| 书目名称 | Serious Games Analytics | | 副标题 | Methodologies for Pe | | 编辑 | Christian Sebastian Loh,Yanyan Sheng,Dirk Ifenthal | | 视频video | | | 概述 | Includes international collaborations and current perspectives on serious game research.Offers practical knowledge on how to conduct serious games research.Critically examines various methods of serio | | 丛书名称 | Advances in Game-Based Learning | | 图书封面 |  | | 描述 | This volume brings together research on how gameplay data in serious games may be turned into valuable analytics or actionable intelligence for performance measurement, assessment, and improvement. Chapter authors use empirical research methodologies, including existing, experimental, and emerging conceptual frameworks, from various fields, such as: computer science software engineering educational data mining statistics information visualization. Serious games is an emerging field where the games are created using sound learning theories and instructional design principles to maximize learning and training success. But how would stakeholders know what play-learners have done in the game environment, and if the actions performance brings about learning? Could they be playing the game for fun, really learning with evidence of performance improvement, or simply gaming the system, i.e., finding loopholes to fake that they are making progress? This volume endeavors to answer these questions. | | 出版日期 | Book 2015 | | 关键词 | Gameplay Data in Serious Games; Gameplay in Computer Science; Gameplay in Educational Data Mining; Game | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-05834-4 | | isbn_softcover | 978-3-319-38219-7 | | isbn_ebook | 978-3-319-05834-4Series ISSN 2567-8086 Series E-ISSN 2567-8485 | | issn_series | 2567-8086 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 17:51:16
