The contribution aims at determining the endogenous potential for a proposal for sustainability and potential development of tourist destinations located in the Czech border areas - Liberec region - that lag behind in rural development. Based on the results of the empirical research, according to optimal scaling the ASEB-C analysis is applied suggesting the LAC (Limits of Acceptable Change) planning system will improve sustainability and competitiveness of all LAU 1 (in the Liberec region) and of the specific touristic destinations. The potential of development in the Czech border areas is in the stagnation phase, due to the fear and (dis)embedded identity in some less developed border areas. It should be evident that even in the Czech rural border areas the potential of “growth of endogenous potentials seems feasible” in combination with an endogenous and exogenous model of regional rural development.
Today’s educational institutions are expected to create learning opportunities independent of time and place, to offer easily accessible learning environments and interpersonal communication opportunities. Accordingly, higher education institutions develop strategies to meet these expectations through teaching strategies, such as e-learning, blended learning, mobile learning, etc., by using teaching technologies. These new technology-based teaching strategies are mainly shaped by decision-makers in education. This study seeks to analyse the individual factors that affect learners’ mode of teaching and learning delivery preferences. In this study, blended and online learning is considered as preferences of learners’ mode of teaching and learning delivery. The individual factors discussed in this research are cognitive learning strategies, e-learning readiness, and motivation. The data were obtained from the pre-service teachers at the end of the academic semester when they experienced online and blended learning. Data were analysed using optimal scaling analysis. The analysis method provides a two-dimensional centroid graph which shows the correlations between the variable categories. According to study findings, there is a correlation between the preferences of the learning environment, and the constructs of self-efficacy, e-learning motivation, and task value. It can be said that the motivational variables are more effective in the learning environment preference. The students with high task value, e-learning motivation, and self-efficacy preferred studying in blended learning environments. Cognitive strategies, self-directed learning, learner control, and test anxiety factors are independent of the learners’ learning delivery preferences.
The article contains methods for conducting and results of research on the optimization of the navigation charts scale. The methodology is based on the principles of information theory. The basis for the calculation were the data read from the Polish charts. Certain been recommended optimal scales of the navigation charts.
The distribution of invasive plants depends on several environmental factors, e.g. on the distance from the vector of spreading, invaded community composition, land-use, etc. The species distribution models, a research tool for invasive plants spread prediction, involve the combination of environmental factors, occurrence data, and statistical approach. For the construction of the presented distribution model, the occurrence data on invasive plants (Solidago sp., Fallopia sp., Robinia pseudoaccacia, and Heracleum mantegazzianum) and Natura 2000 habitat types from the Protected Landscape Area Kokořínsko have been intersected in ArcGIS and statistically analyzed. The data analysis was focused on (1) verification of the accuracy of the Natura 2000 habitat map layer, and the accordance with the habitats occupied by invasive species and (2) identification of a suitable scale of intersection between the habitat and species distribution. Data suitability was evaluated for the construction of the model on local scale. Based on the data, the invaded habitat types were described and the optimal scale grid was evaluated. The results show the suitability of Natura 2000 habitat types for modelling, however more input data (e.g. on soil types, elevation) are needed.
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