Intelligent Collaborative Assessment in Game-Based Learning: A Bibliometric Analysis

Game-based learning environments are capturing increasing attention for their ability to engage learners and promote knowledge acquisition. Artificial intelligence holds immense potential to personalize learning experiences and deliver intelligent assessment. Collaborative learning approaches, when integrated seamlessly with game settings, can further enhance the learning process. This study explores the domain of intelligent collaborative assessment in game-based learning environments through bibliometric analysis. Using data from Scopus, we uncover important research themes, global impact trends, influential sources, and the evolution of research over time. Our analysis of findings reveals a gap in research concerning the integration of AI assessment within collaborative game-based learning environments. To address this gap, we propose a novel framework that utilizes continuous assessment, personalized learning, and dynamic adaptation to optimize the learning experience for all participants. This study provides valuable insights to guide future research and educational improvements in intelligent collaborative assessment for game-based learning.