Magistro darbe yra iškeltas tikslas išsiaiškinti mokytojų vaidmenis organizuojant darbą heterogeninėse klasėse. Buvo išanalizuoti ir susisteminti įvairūs Lietuvos ir užsienio autorių vadybinės, pedagoginės, psichologinės srities darbai. Atlikta Lietuvos Respublikos teisinių dokumentų, reglamentuojančių švietimo ir specialiojo ugdymo organizavimą, analizė. Darbo tikslui ir uždaviniams pilnai atskleisti buvo naudojamas anketinės apklausos metodas. Tyrimo duomenys patvirtino literatūros apžvalgoje minimus mokytojo vaidmenis, atskleidė dominuojančius pedagogų, dirbančių heterogeninėse klasėse, vaidmenis, jų realizavimo dažnumą. Taip pat tyrimo duomenys atskleidė rečiausiai arba ne taip intensyviai atliekamus mokytojo vaidmenis, į kuriuos derėtų atkreipti dėmesį, įdėti daugiau pastangų jiems atlikti. / The aim of this master‘s final paper is to clear up the roles of teachers organizing the work in heterogeneous classes. Different works of Lithuanian and foreign author‘s management, pedagogics, psychology spheres were analised and structured. The analysis of the Republic of Lithuania documents, regulating education and special education, was done. The method of questionnaire was used to reveal the aim and the objectives of the work fully. The resuls of the research confirmed the teacher‘s roles mentioned in literary review, relealed the dominant teacher‘s working heterogeneous classes roles, and the frequency of these roles. The results of the research also shuowed rarely or not so intensively performed teacher‘s roles, which one shuold pay more attention at, and make more effors to perform them.

Gaussian graphical model has been a popular tool to investigate conditional dependency between random variables by estimating sparse precision matrices. The estimated precision matrices could be mapped into networks for visualization. For related but different classes, jointly estimating networks by taking advantage of common structure across classes can help us better estimate conditional dependencies among variables. Furthermore, there may exist multilevel structure among variables; some variables are considered as higher level variables and others are nested in these higher level variables, which are called lower level variables. In this dissertation, we made several contributions to the area of joint estimation of Gaussian graphical models across heterogeneous classes: the first is to propose a joint estimation method for estimating Gaussian graphical models across unbalanced multi-classes, whereas the second considers multilevel variable information during the joint estimation procedure and simultaneously estimates higher level network and lower level network. For the first project, we consider the problem of jointly estimating Gaussian graphical models across unbalanced multi-class. Most existing methods require equal or similar sample size among classes. However, many real applications do not have similar sample sizes. Hence, in this dissertation, we propose the joint adaptive graphical lasso, a weighted L1 penalized approach, for unbalanced multi-class problems. Our joint adaptive graphical lasso approach combines information across classes so that their common characteristics can be shared during the estimation process. We also introduce regularization into the adaptive term so that the unbalancedness of data is taken into account. Simulation studies show that our approach performs better than existing methods in terms of false positive rate, accuracy, Mathews correlation coefficient, and false discovery rate. We demonstrate the advantage of our approach using liver cancer data set. For the second one, we propose a method to jointly estimate the multilevel Gaussian graphical models across multiple classes. Currently, methods are still limited to investigate a single level conditional dependency structure when there exists the multilevel structure among variables. Due to the fact that higher level variables may work together to accomplish certain tasks, simultaneously exploring conditional dependency structures among higher level variables and among lower level variables are of our main interest. Given multilevel data from heterogeneous classes, our method assures that common structures in terms of the multilevel conditional dependency are shared during the estimation procedure, yet unique structures for each class are retained as well. Our proposed approach is achieved by first introducing a higher level variable factor within a class, and then common factors across classes. The performance of our approach is evaluated on several simulated networks. We also demonstrate the advantage of our approach using breast cancer patient data. / Ph. D.

The thesis deals with the subject of the role of the teacher in low-threshold courses of Czech for foreigners provided by The Centre for Integration of Foreigners (CIC). The thesis is divided into a theoretical and empirical part. The theoretical part is divided into three main parts. The first chapter explains the term "low-threshold", which is later put into context of foreign language education organized by the state or non-profit organizations. We focus mainly on NPK CIC. We cover how the courses are built, what is their content and what are the specific of (large) heterogenous classes. The second chapter focuses on adult education in general. We cover the basic of adult education and introduce the key competencies that are developed at NPK. The third chapter covers the adult's teacher. It defines who the teacher is and what his competencies are. We also compare the demands that the teacher has to meet in schools or when they are a teacher at NPK. The chapter covers the role of the teacher and analyses the usage of these models in the environment of NPK. Attention is also paid to team teaching. The empiric part deals with the description of the results and implementation of qualitative research. The aim of this research was to find out how the teachers view their role at NPK that substantially...

The goal of my thesis is to describe which campaigns and projects support reader and which are suitable for work with children in the kindergarten's heterogeneous classes. As part of the thesis, project is created base of the studied literature which should support reading literacy in a kindergarten's heterogeneous class and cooperate on its implementation with other subjects. I define the terms closely related to the given topic in the theoretical part, namely literacy and numeracy, reading literacy (in relation to RVP PV). Focus is on the role of kindergarten and the necessity of developing a child in reading literacy with the emphasis on the heterogeneous classes. I also emphasize the role of the family in reading literacy. Finally, I describe specific campaigns and projects in the Czech Republic that support readership and reading literacy. I devote myself to the implementation of the project itself in the maternal Schools with heterogeneous classes in the practical part. In more detail, I focus on the Celé Česko čte dětem, Noc s Andersenem and Listování. While the Celé Česko čte dětem a whole range of uses, Listování and Noc s Andersenem serves as a mere addition to the development of reading literacy. I value positively the cooperation with the city's library and parents.