Emotions recognition in synchronic textual CSCL situations
Germán Lescano, Rosanna Costaguta, Analı́a Amandi · International Journal of Data Mining Modelling and Management · 2022
Computer-supported collaborative learning (CSCL) is a useful practice to teach learners working in groups and to acquire collaborative skills. To evaluate the collaborative process can be heavy for teachers because it implies to analyse a lot of interactions. One issue to consider is socio-affective interactions due to their influence in the learning process. In this work, we propose an approach to recognise affective states in synchronic textual CSCL situations of students that speak Spanish. Through experimentation, we analyse emotions manifested by university students of computer sciences when they worked in groups in these situations and we evaluated the proposed approach using tools and libraries available in the market to make a sentiment analysis. Results obtained are promising. Providing CSCL environments with a tool to recognise socio-affective interactions can be useful in order to help teachers evaluate this dimension of the collaborative process.