Artificial intelligence in the analysis of emotions of nursing students undergoing clinical simulation

Abstract

Objective: to assess nursing students’ emotions undergoing maternal-child clinical simulation. Methods: an observational study, carried out between June and July 2019. The Focus Group technique was used, with 28 nursing students, randomly distributed into three groups, with qualitative (Bardin technique) and quantitative data (Artificial Intelligence) analysis, to analyze emotions through facial expressions, tone of voice and description of speeches. Results: we defined two categories: “It was not easy, it was very stressful”; and “Very valuable experience”. In Artificial Intelligence, emotional distribution between face, voice and speech revealed a prevalence of negative valence, medium-high degree of passivity, medium power to control the situation and medium-high degree of obstruction in task accomplishment. Final considerations: this study revealed an oscillation between positive and negative emotions, and shows to the importance of recognizing them in the teaching-learning process in mother-child simulation.