Serious games analytics : methodologies for performance measurement, assessment, and improvement / edited by Christian Sebastian Loh, Yanyan Sheng, Dirk Ifenthaler

Includes bibliographical references and index.

Part 1. Foundations of serious game analytics -- 1. Serious games analytics: theoretical framework -- 2. A meta-analysis of data collection in serious games research -- Part 2. Measurement of data in serious games analytics -- 3. Guidelines for the design and implementation of game telemetry for serious games analytics -- 4. The dynamical analysis of log data within educational games -- 5. Measuring expert performance for serious games analytics: from data to insights -- 6. Cluster evaluation, description, and interpretation for serious games -- Part 3. Visualizations of data for serious games analytics -- 7. Comparative visualization of player behavior for serious game analytics -- 8. Examining through visualization what tools learners access as they play a serious game for middle school science -- Part 4. Serious games analytics for medical learning -- 9. Using visual analytics to inform rheumatoid arthritis patient choices -- 10. The role of serious games in robot exoskeleton-assisted rehabilitation of stroke patients -- 11 .Evaluation-based design principles -- Part 5. Serious games analytics for learning and education -- 12. Analytics-driven design: impact and implications of team member psychological perspectives on a serious games (SGs) design framework -- 13. Design of game-based stealth assessment and learning support -- 14. An application of exploratory data analysis in the development of game-based assessments -- 15. Serious games analytics to measure implicit science learning -- Part 6. Serious games analytics design showcases -- 16. A game design methodology for generating a psychological profile of players -- 17. Replay analysis in open-ended educational games -- 18. Using the startle eye-blink to measure affect in players -- 19. Using pattern matching to assess gameplay.

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.