Introduction: The article presents the results of a research project the aim of which was to describe the level of kindergarten teachers’ work with educational objectives in connection with the application of a differentiated curriculum for the development of gifted children.
Methods: The research tool was a questionnaire in which the teachers selected one of three answers possible and matched their pedagogical activities in kindergarten the most. 345 teachers from kindergartens in the Czech Republic took part in the research. Data was processed using computer software SPSS.
Results: It was discovered that most of them can differentiate their instructions, however, at least a half of them do not respect the rules of inclusive education and their instructions result in an unwanted labelling of the gifted children. We have also proved that the level of the teachers’ work with the educational objectives is positively influenced by their longer than 10 years’ experience, work with heterogeneous class age-wise, and their having attended a seminar focused on the topic of giftedness.
Discussion: The discussion focuses on the description of variables affecting the level of work with educational objectives in connection with the application of a differentiated curriculum for the development of gifted children.
Limitations: The limitation is the simplification of the pedagogical reality into 3 possible answers and the artificial metrization of this data. Another problem was that our questionnaire was focused only on selected aspects of pedagogical work with gifted preschoolers, which were related to the curriculum modification and inclusive education. Furthermore, despite the big amount of validly filled in questionnaires (345) the research cannot be considered to be large area survey and the results cannot be generalized.
Conclusions: Gifted children should have the maximal space for the development of their own potential. It is also necessary to increase the teachers’ skills to apply the differentiated curriculum with the features of inclusive education in order to develop the giftedness of all the children as much as possible. One of the possibilities is the kindergarten teachers’ attendance to educational events on the topic of giftedness, which is one of the variables which significantly influence the quality of their work.
Aim of this paper is to present the remote sensing-based systems of forest health assessment in the Czech Republic and Slovakia, and to analyse both their strengths and weaknesses. Nationwide assessment of forest health in the Czech Republic is based on the interpretation of Sentinel–2 satellite data using novel approaches for cloud-free image synthesis based on all available satellite observations. A predictive statistical model to yield time series of leaf area index (LAI) from satellite observations is developed above extensive in-situ data, including LAI and forest defoliation assessment. Forest health is evaluated for each pixel from yearly changes of forest LAI, while the country-wise assessment of the health status is performed at the cadastral level. Methodology developed for Slovakia is based on a two-phase regression sampling. The first phase of the procedure provides an initial fast estimate of forest damage using only satellite observations (visible and infrared channels from Landsat or Sentinel–2 systems). The second phase refines the result of the first phase using data from a ground damage assessment (site-level defoliation from ICP Forests database). Resulting forest health assessment over the whole forest area is presented in 10 defoliation classes. The Czech Republic shows 1.6% of heavily damaged forests, 12.5% of damaged forests, 79.2% of forests with stable conditions, 6.3% of regenerated forests and 0.4% of strongly regenerated forests. In Slovakia, the total share of damaged stands (i. e. with defoliation higher than 40%) increased from 6 – 8% in 2003 – 2011 to 13 – 15% in 2012 – 2017. Both methodologies conduct nationwide assessment of forest health status in a fast and automatized way with high accuracy and minimal costs. The weaknesses are, for example, a high computational demands for production cloud free mosaics, inability to identify initial phases of forest health decline, exclusion of stands older than 80 years (in the Czech Republic) and inability to differentiate between harvested and severely damaged stands (in Slovakia). Finally, the paper outlines future development of both methodologies.