This systematic review analyzed the role of microlearning in basic education, identifying the most widely used Digital Information and Communication Technologies, relevant learning theories, and the role of social technologies from a Science, Technology, Society, and Environment (STSE) perspective. Following PRISMA 2020, searches were conducted in Web of Science, Scopus, ERIC, and IEEE Xplore databases. Studies on microlearning were selected based on previously defined eligibility criteria. The review process in Rayyan involved deduplication, screening, and full-text analysis. Data were qualitatively analyzed using content analysis, and methodological quality was assessed with CASP and the Downs and Black. The findings highlight that microlearning, integrated with digital tools such as online platforms, mobile apps, and short videos, significantly enhances student motivation, performance, and interaction; content in short modules facilitates knowledge retention and connects concepts to real-life situations. Promising trends include mobile technologies and gamification, which foster active, meaningful learning. Grounded in theories like Self-Determination, Constructionism, and Constructivism, microlearning personalizes teaching and promotes engagement, critical thinking, and accessibility, contributing to inclusive and sustainable education. From a STSE perspective, social technologies enhance autonomy, social interaction, and ethical–environmental awareness. In Brazil, further research on digital platforms and gamified strategies is needed to drive innovative educational practices.

Estimating foliar damage is essential in agricultural processes to provide proper crop management, such as monitoring the defoliation level to take preventive actions. Furthermore, it is helpful to avoid the reduction of plant energy production, nutrition decrement, and consequently, the reduction of the final production of the crop and economic losses. In this sense, numerous proposals support the defoliation estimate task, ranging from traditional methodologies to computational solutions. However, subjectivity characteristics, reproducibility limitations, and imprecise results persist. Then, these circumstances justify the search for new solutions, especially in defoliation assessments. The main goal of this paper consists of developing an automatic method to estimate the percentage of damaged leaf areas consumed by insects. As a novelty, our method provides high precision in calculating defoliation severity caused by insect predation on the leaves of various plant species and works effectively to estimate leaf loss in leaves with border damage. We describe our method and evaluate its performance concerning 12 different plant species. Our experimental results demonstrate high accuracy in the determination of leaf area loss with a correlation coefficient superior to 0.84 for apple, blueberry, cherry, corn, grape, bell pepper, potato, raspberry, soybean, and strawberry leaves, and mean absolute error (MAE) less than 4% in defoliation levels up to 54% in soybean, strawberry, potato, and corn leaves. In addition, the method maintains a mean error of less than 50%, even for severe defoliation levels up to 99%.

Objective. The objective of this investigation was to verify the possibilities and potentialities of the use of active methodologies (AM), with a focus on rotation by stations, in Youth and Adult Education (YAE). The study also aimed to suggest AM as a proposal that collaborates with quality in teaching-learning and can contribute to students becoming autonomous subjects. Since it is an audience that needs more attention from researchers in the area of education, from this the practice in question was carried out in a six-class municipal school with 112 students in the center-west of Goiás. The class chosen for the practice has 28 students enrolled, and two are from Inclusive Education. Methodology. In the data collection, we used questionnaires, and the data collected were analyzed in a discursive way. For this research, we used a qualitative approach of the descriptive type and documental analysis of public policies. Conclusions. It is concluded that the applied practice must gradually be inserted into the education of young people and adults, collaborating with the student to facilitate learning and with the teacher, who is always looking for new ways to meet your student.

In stereo vision field, image processing techniques are used to increase the robustness of some types of solutions, especially those involved in real-world applications. With the objective to improve raw disparity maps, we investigated strategies of how to reduce the error measurement between a map and its correspondent ground truth. In this paper, we propose a simple but an effective technique, named as segment consistency check (SCC), to adjust a disparity map in a more appropriate configuration. The SCC method is organized into three main steps: segmentation process, statistical analysis, and by using adaptive support window. Experiment results show that the proposed method is comparable with other postprocessing strategies, in some cases with better results. Furthermore, through a qualitative evaluation, it is possible to note that the SCC method reaches significant results, especially in retaining object shapes, in maintaining the regularity of disparity in uniformed areas, and to preserve discontinuities.