Understanding how software works and writing a program are currently frequent requirements when hiring employees. The complexity of learning programming often results in educational failures, student frustration and lack of motivation, because different students prefer different learning paths. Although e-learning courses have led to many improvements in the methodology and the supporting technology for more effective programming learning, misunderstanding of programming principles is one of the main reasons for students leaving school early. Universities face a challenging task: how to harmonise students’ education, focusing on advanced knowledge in the development of software applications, with students’ education in cases where writing code is a new skill. The article proposes a conceptual framework focused on the comprehensive training of future programmers using microlearning and automatic evaluation of source codes to achieve immediate feedback for students. This framework is designed to involve students in the software development of virtual learning environment software that will provide their education, thus ensuring the sustainability of the environment in line with modern development trends. The paper’s final part is devoted to verifying the contribution of the presented elements through quantitative research on the introductory parts of the framework. It turned out that although the application of interactive features did not lead to significant measurable progress during the first semester of study, it significantly improved the results of students in subsequent courses focused on advanced programming.

During pregnancy, an array of changes occurs in women body to enable the growth and development of the future baby and the consequent delivery. These changes are reflected in the range of motion of trunk, pelvis, lower limbs and other body segments, affect the locomotion and some of these changes may persist to the postpartum period. The aim of this study was to describe the changes affecting the gait during pregnancy and to determine the effect of tested footwear on kinematic gait characteristics during pregnancy as previous studies indicate that special orthopaedic insoles and footwear might be useful in prevention of the common musculoskeletal pain and discomfort related to pregnancy. Participants from the control group (n = 18), without any intervention, and the experimental group (n = 23), which was wearing the tested shoes, were measured at their 14, 28 and 37 gestational weeks and 28 weeks postpartum to capture the complete pregnancy-related changes in gait. The gait 3D kinematic data were obtained using Simi Motion System. The differences between the control and experimental group at the first data collection session in most of the analysed variables, as well as relatively high standard deviations of analysed variables indicate large individual differences in the gait pattern. The effect of tested footwear on kinematic gait pattern changes may be explained by its preventive effect against the foot arches falling. In the control group, changes associated previously with the foot arches falling and hindfoot hyperpronation were observed during advanced phases of pregnancy and postpartum, e.g. increase in knee flexion or increase in spinal curvature. For the comprehensive evaluation of the tested footwear on pregnancy gait pattern, future studies combining the kinematic and dynamic plantographic methods are needed.

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, the scientific journal of the Mendel University in Brno, Czech Republic

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, the scientific journal of the Mendel University in Brno, Czech Republic

This paper summarizes results of the research project “Application of modern methods to data processing in the field of marketing research” which was solved at the Department of Informatics, Faculty of Business and Economics of Mendel University in Brno. The most of these results were presented at international conferences. It describes the use of knowledge discovery techniques on data from marketing research of consumers’ behaviour. The paper deals with issues of classification, cluster analysis, correlation and association rules. For classification there were used various algorithms: multi-layer perceptron neural network, self-organizing (Kohonen’s) maps, bayesian networks and generation of a decision tree. Beside Kohonen’s maps, which were tested in MATLAB software, all classification methods were tested in Weka software. In order to find clusters of the methods K-means, Expectation-Maximization, DBSCAN Weka was also used as software for clustering. Correlation analysis was done based on statistical approach. Generation of association rules was achieved by use of Apriori and the FP-growth algorithm in Weka. The paper describes above mentioned methods and shows achieved results of exploring data from marketing research on consumers’ behaviour. This article discusses the suitability of these methods usage on such data sets. It also suggests further research possibilities of knowledge discovery on consumers’ behaviour.

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, the scientific journal of the Mendel University in Brno, Czech Republic