User Experiences Around Sentiment Analyses, Facilitating Workplace Learning

User acceptance is key for the adoption of a new technology. In this work we experiment with a novel service for tutors in workplace learning settings. Sentiment analysis is a way to extract feelings and emotions from a text. In a learning setting such a sentiment analysis can be part of learning analytics. It has the potential to foster the understanding of emotions in shared discussions in learning environments, detect group dynamics as well as the impact of certain topics on learners’ sentiments. However, sentiment analysis presents some challenges too, as lived experiences, expectations and ultimately acceptance of this technology varies greatly and can become barriers to adoption. In order to design a system for learning analytics accepted by tutors we experimented with proof-of-concept prototypes and received valuable feedback from tutors regarding the usefulness of the overall sentiment analysis as well as certain features. The qualitative feedback confirms the overall interest of tutors in sentiment analysis and gives important hints towards more detailed analytical elements.