655 035 $a(PQKB)11735367 035 $a(MiAaPQ)EBC351037 035 $a(EXLCZ)991000000000376958 100 $a20071026d2007 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aCooperative control of distributed multi-agent systems$b[electronic resource] /$fedited by Jeff S. Shamma 210 $aChichester, West Sussex, England ;$aHoboken, NJ $cJohn Wiley & Sons$dc2007 215 $a1 online resource (453 p.) 300 $aDescription based upon print version of record. 311 $a0-470-06031-X 320 $aIncludes bibliographical references and index. 327 $aCooperative Control of Distributed Multi-Agent Systems; Contents; List of Contributors; Preface; Part I Introduction; 1 Dimensions of cooperative control; 1.1 Why cooperative control?; 1.1.1 Motivation; 1.1.2 Illustrative example: command and control of networked vehicles; 1.2 Dimensions of cooperative control; 1.2.1 Distributed control and computation; 1.2.2 Adversarial interactions; 1.2.3 Uncertain evolution; 1.2.4 Complexity management; 1.3 Future directions; Acknowledgements; References; Part II Distributed Control and Computation 327 $a2 Design of behavior of swarms: From flocking to data fusion using microfilter networks2.1 Introduction; 2.2 Consensus problems; 2.3 Flocking behavior for distributed coverage; 2.3.1 Collective potential of flocks; 2.3.2 Distributed flocking algorithms; 2.3.3 Stability analysis for flocking motion; 2.3.4 Simulations of flocking; 2.4 Microfilter networks for cooperative data fusion; Acknowledgements; References; 3 Connectivity and convergence of formations; 3.1 Introduction; 3.2 Problem formulation; 3.3 Algebraic graph theory 327 $a3.4 Stability of vehicle formations in the case of time-invariant communication3.4.1 Formation hierarchy; 3.5 Stability of vehicle formations in the case of time-variant communication; 3.6 Stabilizing feedback for the time-variant communication case; 3.7 Graph connectivity and stability of vehicle formations; 3.8 Conclusion; Acknowledgements; References; 4 Distributed receding horizon control: stability via move suppression; 4.1 Introduction; 4.2 System description and objective; 4.3 Distributed receding horizon control; 4.4 Feasibility and stability analysis; 4.5 Conclusion; Acknowledgement 327 $aReferences5 Distributed predictive control: synthesis, stability and feasibility; 5.1 Introduction; 5.2 Problem formulation; 5.3 Distributed MPC scheme; 5.4 DMPC stability analysis; 5.4.1 Individual value functions as Lyapunov functions; 5.4.2 Generalization to arbitrary number of nodes and graph; 5.4.3 Exchange of information; 5.4.4 Stability analysis for heterogeneous unconstrained LTI subsystems; 5.5 Distributed design for identical unconstrained LTI subsystems; 5.5.1 LQR properties for dynamically decoupled systems; 5.5.2 Distributed LQR design; 5.6 Ensuring feasibility 327 $a5.6.1 Robust constraint fulfillment5.6.2 Review of methodologies; 5.7 Conclusion; References; 6 Task assignment for mobile agents; 6.1 Introduction; 6.2 Background; 6.2.1 Primal and dual problems; 6.2.2 Auction algorithm; 6.3 Problem statement; 6.3.1 Feasible and optimal vehicle trajectories; 6.3.2 Benefit functions; 6.4 Assignment algorithm and results; 6.4.1 Assumptions; 6.4.2 Motion control for a distributed auction; 6.4.3 Assignment algorithm termination; 6.4.4 Optimality bounds; 6.4.5 Early task completion; 6.5 Simulations; 6.5.1 Effects of delays; 6.5.2 Effects of bidding increment 327 $a6.5.3 Early task completions 330 $aThe paradigm of 'multi-agent' cooperative control is the challenge frontier for new control system application domains, and as a research area it has experienced a considerable increase in activity in recent years. This volume, the result of a UCLA collaborative project with Caltech, Cornell and MIT, presents cutting edge results in terms of the "dimensions" of cooperative control from leading researchers worldwide. This dimensional decomposition allows the reader to assess the multi-faceted landscape of cooperative control. Cooperative Control of Distributed Multi-Agent Systems is organized 606 $aDistributed artificial intelligence 606 $aControl theory 606 $aCooperation$xMathematics 606 $aDistributed databases 606 $aElectronic data processing$xDistributed processing 615 0$aDistributed artificial intelligence. 615 0$aControl theory. 615 0$aCooperation$xMathematics. 615 0$aDistributed databases. 615 0$aElectronic data processing$xDistributed processing. 676 $a003.5 676 $a003/.5 701 $aShamma$b Jeff S$01663527 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830464603321 996 $aCooperative control of distributed multi-agent systems$94020888 997 $aUNINA