We provide ongoing results from the development of a personalized learning system integrated into a serious game. Given limited instructor resources, the use of computerized systems to help tutor students offers a way to provide higher quality education and to improve educational efficacy. Personalized learning systems like the one proposed in this paper offer an accessible solution. Furthermore, by combining such a system with a serious game, students are further engaged in interacting with the system. The proposed learning system combines expert-driven structure and lesson planning with computational intelligence methods and gamification to provide students with a fun and educational experience. As the project is ongoing from past years, numerous design iterations have been made on the system based on feedback from students and classroom observations. Using computational intelligence, the system adaptively provides support to students based on data collected from both their in-game actions and by estimating their emotional state from webcam images. For our evaluation, we focus on student data gathered from in-classroom testing in relevant courses, with both educational efficacy, results and student observations. To demonstrate the effect of our proposed system, students in an early electrical engineering course were instructed to interact with the system in place of a standard lab assignment. The system would then measure and help them improve their background knowledge before allowing them to complete the lab assignment. As they played through the game, we observed their interactions with the system to gather insights for future work. Additionally, we demonstrate the system's educational efficacy through pre-post-test results from students who played the game with and without the personalized learning system.

翻译：我们提供了集成于严肃游戏中的个性化学习系统开发的阶段性成果。在教师资源有限的情况下，利用计算机化系统辅助学生教学，为提供更高质量教育及提升教学效能提供了可行方案。本文提出的个性化学习系统等方案提供了易获取的解决方案。此外，通过将此类系统与严肃游戏相结合，能进一步增强学生与系统的互动性。该学习系统融合了专家驱动的课程结构设计与计算智能方法及游戏化元素，旨在为学生提供兼具趣味性与教育性的体验。由于该项目已持续多年，系统基于学生反馈与课堂观察进行了多次设计迭代。通过计算智能技术，系统能根据学生游戏内行为数据及通过摄像头图像评估的情绪状态，自适应地提供支持。评估阶段，我们重点关注相关课程课堂测试中收集的学生数据，涵盖教学效能、成果及学生观察记录。为验证系统效果，我们让电气工程入门课程的学生在标准实验任务中改用本系统进行交互。系统在允许学生完成实验任务前，会先测量并帮助其提升背景知识水平。通过记录学生在游戏中的互动行为，我们为后续研究收集了洞察。同时，我们通过对比使用与未使用个性化学习系统的两组学生的前后测成绩，验证了系统的教学效能。