Enhancing Games with Assessment and Metacognitive Emphases (EGAME)

这个由范德比尔特大学、Facet Innovations和Filament Games合作的开发和研究项目，设计、开发和测试了一个基于数字游戏的学习环境，用于支持、评估和分析中学生在学习物理，特别是牛顿力学方面的概念知识。本研究整合了先前的研究成果，并改进了计算机辅助测试和隐马尔可夫建模，以开发一种新的方法，让学生在诊断和脚手架学习牛顿力学的同时参与深度学习。该项目采用随机实验2 × 1设计，将单一控制条件与多个迭代的单一实验条件进行比较，以测试游戏对牛顿物理学习的影响。通过对教师和学生的设计研究，研究人员通过访谈、前后测试和隐形评估，迭代地开发和测试学生的互动和知识获取。在游戏过程中记录学生的学习行为日志以及随机的学生访谈。学生的解释和游戏数据收集和分析领域理解的变化使用测试前后评估。该项目将验证EGAME作为认知、概念变化、计算机自适应测试和隐马尔可夫建模等领域新知识的推动者，帮助90至300名中学生在基于游戏的学习和设计中学习牛顿力学和其他科学内容。这个数字游戏平台的设计包含了一个非常灵活的环境，可以让不同的受众群体访问，并具有变革性的影响，将推动基于游戏的学习环境中的理论，设计和实践。

This development and research project from Vanderbilt University, Facet Innovations, and Filament Games, designs, develops, and tests a digital game-based learning environment for supporting, assessing and analyzing middle school students' conceptual knowledge in learning physics, specifically Newtonian mechanics. This research integrates work from prior findings and refines computer assisted testing and Hidden Markov Modeling to develop a new methodology to engage students in deep learning while diagnosing and scaffolding the learning of Newtonian mechanics.The project uses a randomized experimental 2 x 1 design comparing a single control condition to a single experimental condition with multiple iterations to test the impact of the game on the learning of Newtonian physics. Using designed based research with teachers and students, the researchers are iteratively developing and testing the interactions and knowledge acquisition of students through interviews, pre and post tests and stealth assessment. Student learner action logs are recorded during game-play along with randomized student interviews. Students' explanations and game-play data are collected and analyzed for changes in domain understanding using pre-post tests assessment. The project will afford the validation of EGAME as an enabler of new knowledge in the fields of cognition, conceptual change, computer adaptive testing and Hidden Markov Modeling as 90 to 300 middle school students learn Newtonian mechanics, and other science content in game-based learning and design. The design of this digital game platform encompasses a very flexible environment that will be accessible to a diverse group of audiences, and have a transformational affect that will advance theory, design and practice in game-based learning environments.