EAGER: Reimagining Teachers' Assessment Literacy Using Game-Based Learning Analytics

教育大数据的基本前提是，技术可以帮助教师和学校做出基于数据的决策，以更好地支持学生的学习。随着技术在课堂上的使用不断增加，技术使用产生的数据也将增加。教师们很快就会被要求开发一套全新的评估素养，利用教育技术提供的丰富数据和分析。然而，对于如何处理和呈现这些数据以反映教师的决策和教学愿望，人们知之甚少。为了解决这一差距，该项目将通过利用基于游戏的评估来帮助教师成为教育技术中嵌入的分析和算法的重要消费者，从而重新构想教师在数据和技术丰富的课堂中的评估素养。有了更多有文化的教师，就有可能最大限度地发挥教育技术的潜力，这样教师就可以在学习过程中提供个性化和数据驱动的反馈。该项目将利用现有的基于游戏的评估，Shadowspect，衡量共同核心数学标准以及认知和非认知技能，如空间推理和毅力。研究人员将进行基于设计的研究，以迭代开发和嵌入游戏中的交互式仪表板，并调查仪表板的不同表示和特征如何有效地支持教师的理解并告知他们的行动。此外，研究人员将研究如何使用学习分析来直接支持K-12教师的评估实践，并确定教师在这一领域取得成功所需的知识和技能。本研究的最终目标是了解大数据时代教师的评估素养，并得出交互式仪表板工具的通用设计原则，使教师无需进行实质性的外部培训即可方便地使用数据。最终，这项研究可以引导未来的调查，即当教师对学习分析有了更多的了解时，他们的形成性评估实践可能会发生什么变化。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The underlying premise of big data in education is that technology can help teachers and schools make data-informed decisions to better support student learning. As technology use in classrooms continues to increase, the data generated from technology use will also increase. Teachers will soon be required to develop a completely new set of assessment literacies around using the rich data and analytics provided in educational technology. However, little is known about how these kinds of data should be processed and presented to reflect teachers' decision-making and pedagogical desires. To address this gap, this project will reimagine teachers' assessment literacy in data- and technology-rich classrooms by leveraging a game-based assessment to help teachers become educated and critical consumers of analytics and algorithms embedded in educational technology. With more literate teachers, it is possible to maximize the potential of educational technology so that teachers can provide personalized and data-driven feedback during the process of learning.This project will leverage an existing game-based assessment, Shadowspect, that measures Common Core math standards as well as cognitive and noncognitive skills such as spatial reasoning and persistence. The researchers will conduct design-based research to iteratively develop and embed interactive dashboards in the game and investigate how effectively different representations and features of the dashboards can support teachers' understanding and inform their actions. Additionally, the researchers will investigate how learning analytics can be used to directly support K-12 teachers' assessment practices and identify the knowledge and skills teachers need to be successful in this area. The ultimate goal of the research is to understand teachers' assessment literacy in the era of big data and yield generalizable design principles for interactive dashboard tools that can facilitate teachers' data use without substantive external training. Ultimately, this research can lead to future investigations of how teachers' formative assessment practices might change when they have an increased understanding of learning analytics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.