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The digitalization of education is a continuously developing process, aimed at the use of information and communication technologies. However, engineering education utilizes several forms of learning, with laboratory experiments being one of them. The use of digital learning materials (DLM) in labs is still limited due to numerous existing factors. This study investigates students' acceptance of using DLM during laboratory exercises in three universities located in Turkey, Poland, and Bulgaria. A questionnaire was prepared, and a survey was conducted among 625 learners. They were divided into eight categories, based on their engineering area and country. The survey results demonstrate that there is a strong correlation between the students' opinion on DLM and the use of DLM by their lab instructors, which means that their acceptance could be increased if more DLM are integrated in lab courses. The analysis of the questionnaire results also showed that there is a significant difference in the students' opinion on DLM, depending on the engineering area. Students of Food, Chemistry, and Electrical engineering rated the use of DLM quite high (above 4.0 out of 5), followed by the Civil engineering students with average results between 3.5 and 4.0. Respondents involved in Textile, Bio, and Machine engineering were the most skeptical (<3.5). Furthermore, their opinions covered a wide range from "Strongly disagree" to "Strongly agree."

In this paper are presented a new extended methodology and tools for providing electrical engineering education in a distant form. It was used by two Bulgarian universities, in order to adapt their Electrical engineering classes to the COVID-19 situation. The methodology includes several phases: needs analysis, preparation of educational materials, selection of teaching methods, increasing competencies and selection of assessment methods. In the results of the paper is presented the implementation of the methodology based on the EVEEE environment for electrical engineering equipment. At the end of the semester a questionnaire was conducted among the students. The results about the students' opinion clearly indicate that engineering education should be implemented in a distant form only during emergency situations.

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The integration of information and communication technologies into agriculture lead to the development of precision agriculture. Nowadays it relies on Internet of Things devices, geospatial data, historical and real-time information, which has the potential to transform farming into smart farming. However the use of Big Data requires significantly different skills and knowledge, compared to what many farmers and agronomists possess, which is an obstacle for their effective use. This study aims to summarize and provide insight into the common methods used for data analysis in a wide variety of agricultural applications. Initially, the basic characteristics and sources of agricultural data are explained. Next, a review of the common data analysis methods (classification, clustering and regressions) is provided, containing information about the data sources used as well as the desired goal of the analysis. At the end of the paper, a summary is given on the applicability of data analysis methods depending on the desired goals.