Data journalism and more generally, data-based communication represents a rapidly growing experience in higher educational courses and in professional training in European countries, since the media and news systems are more and more appreciating the use of data, in a systematic and scientific way, in the production of journalistic and communication content. WEBJOU project aims to promote knowledge exchange and multidisciplinary teaching and learning innovation in the Western Balkan reality, for what concerns providing all knowledge and skills, in particular from fields such as data science, statistics, visualization and communication, necessary to fruitfully operate in the data journalism and data communication frameworks. The WEBJOU Project has the following four major goals: 1. The definition of the profile of data journalism and data communication for the higher education (ISCED-6) with reference to the Wester Balkan higher education system. 2. The design of 6 modular courses, which can be composed to realize different training paths (Big Data, Data Visualization, statistical analysis, Geospatial representations, Story telling, Legislation on data property in EU (GDPR)). The courses will be compliant with a competences assessment and qualification system based on the ECTS credit points. 3. The realization of 7 first course/bachelor's (ISCED-6) in Data journalism, one for each partecipating HE, tailored for the Wester Balkan context with particular reference to the Albanian and Kosovan higher education system. 4. The development of an online platform. All the resources and teaching aids will be available to the public free of charge through open licenses. (Open Educational Resources -OER) To evaluate these objectives, WEBJOU will test the courses with 70 students with particular reference to females (50). Additionally, both academic and administrative staff will be trained both on the courses and on the learning platform.


Contact person:  Prof. dr Uglješa Marjanović
Period of realization: 2023 – 2025
ID: ERASMUS+ KA2 - 101083122