A Visual Dashboard to Track Learning Analytics for Educational Cloud Computing

[EN] 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. This research was funded by the Spanish Ministerio de Economia, Industria y Competitividad, grant number TIN2016-79951-R (BigCLOE) and by the Vicerrectorado de Estudios, Calidad y Acreditacion of the Universitat Politecnica de Valencia (UPV) to develop the PIME B29. Naranjo, DM.; Prieto, JR.; Moltó, G.; Calatrava Arroyo, A. (2019). A Visual Dashboard to Track Learning Analytics for Educational Cloud Computing. Sensors. 19(13):1-15. https://doi.org/10.3390/s19132952 Porter, W. W., Graham, C. R., Spring, K. A., & Welch, K. R. (2014). Blended learning in higher education: Institutional adoption and implementation. Computers & Education, 75, 185-195. doi:10.1016/j.compedu.2014.02.011 Thai, N. T. T., De Wever, B., & Valcke, M. (2017). The impact of a flipped classroom design on learning performance in higher education: Looking for the best «blend» of lectures and guiding questions with feedback. Computers & Education, 107, 113-126. doi:10.1016/j.compedu.2017.01.003 Chen, Y., Wang, Y., Kinshuk, & Chen, N.-S. (2014). Is FLIP enough? Or