Enhancing Games with Assessment and Metacognitive Emphases (EGAME)

这个来自范德比尔特大学、Facet Innovations和Filament Games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）时的概念知识。这项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模型，以开发一种新的方法，让学生在诊断和支架学习牛顿力学的同时进行深度学习。该项目使用随机实验2 x 1设计，将单个控制条件与单个实验条件进行多次迭代，以测试游戏对牛顿力学学习的影响。物理学使用基于设计的研究与教师和学生，研究人员正在迭代开发和测试的互动和知识获取的学生通过访谈，前，后测试和隐形评估。 学生学习者的行动日志记录在游戏过程中沿着随机学生访谈。 学生的解释和游戏数据收集和分析领域的理解变化，使用前后测试评估。该项目将提供EGAME作为认知，概念转变，计算机自适应测试和隐马尔可夫建模领域新知识的推动者的验证，因为90至300名中学生学习牛顿力学，以及基于游戏的学习和设计中的其他科学内容。这个数字游戏平台的设计包括一个非常灵活的环境，将访问不同的观众群体，并有一个变革的影响，将推进理论，设计和实践在基于游戏的学习环境。

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.