## 2 Materials and Methods  
The case study analyzed in this paper concerns the evaluation of users' engagement in interacting with a virtual learning environment developed during a European project for education purposes. An approach based on design science research (DSR) was followed taking inspiration from the one proposed by [PERSON] et al [19]. Our DSR approach to the issue was as follows: (1) problem statement: self-reports are not sufficient in giving a complete evaluation of users' feedback; (2) hypothesis: an FER methodology can make more thorough the users' feedback analysis; (3) development: an SVM(support vector machine) method can classify the level of user engagement based on facial analysis; (4) evaluation: assessment of the proposed solution on a group of sample users during the navigation in a virtual learning environment. A scheme of the followed DSR approach is shown in Figure 1.  
A sample of 12 participants (six males and six females) were asked to navigate the virtual learning environment; the participants (students, postdoctoral students, PhD students, and researchers) with an age from 20 to 30 years and without any payment for their participation, took part in our research. During the navigation, the participants were equipped with the Intel(r) RealSense(tm) SR300 structured-light depth camera; this way, learners' body posture and facial expressions were monitored and recorded in real time in the form of depth maps (Figure 2). During the experience, two raters evaluated and annotated the emotional response of the user. Immediately after the virtual learning experience, the participants were asked to fill in the UES (user engagement scale) questionnaire [20]. The two raters analyzed the 3D videos and selected frames of interest according to their annotations during the users' experience; this was necessary to construct the dataset for the automatic expression classification. The aim of involving facial expressions in the monitoring of emotional activation was to measure the involvement and the engagement of sample users interacting with the virtual environment with a real-time acquisition of facial expressions that are supposed to be spontaneous. The virtual learning environment involved in this study was developed as a supporting tool for educational purposes within the context of the Erasmus+ project \"EVA--A European Entrepreneuring VET Model and Assessment Framework for Ethnic Minorities\". The virtual environment was created using 360-degree computer-generated panorama images produced using a 3D computer graphics software toolset. Blender was applied because it is one of the best free and open-source alternatives  
Figure 1: Schematization of design science research (DSR) approach. Figure 2: Example of experimental set-up. currently available on the market. Thanks to its Cycles Render Engine which allows generating ray-tracing production-quality images, it was possible to obtain the best photorealism possible and enhance the immersivity and effectiveness of the images. Then, different high-quality, royalty-free 3D models, commonly available on the internet on repositories such as Google SketchUP Repository, were used to assemble the virtual environment. Then, we employed Google VR (virtual reality) view, which allows embedding 360-degree VR media into websites. It is based on WebGL technology, allowing our virtual environment to be effectively cross-platform. Our virtual environment was a 3D simulator, hosted on a website, in which the user navigates multiple rooms in order to learn the required paths to become an entrepreneur. The 3D simulator is composed of five rooms projecting the learner in five different scenarios a starter entrepreneur could have to face: business creation, business starting, financial issues, marketing and communication, and networking. In Figure 3, it is possible to observe one of the five rooms, the scenario of business starting: a virtual shop under construction.