Abstract
Development tools have an impact on software engineers' productivity and quality of software construction. We believe that it is crucial to teach future software engineers how to exploit integrated development environment functionality, if we want to encourage the effective application of software development principles and practices. Our research shows that recommender systems can be deployed to improve integrated development environment knowledge of computer science students by automatically suggesting new and useful commands, such as buttons and shortcuts that execute different functions. While previous work focused on optimizing the algorithmic predictive capability of a recommender to identify the commands that the users will eventually use, we have addressed a set of research questions related to the overall acceptance of a complete recommender system in a real-life setting. The evaluation results show that a command recommender system can be well accepted by computer science students. In particular, when students are supported by such a system, they use a considerably larger set of commands available in their development environment. Moreover, the results show that the highest acceptance rate and the usefulness score were achieved by a non-personalized, popularity-based algorithm, while the most novel commands were suggested by a context-aware algorithm.