Pilot case

CloudScape: Scalable and Personalized Teaching in Cloud Computing

Creating personalized exercises and grading tools for teaching mobile and cloud computing.
CloudScape: Scalable and Personalized Teaching in Cloud Computing

Pilot leader

Mario Di Francesco


School of Science


94 students


2017 – 2018


Is it possible to replace a skilled team of teaching assistants in assessing software projects on mobile application development and cloud computing? The goal of the CloudScape pilot was to answer this question by developing tools for automated assessment of student assignments. The pilot specifically targeted mobile application programming with Android in the context of modern cloud-based services. The outcome of CloudScape is a system that automatically assesses Android assignments by using industry-standard practices in mobile app testing. Students obtain detailed feedback just a few minutes after their submission. The system has been already been used for the Mobile Cloud Computing course (CS-E4100) in Fall 2017. The course had 115 students enrolled and included 4 Android assignments; the system automatically graded a total of 893 submissions. What did the student think about it? “Pretty cool”, “good job!”, and “great!” are among the comments received in the student feedback. The CloudScape pilot demonstrated how automated grading of mobile application programming is effective and scalable; therefore, it can be employed in large-scale courses, including massive online open courses.

Platforms and tools

  • A+
  • Appium
  • Android SDK/Emulator

Involved courses

CS-E4100  – Mobile Cloud Computing (5 ECTS)


Mario Di Francesco
School of Science, Department of Computer Science
Pilot leader

Daniel Bruzual
School of Science, Department of Computer Science
System developer and course assistant

Maria Lorena Montoya Freire
School of Science, Department of Computer Science
Teaching assistant

Manoj Kumar
System developer

Prasant Sukumar
System developer and editor

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