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Contribution This study reveals that the programming paradigm is relevant to obtain advanced programming skills. Background Parallel computing has become mandatory for computer science students. The increasing amount of computational resources required by emerging applications need experienced programmers that fully exploit hardware resources. However, the hardware platforms and programming languages to leverage them evolve at a dizzying pace, making very challenging for students the successful learning of the continuously changing high‐performance computing concepts. Research Questions (a) Is the learning curve of the programming language too steep to begin learning parallel programming fundamentals? (b) Are emergent learning methodologies making even more difficult to learn parallel programming in general? Methodology It is analyzed the main challenges for succeeding in parallel programming courses at the undergraduate level in two different learning modalities, namely on‐campus and online. It is analyzed the main tools available within a learning management system, showing their impact on online studies. Findings Our results reveal that the steep learning curve for parallel programming is one of the main barriers to student success, leading to an early drop out of the subject. On‐campus studies mitigate this problem through a close relationship between students and educators. Online studies, however, do not have this tight relationship by its definition.

The constant innovation in new technologies and the increase in the use of computing devices in different areas of the society have contributed to a digital transformation in almost every sector. This digital transformation has also reached the world of education, making it possible for members of the educational community to adopt Learning Management Systems (LMS), where the digital contents replacing the traditional textbooks are exploited and managed. This article aims to study the relationship between the type of computing device from which students access the LMS and how affects their performance. To achieve this, the LMS accesses of students in a school comprising from elementary to bachelor’s degree stages have been monitored by means of different computing devices acting as sensors to gather data such as the type of device and operating system used by the students.The main conclusion is that students who access the LMS improve significantly their performance and that the type of device and the operating system has an influence in the number of passed subjects. Moreover, a predictive model has been generated to predict the number of passed subjects according to these factors, showing promising results.