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.

This paper focuses on problematic of use of association rules in exploring consumer behavior and presents selected results of applied data analyses on data collected via questionnaire survey on a sample of 1127 Czech respondents with structure close to representative sample of population the Czech Republic. The questionnaire survey deals with problematic of shopping for meat products. The objective was to explore possibilities of less frequently used data-mining techniques in processing of customer preference. For the data analyses, two methods for generating association rules are used: Apriori algorithm and FP-grow algorithm. Both of them were executed in Weka software. The Apriori algorithm seemed to be a better tool, because it has provided finer data, due to the fact that FP-growth algorithm needed reduction of preference scale to only two extreme values, because the input data must be binary. For consumer preferences we also calculated their means. This paper explores the different preferences and expectations of what customers’ favorite outlet should provide, and offer. Customers based on the type of their outlet loyalty were divided into five segments and further explored in more detail. Some of the found best association rules suggest similar patterns across the whole sample, e.g. the results suggest that the respondents for whom a quality of merchandise is a very important factor typically also base their outlet selection on freshness of products. This finding applies to all types of retail loyalty categores. Other rules seem to indicate a behavior more specific for a particular segment of customers. The results suggest that application of association rules in customer research can provide more insight and can be a good supplementary analysis for consumer data exploration when Likert scales were used.

Decreasing number of secondary school graduates means that, for college, it becomes more difficult to fulfill guide number of newly admitted students. In order to maintain an optimum number of registered students, the Faculty of Business and Economics decided to support activities which increase the interest of its accredited programs.Potential students should be treated as customers to whom we want to offer a product – knowledge, skills and competencies. Promoting study programs PEF MENDELU is handled by PR department in collaboration with several students.Availability of resources for promotion is limited. It is crucial to deciding how to deal with these sources. By creating a system for monitoring and decision support, we provide all interested collaborators tool to improve decision-making processes.The system itself will be built on the tools of Business Intelligence (BI) that can observe consumer trends, identify customer segments and other important information. The BI emphasizes the use of OLAP technology for data processing. In the collected data about students is hidden a large amount of information that can be obtained using techniques such as knowledge discovery in databases.This article aims to describe the methodology for solving problems and show the application, which result in support of decision-making processes in the propagation PEF MENDELU, which should also lead to the efficiency of spending on this activity.

The aim of the study was to determine the growth of explosive strength in both lower extremities in ice hockey players in the course of several years training cycles (later as RTC). Measurement was carried out at the beginning of the competitive season, and at the end of competitive and training season in years 2015-2017. To compare findings among age categories in each particular year. The level of explosive skills has been diagnosed by force plate Bertec in the laboratory of the Faculty of Sport Studies in Brno. The survey was carried out in groups of ice hockey players