A Robotics Course during COVID-19: Lessons Learned and Best Practices for Online Teaching beyond the Pandemic

Author:

Birk AndreasORCID,Dineva Evelina,Maurelli FrancescoORCID,Nabor Andreas

Abstract

The article describes observations from the online teaching of a robotics class during the COVID-19 pandemic caused by SARS-CoV-2, also known as the coronavirus. The changes in the course structure and in the provided material lead to an unexpected increase in the grade performance of the students. The article provides a description and an analysis of the effects and their possible causes. In addition to a grade-performance analysis, further data from a university-wide and from a course-specific survey are used. The analysis of the effects and their possible causes is furthermore discussed in relation to the educational research literature. Some evidence for the general findings is provided, which are of interest for online teaching or blended learning in general, respectively, for teaching in robotics and related areas. These include some evidence for the benefits of asynchronous online teaching and for the role of social interaction, which may happen in self-organized, smaller peer groups, even without the intervention of the instructor. The findings and the extensive pointers to the literature can also provide useful guidelines for instructors of robotics courses when considering the use of online or blended teaching in the future beyond the COVID-19 pandemic.

Funder

Jacobs Foundation

Publisher

MDPI AG

Subject

Artificial Intelligence,Control and Optimization,Mechanical Engineering

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