Naranjo Diana M, Prieto José R, Moltó Germán, Calatrava Amanda
Instituto de Instrumentación para Imagen Molecular (I3M), Centro Mixto CSIC-Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain.
Sensors (Basel). 2019 Jul 4;19(13):2952. doi: 10.3390/s19132952.
Cloud providers such as Amazon Web Services (AWS) stand out as useful platforms to teach distributed computing concepts as well as the development of Cloud-native scalable application architectures on real-world infrastructures. Instructors can benefit from high-level tools to track the progress of students during their learning paths on the Cloud, and this information can be disclosed via educational dashboards for students to understand their progress through the practical activities. To this aim, this paper introduces CloudTrail-Tracker, an open-source platform to obtain enhanced usage analytics from a shared AWS account. The tool provides the instructor with a visual dashboard that depicts the aggregated usage of resources by all the students during a certain time frame and the specific use of AWS for a specific student. To facilitate self-regulation of students, the dashboard also depicts the percentage of progress for each lab session and the pending actions by the student. The dashboard has been integrated in four Cloud subjects that use different learning methodologies (from face-to-face to online learning) and the students positively highlight the usefulness of the tool for Cloud instruction in AWS. This automated procurement of evidences of student activity on the Cloud results in close to real-time learning analytics useful both for semi-automated assessment and student self-awareness of their own training progress.
诸如亚马逊网络服务（AWS）这样的云提供商，是教授分布式计算概念以及在真实基础设施上开发云原生可扩展应用程序架构的有用平台。教师可以借助高级工具来跟踪学生在云端学习过程中的进度，这些信息可以通过教育仪表盘披露，以便学生了解自己在实践活动中的进展。为此，本文介绍了CloudTrail-Tracker，这是一个用于从共享的AWS账户获取增强型使用分析的开源平台。该工具为教师提供了一个可视化仪表盘，展示了所有学生在特定时间段内资源的汇总使用情况以及特定学生对AWS的具体使用情况。为了促进学生的自我管理，仪表盘还展示了每个实验环节的进度百分比以及学生的待办事项。该仪表盘已集成到四门使用不同学习方法（从面对面学习到在线学习）的云课程中，学生们积极强调了该工具对AWS云教学的实用性。这种对学生在云端活动证据的自动获取，产生了近乎实时的学习分析结果，这对半自动化评估和学生了解自己的培训进度都很有用。
