This project aims to develop STEM students' and academic staff's competences in using advanced technologies (like Artificial Intelligence and Machine Learning) in processing the information provided by Big Data (open source) and to facilitate an exchange of experience and good practices to the academic staff regarding new methods of teaching and learning that will be used during post-pandemic period.
There are sets of open source Big Data about the environment pollution and climate change. Processing these data, students and academic staff will become more aware, more sensitive to the environmental issues, in the context of existing climate change and will improve their green competences.
The project partners are from complementary fields and are led by the same needs, to improve their human resource's (both students and staff) competences and to increase the employability of own graduates, contributing with higher taxes to the development of their local communities.
These collections of big data represent a perfect environment for the new Artificial Intelligence applications, and change the way that we have experienced innovation. It is necessary for students and academic staff to develop their skills in using advanced technologies to process and use this information. Into this project, the team plans to address to the following needs:
1. At individual level - developing digital, green and STEM competences (for the students at Science and Engineering faculties) - need of training in new methods of teaching and learning adapted to the post-pandemic time (for the academic staff) - applying "advanced technologies" in scientific research (for the academic staff)
2. At Institutional level: - increasing graduates' degree of professional insertion on the labor market by their training in using advanced technologies - increasing students' degree of satisfaction by improving the quality of educational act given by academic staff -increasing the number of published scientific papers and number of multidisciplinary research projects
3. At Community level: - development of some environmental strategies by the local decision makers based on some information given by the processing existing data - community development based on the collecting higher taxes from the highly skilled graduates' salaries and slowing the rate of labor migration of the graduates from higher education in other more developed European regions - attracting in their region of some companies that need a highly skilled workforce
Beneficiaries:
-direct beneficiaries: target group (40 students, 10 academic staff), team of project implementation
-indirect beneficiaries: other students and academic staff from the partner universities where will be implemented project results and will use them, research community where will be disseminated some of the project results, mass-media that will communicate to the local community about the benefits of this project (increasing the employability of the high skilled graduates in advanced technologies, information about processing data related to the environment protection), partner universities (will have more satisfied academic staff and students, more published papers, more multidisciplinary projects, more international relations), companies (will find easier highly skilled workforce), community (will decrease the migration process of young people).