User Interface Design of Humanoid Robot at Library: Case of Chemnitz University of Technology

The university library is one of the key places for students at higher education institutions. Some universities support their students with their literature search and research with humanoid robots. The Chemnitz University of Technology (CUT) is one of pioneer universities where a humanoid robot will assist at the university library. This paper describes user interface requirement and its programming, testing and implementation of humanoid robot at the university library. The programmed humanoid robot should support students and visitors with useful guidance and hints in finding materials they need for their research and study. For programming of the robot, the programming language Python was used and the implementation was tested with limited number of users due to the pandemic situation

Evaluation of Python Error Message Interpretation: Study on Students with Different Levels of Programming Experience

Error messages are a helpful tool for everyone interested in learning a programming language. Even after learning the language, novice and experienced programmers alike, have to interact with an error message one way or another. However, there is no single programming language that is usedacross all platforms and systems, so the programmers have to write programs in many different languages. If the programming languages have similar structures, working with a new language is relatively easy. We have asked the question, whether the same effect could be observed in case of error messages. We designed an online survey which was conducted internationally to measure whether the general experience of programmers from any programming language influences the programmer’s ability to correct python error message. The survey was aimed at students who have some experience with programming. We find in comparison with novices, on average the experiencedprogrammers find and fix an error in the code given the sameerror message with its corresponding code snippet. Additionally,we see correlations between the average of correctly fixed errorsand number of programming languages that the participants hadexperience with, as well as their chosen major and their age