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- Author or Editor: Tímea Kocsis x
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In the present explorative study, different time-series analysis methods, such as moving average, deterministic methods (linear trend with seasonality), and non-parametric Mann–Kendall trend test, were applied to monthly precipitation data from January 1871 to December 2014, with the aim of comparing the results of these methods and detecting the signs of climate change. The data set was provided by the University of Pannonia, and it contains monthly precipitation data of 144 years of measurements (1,728 data points) from the Keszthely Meteorological Station. This data set is special because few stations in Hungary can provide such long and continuous measurements with detailed historical background. The results of the research can provide insight into the signs of climate change in the past for the region of West Balaton. Parametric methods (linear trend and t-test for slope) for analyzing time series are the simplest ones to obtain insight into the changes in a variable over time. These methods have a requirement for normal distribution of the residuals that can be a limitation for their application. Non-parametric methods are distribution-free and investigators can get a more sophisticated view of the variable tendencies in time series.
Higher educational dropout is a major education policy issue that can be influenced by several factors. In addition to the family background, it is necessary to mention the motivation for further education as an individual factor which has a complex effect. Another possible individual cause can be the attractiveness of the labor market. Due to the ratio of students dropping out of higher education in Hungary, it can be suspected that students’ intensive work contributes to weaker learning outcomes, resulting dropout finally. In this context, however, the decisive role of the different work values and working attitudes is also unquestionable. Other institutional factors such as the country of the institution or the type of financing of the training cannot be ignored as well. Accordingly, in our research, we investigated individual, institutional, and sociodemographic factors affecting persistence through the TESCEE 2015 (N = 2015) database. Factors influencing persistence were measured by linear regression analysis with the application of two-sample t-test to measure the between-group differences. Regarding socio-demographic factors, the father’s educational level showed a significant impact on a negative while the mother’s employment in a positive way, furthermore, gender presented a trend effect. Institutional factors by themselves are not remarkable; however, some individual factor can increase their impact. At the individual level, the significant effect of career office membership and work values could be detected. Our results can contribute to the recognition of the relationships behind the high ratio of dropout and the identification of factors that can promote persistence, which can support to reduce the dropout ratio at a national and international level.
Higher educational dropout is a significant area of education policy in Hungary. First, the proportion of graduated higher educational students is low when compared to the OECD average, which may be caused by dropout from higher educational courses. On the other hand, although the phenomenon of dropout has been closely investigated in several international research papers, the methodology used to determine the dropout ratio is unsatisfactory, mainly due to the lack of expert consensus. As a consequence, we do not have precise data regarding the dropout ratios, which make investigations related to this area even more necessary. The aim of this study was to measure the possible reasons for delayed graduation and dropout, and it was carried out as a qualitative study based on existing theories. In our investigation, the role of the sociocultural background; the years prior to the time spent in higher education; and the motivation of the choice of institution, employment, sports, and social activities were measured through an analysis of seven individual interviews and one focus group conversation involving 10 participants based on a semi-structured interview methodology. The causes of delayed graduation and dropout, which are more difficult to observe, are an inappropriately chosen institution and/or course, employment while studying intensively in a higher education institution, competitive sport and friends with a negative attitude toward learning. Our analysis provides a stable basis for a wider questionnaire-based investigation on a representative sample and its main units have been developed according to the research blocks of the interview analysis.