The design of multimedia teaching materials and the principles of their presentation to students strongly influence distance learning efficiency. The appropriate design of online educational multimedia content became especially important during the period of the COVID-19 crisis. This study presents a methodology for improving the efficiency of multimedia-based distance learning by reducing the cognitive load. Combining the segmentation principle with pauses and testing questions in the design of multimedia teaching materials has a positive influence on reducing the cognitive load in distance learning. Practice as an instructional element was more efficient if it was used between the multimedia educational segments than after the presentation of complete multimedia material. The obtained experimental results show an improvement in distance learning efficiency and an increase in the students’ quality of experience. The improvement of learning outcomes using the proposed methodology of multimedia segmentation combined with pauses and testing questions can be especially important for distance education in situations such as the COVID-19 pandemic.

This study investigates the application of Multi-Criteria Decision-Making (MCDM) techniques in fruit production, specifically focusing on the use of the interval fuzzy rough pivot pairwise relative criteria importance assessment (PIPRECIA) method for criteria evaluation. A total of 11 criteria were evaluated to rank various combinations of plum varieties and rootstocks. The criteria selected represent key aspects of plum production, including phenology, yield, physical fruit characteristics, and the chemical composition and quality of the fruit. Data for the study were collected through surveys of 17 experts and plum producers. The results indicated that the criteria related to overall yield and fruit weight were deemed the most significant, while those concerning the chemical composition and fruit quality were considered of lesser importance. The findings highlight the potential of the interval fuzzy rough PIPRECIA method in addressing both research and managerial challenges in fruit production. It is suggested that future research expand the application of this method to other geographical regions and agricultural sectors. Additionally, the development of accessible software tools featuring user-friendly interfaces could facilitate broader adoption of MCDM techniques in agricultural decision-making.

Feed costs represent a significant component of milk production expenses, making up a share of 50% or more of the total cost. The optimization of feed costs is important to achieve financial stability, competitiveness, and sustainability in dairy farming. Optimizing dairy rations not only improves economic efficiency but also plays a significant role in reducing the environmental impact of dairy farming. On the other hand, dairy rations need to meet the specific nutritional requirements of cattle to ensure their health, well-being, and maximum milk production. The formulation of an optimal dairy ration is not an easy task for farmers due to the many challenges they face in this process. This study presents an intuitive web-based tool called OPTIMILK that is used for the optimization of dairy rations using the Simplex method of linear programming. This tool enables farmers to efficiently find a least-cost ration considering the nutritional needs of dairy cows, feed availability and costs, and the nutritional composition of feed. The tool was created for a dairy farmers’ association in Bosnia and Herzegovina and made available to its members for free. After almost four years of operation, the tool’s usage was evaluated by analyzing the collected data. The results show that after an initial period of low activity, there was evidence of an increase in the level of use, which implies the gradual adoption of the tool in dairy farming practice.

Two types of economic effectiveness and two types of economic efficiency, as well as three types of indicators as nutritional quality criteria were used in this paper for ranking certain winter lettuce growing technologies. Four certain types of growing technologies of winter lettuce in greenhouses were ranked by two multi-attribute decision making methods. Results of ranking for both methods, SAW and TOPSIS are shown. Alternatives were ranked by three different scenarios with different weight coefficients. The type of growing technology with combination of mulching + agro textile is the best ranked one according both methods and all scenarios. The SAW method showed more sensitivity on weight coefficients changes than TOPSIS.