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.

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 serious game analytics data collection

Autorentext

Christian Sebastian Loh's research interests focus on the performance measurement/assessment/ improvement with and the analytics for serious games and virtual environments. He was the 2008/09 President for the Division of Multimedia Production of the AECT (Association for Educational Communications and Technology), and recipient of the 2009 Defense University Research Instrument Program grant awarded by the Army Research Office (ARO). He has designed and developed serious games for research, Information Trails for telemetric performance measurement, Performance Tracing Report Assistant (PeTRA) for performance improvement via gameplay data visualization. He is currently serving on the editorial board of Technology, Knowledge and Learning (TKL), and as associate editor for International Journal of Gaming and Computer-Mediated Simulations (IJGCMS), and International Journal of Game-Based Learning (IJGBL).

Dr. Yanyan Sheng's research interests focus on modeling dichotomous responses in educational and psychological measurement using advanced modern statistics, and specifically on developing and applying complex yet efficient Bayesian hierarchical item response models. She developed complex Bayesian multidimensional models with various latent dimensional structures and has written and published MATLAB programs for these models. She is also interested in applying the biased coin up-and-down design to adaptive testing.

Dr. Ifenthaler's research interests focus on learning analytics, cognitive structures, complex problem solving, learning analytics, game-based and mobile learning, as well as computer-based assessment. He developed computer-based methodologies for the assessment and analysis of graphical and natural language representations (SMD Technology, HIMATT, AKOVIA, TASA) as well as games for teacher education (DIVOSA, SeSIM). Dr. Ifenthaler's research outcomes spans numerous co-authored books, book chapters, journal articles andinternational conference papers. He was a 2012 Fulbright Scholar-in-Residence at the Jeannine Rainbolt College of Education, the University of Oklahoma, USA and Interim Department Chair and Professor at the University of Mannheim, Germany. He is the 2013/2014 President for the AECT (Association for Educational Communications and Technology) Division Design and Development, 2013/2014 Chair for the AERA Special Interest Group Technology, Instruction, Cognition and Learning and Program Chair for the international conference on Cognition and Exploratory Learning in the Digital Age. Dr. Ifenthaler received the 2012 Outstanding Journal Article Award by AECT, 2009 Outstanding Reviewer Award for Educational Technology Research and Development and the 2006 Outstanding Dissertation Award by University of Freiburg, Germany. He is the Editor-In-Chief of Technology, Knowledge and Learning.

Klappentext

This first-of-its-kind reference moves the concepts and methodologies of game analytics and learning analytics into the emerging field of serious games. The book calls for more validated and standardized research into serious games analytics, backing up this demand with ways that player data can be transformed into information of value to the academic and serious games sectors. Featured methodologies derive from diverse disciplines, from computer science and data visualization to learning science and statistics. And the volume's second half highlights new frontiers for serious games in medical education and patient care, psychological profile generation, and learning support.

Included in the coverage:

• A meta-analysis of data collection in serious games research.
• Measuring expert-performance for serious games analytics: from data to insights.
• Comparative visualization of player behavior for serious games analytics.
• The role of serious games in robot exoskeleton assisted rehabilitation of stroke patients.
• Design of game-based stealth assessment and learning support.
• A game design methodology for generating a psychological profile of players.

Serious Games Analytics gives educators, instructional designers, and researchers in educational technology a fuller grasp of the knowledge learners access in serious game play, and data and ideas leading to the next wave of serious games.

Inhalt
An Introduction to Serious Games Analytics (SEGA).- Methods for Learners' Gameplay Data Collection.- Methods for Learners' Gameplay Data Analysis.- Visualization of Learners' Play-paths.- Serious Games Analytics Methodologies.- Serious Games, Virtual Worlds, Simulations, and Augmented Reality.