Engagement Evaluation in a Virtual Learning Environment via Facial Expression Recognition and Self-Reports: A Preliminary Approach

• Main Authors: Elena Carlotta Olivetti, Maria Grazia Violante, Enrico Vezzetti, Federica Marcolin, Benoit Eynard
• Format: Article
• Language: English
• Published: MDPI AG 2019-12-01
• Series: Applied Sciences
• Subjects: virtual learning environment; student engagement; product life cycle; fer (facial expression recognition); self-reports
• Online Access: https://www.mdpi.com/2076-3417/10/1/314

Due to its versatility, virtual technology is being widely employed in different domains, from industry to amusement. The possibility to adopt this technology in early product/service design is going to bring positive effects such as the reduction of costs associated with the production of physical prototypes and the generation of a more effective knowledge of users’ feedback. This study proposes a preliminary methodology to evaluate users’ engagement in interacting with a virtual environment that consists of the integration between a self-report method (the user engagement scale questionnaire) and a method based on facial expression recognition. Results reported in this paper show that the two methodologies generate different types of knowledge which can be used to fit users’ needs and expectations. Even if focused on a specific case study, i.e., the evaluation of the engagement in a virtual learning environment, this paper aims to propose a methodology that can be applied to all kinds of virtual products.