Jānis Grundspeņķis

The Use of Structural Modelling Methods for Analysis of Personalized Study Planning

Fast technological development dictates the growing demand for knowledge and skills. Thus for the learners it is necessary to offer a more flexible way of knowledge acquisition where they can plan their studies independently. Such personalized study planning allows learners to be engaged in this process. The learner can create study programme according to his/her preferences and, as a result, they are more motivated to learn within the study programme planned by them. The authors had already implemented personalized study planning process in a prototype, which allows to create a personalized study programme, and then to plan the course learning, setting the courses in the required sequence [1, 2]. The prototype of personalized study planning system is designed as a part of pedagogical module of intelligent tutoring system and in its essence is a graph-based framework consisting of four hierarchical graphs. Study programme and study course depicted in a form of a graph allows learners to obtain a content of the programme or course structure transparently. In this paper the authors propose the use of structural modelling methods for analysis of personalized study planning based on graph framework. This approach allows to rank elements in the structure according to their importance. That helps the study programme directors, teachers and programme administrators to make the right decisions, making changes to the structure, not threatening the existence of programme or course structure.

The Role of Feedback in Intelligent Tutoring System

Abstract Improvement of IT technologies, expansion of internet and popularization of web technologies have enabled technology enhanced learning introduction in adaption of general matters and acquaintance of specialized problems. It is necessary to integrate in ITS (Intelligent Tutoring System) analysis mechanisms and reactions to simulate or overcome natural tutoring environment achievements. In the development of learning systems it is necessary to take into account both individual needs and requirements, as well as the resources of information technologies. Feedback should be aligned, as much as possible, to the learner’s individuality, special needs, self-evaluation, self-explanation, self-regulation, etc.

Machine Learning Methods for Identifying Composition of Uranium Deposits in Kazakhstan

Abstract The paper explores geophysical methods of wells survey, as well as their role in the development of Kazakhstan’s uranium deposit mining efforts. An analysis of the existing methods for solving the problem of interpreting geophysical data using machine learning in petroleum geophysics is made. The requirements and possible applications of machine learning methods in regard to uranium deposits of Kazakhstan are formulated in the paper.

Analysing the Methods of Dzongkha Word Segmentation

Abstract In both Chinese and Dzongkha languages, the greatest challenge is to identify the word boundaries because there are no word delimiters as it is in English and other Western languages. Therefore, preprocessing and word segmentation is the first step in Dzongkha language processing, such as translation, spell-checking, and information retrieval. Research on Chinese word segmentation was conducted long time ago. Therefore, it is relatively mature, but the Dzongkha word segmentation has been less studied by researchers. In the paper, we have investigated this major problem in Dzongkha language processing using a probabilistic approach for selecting valid segments with probability being computed on the basis of the corpus.

Intelligent Tutoring System for Learning Graphics in CAD/CAM

In the paper general tendencies of learning graphics in CAD/CAM are described in the aspects of evaluation of performance. The common problems in learning of such systems and tools, in knowledge assessment and in the efficiency and quality of usage of CAD/CAM in graphics are searched. In time when IT technologies and use of automatization is live topic in researches about technology enhanced learning with the aid of intelligent learning systems is necessary to create such tools for fast and accurate result of learning process. Adaptive learning and knowledge assessment principle analysis and description of intellectual tutoring system created are given in the research. The ITS created carries out the compilation of the user’s accomplished graphical operations in CAM/CAD system, the analysis of the time spent and data processing. These data help to understand for which operations the user has spent the most time as well as in how many steps the designer has accomplished the task.