Universities play an essential role in preparing human resources for the industry of the future. By providing the proper knowledge, they can ensure that graduates will be able to adapt to the ever-changing industrial sector. However, to achieve this, the courses provided by academia must cover the current and future industrial needs by considering the trends in scientific research and emerging technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and Edge Computing (EC). This work presents the survey results conducted among academics to assess the current state of university courses, regarding the level of knowledge and skills provided to students about the Internet of Things, Artificial Intelligence, and Edge Computing. The novelty of the work is that (a) the research was carried out in several European countries, (b) the current curricula of universities from different countries were analyzed, and (c) the results present the teachers’ perspective. To conduct the research, the analysis of the relevant literature took place initially to explore the issues of the presented subject, which will increasingly concern the industry in the near future. Based on the literature review results and analysis of the universities’ curricula involved in this study, a questionnaire was prepared and shared with academics. The outcomes of the analysis reveal the areas that require more attention from scholars and possibly modernization of curricula.

Knowledge and skills in the field of Artificial Intelligence (AI), Internet of Things (IoT), and Edge Computing (EC) are more and more important for industry. Therefore, it is crucial to know what current students and future employees can offer to the industry. University students develop their knowledge and skills to support the industry in implementing modern technologies in the future. It can be expected that the first source of information for students will be lectures and other activities at the university. However, they may obtain knowledge from other sources. This article presents the results of research conducted among students assessing their own knowledge and skills in the field of IoT, AI, and EC. The research was preceded by an analysis of curricula at selected universities in terms of topics related to AI, IoT, and EC. Based on the results of the analysis, survey questions were prepared. The developed questionnaire was made available to students. The research sample for the survey participants was 563 students. The results obtained were analyzed. The results of the analysis show which issues are better known to students and which are worse. The information presented in this paper can be a source of information for the industry that can assess the competences that are or will be available on the labor market in the near future. Additionally, universities can obtain information on the areas in which there are competency gaps and which methods of teaching AI, IoT, and EC are better perceived by students.

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In face-to-face learning environments, instructors (sub)consciously measure student engagement to obtain immediate feedback regarding the training they are leading. This constant monitoring process enables instructors to dynamically adapt the training activities according to the perceived student reactions, which aims to keep them engaged in the learning process. However, when shifting from face-to-face to synchronous virtual learning environments (VLEs), assessing to what extent students are engaged to the training process during the lecture has become a challenging and arduous task. Typical indicators such as students’ faces, gestural poses, or even hearing their voice can be easily masked by the intrinsic nature of the virtual domain (e.g., cameras and microphones can be turned off). The purpose of this paper is to propose a methodology and its associated model to measure student engagement in VLEs that can be obtained from the systematic analysis of more than 30 types of digital interactions and events during a synchronous lesson. To validate the feasibility of this approach, a software prototype has been implemented to measure student engagement in two different learning activities in a synchronous learning session: a masterclass and a hands-on session. The obtained results aim to help those instructors who feel that the connection with their students has weakened due to the virtuality of the learning environment.

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