STUDENTS’ MOTIVATION TO ATTEND PHYSICAL EDUCATION CLASSES IN UNIVERSITIES OF UKRAINE

The article is dedicated to the research of priority motives according to attending “Physical education” classes by I and II year students from universities of Ukraine. The goal of the research is to determine the ratings of students’ motivation towards attending physical education classes in the universities in Ukraine. The methods of research are analysis and generalization of scientific methodologic literature data, sociologic methods (questionnaire) and mathematical statistics methods. The questionnaire was answered by 363 students from 4 Ukrainian universities. Among them were 170 males and 193 females. The main results of the research are as follows. It was determined the general structure of students’ motivation and value orientation according attending physical education classes by each university particularly. There was performed comparable analysis of significance ranking of the motives to attend physical education classes and also generalized differences between females and males in the choice of motivation priority. It was determined that 57,9% of students that have been taking part in the questionnaire, think that priority motive to attend physical education classes is to get credits from the course, while body strengthening has second priority place (47,9%). As males (46,5%) so females (67,9%) believe the most essential motive is to get credits from the course “Physical education” and body strengthening (males – 38,8%, females – 56,6%). The third place among males got the motive to improve physical efficiency (26,5%), among females – the desire to get fit (35,2%). Conclusions: The results we have got testify the importance to increase motivation level to attend physical education lessons.

Significance ranking of parameters impacting construction labour productivity

PurposeConstruction labour productivity is often influenced by variations in work conditions and management effectiveness. It is substantially important to understand the nature and extent to which individual parameters affect productivity. The purpose of this paper is to focus on providing insight on parameters that affect daily job‐site labour productivity by investigating their relative significance and influence on work output.Design/methodology/approachThe methodology is based on the illustration and use of three different data analysis techniques to rank parameters that affect a certain process. These techniques include Fuzzy Subtractive Clustering, Neural Network Modelling and Stepwise Variable Selection Procedure. The first one belongs to inferential statistics, while the other two are artificial intelligence based techniques. The collection of field information, spanning over a time period of ten months, comprised of daily real time observations of job‐site operations, work progress information collected from project managers and supervisors by using customized forms, and daily weather condition recorded through internet sources. Nine parameters are considered in the study presented in this paper. The data on these parameters is examined and their relative influence and contribution in productivity estimates are assessed. The approach was to consider a limited set of parameters relating to daily job‐site productivity. The methodology presented in this paper provides insight on the relative impact of parameters, affecting labour productivity on short term or daily basis. The results based on each of the three methods are analyzed and transformed into a final ranking of parameters.FindingsThe three most important parameters are identified in the same order by the fuzzy logic and neural networks methods. Regression analysis, however, provided somewhat different results.Originality/valueThis research investigates the contribution of a set of parameters towards the variations in daily job‐site labour productivity. For practitioners such as site engineers, this is of practical importance for making daily work plans. On the other hand, the structured approach presented to perform significance ranking of parameters relevant to an engineering process, may also be of interest to other researchers and practitioners.

Application of the Morris method for screening the influential parameters of fuzzy controllers applied to wastewater treatment plants

In this paper, we evaluate the application of a sensitivity analysis to help fine-tuning a fuzzy controller for a biological nitrogen and phosphorus removal (BNPR) plant. The Morris Screening method is proposed and evaluated as a prior step to obtain the parameter significance ranking. First, an iterative procedure has been performed in order to find out the proper repetition number of the elementary effects (r) of the method. The optimal repetition number found in this study (r = 60) is in direct contrast to previous applications of the Morris method, which usually use low repetition number, e.g. r = 10 ∼ 20. Working with a non-proper repetition number (r) could lead to Type I error (identifying a not-important factor as significant (false positive)) as well as Type II error (identifying an important factor as not significant (false negative)), hence emphasizing the importance of finding the optimal repetition number for each study in question. With the proper r found, the Morris Screening helped identify the parameter significance ranking, thereby facilitating the calibration of fuzzy controllers, which contain many parameters that need to be adjusted for different wastewater treatment plant (WWTP) applications.