[论文解读] Combining Gamification and Intelligent Tutoring Systems in a Serious Game for Engineering Education

Ying Tang, Ryan Hare|arXiv (Cornell University)|May 26, 2023

Intelligent Tutoring Systems and Adaptive Learning被引用 4

一句话总结

本文提出了一种与智能导师系统（ITS）集成的个性化、游戏化严肃游戏，以提升工程教育。通过结合计算智能实现的自适应学习与基于网络摄像头数据的实时情绪状态估计，该系统提高了学生的参与度和知识保留率，在电气工程课程中的前后测结果显示学习成效显著提升。

ABSTRACT

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.

研究动机与目标

• 通过开发一种可访问的个性化学习系统，解决工程教育中教师资源有限的问题。
• 通过在严肃游戏环境中实施游戏化，提高学生参与度。
• 通过将自适应辅导与实时情绪状态监测相结合，提升教育效果。
• 基于学生反馈和课堂观察，对系统进行迭代优化。
• 通过前后测评估系统对学生学习成果的影响。

提出的方法

• 该系统结合专家设计的课程结构与计算智能，以自适应方式支持学习者。
• 它利用游戏内操作数据和基于网络摄像头的情绪状态估计，定制学习体验。
• 游戏化界面通过挑战和奖励激励学生，提高互动性。
• 系统在学生展示出足够的基础知识前，延迟提供实验任务的访问权限。
• 设计迭代基于多个学期的学生反馈和课堂观察结果。
• 通过前后测衡量知识增长，比较使用与不使用个性化系统的情况。

实验结果

研究问题

• RQ1 将游戏化与ITS结合，对工程教育中学生参与度有何影响？
• RQ2 实时情绪状态估计在严肃游戏中对自适应辅导的提升程度如何？
• RQ3 个性化学习系统对早期电气工程课程中学生知识获取的影响是什么？
• RQ4 学生反馈和课堂观察如何指导系统设计的迭代改进？
• RQ5 与传统实验任务相比，使用该系统可衡量的学习成效有哪些？

主要发现

• 使用个性化学习系统的学生成前后测成绩显著提高，表明知识获取能力增强。
• 该系统成功在学生展示足够基础知识前延迟了实验任务的访问。
• 学生与系统的互动为未来的设计迭代提供了宝贵见解。
• 基于网络摄像头数据的情绪状态估计有助于实现自适应支持，尽管未量化具体性能指标。
• 课堂观察和学生反馈在优化系统的可用性和参与度功能方面发挥了关键作用。
• 游戏化与ITS的结合使工程教育背景下的学习体验更具吸引力和有效性。