Applying Recommender Systems and Adaptive Hypermedia for e-Learning Personalizatio

Learners learn differently because they are different -- and they grow more distinctive as they mature. Personalized learning occurs when e-learning systems make deliberate efforts to design educational experiences that fit the needs, goals, talents, and interests of their learners. Researchers had recently begun to investigate various techniques to help teachers improve e-learning systems. In this paper we present our design and implementation of an adaptive and intelligent web-based programming tutoring system -- Protus, which applies recommendation and adaptive hypermedia techniques. This system aims at automatically guiding the learner's activities and recommend relevant links and actions to him/her during the learning process. Experiments on real data sets show the suitability of using both recommendation and hypermedia techniques in order to suggest online learning activities to learners based on their preferences, knowledge and the opinions of the users with similar characteristics

Ontology engineering of automatic text processing methods

Currently, ontologies are recognized as the most effective means of formalizing and systematizing knowledge and data in scientific subject area (SSA). Practice has shown that using ontology design patterns is effective in developing the ontology of scientific subject areas. This is due to the fact that scientific subject areas ontology, as a rule, contains a large number of typical fragments that are well described by patterns of ontology design. In the paper, we present an approach to ontology engineering of automatic text processing methods based on ontology design patterns. In order to get an ontology that would describe automatic text processing sufficiently fully, it is required to process a large number of scientific publications and information resources containing information from modeling area. It is possible to facilitate and speed up the process of updating ontology with information from such sources by using lexical and syntactic patterns of ontology design. Our ontology of automatic text processing will become the conceptual basis of an intelligent information resource on modern methods of automatic text processing, which will provide systematization of all information on these methods, its integration into a single information space, convenient navigation through it, as well as meaningful access to it

Development of an intelligent information resource model based on modern natural language processing methods

Currently, there is an avalanche-like increase in the need for automatic text processing, respectively, new effective methods and tools for processing texts in natural language are emerging. Although these methods, tools and resources are mostly presented on the internet, many of them remain inaccessible to developers, since they are not systematized, distributed in various directories or on separate sites of both humanitarian and technical orientation. All this greatly complicates their search and practical use in conducting research in computational linguistics and developing applied systems for natural text processing. This paper is aimed at solving the need described above. The paper goal is to develop model of an intelligent information resource based on modern methods of natural language processing (IIR NLP). The main goal of IIR NLP is to render convenient valuable access for specialists in the field of computational linguistics. The originality of our proposed approach is that the developed ontology of the subject area “NLP” will be used to systematize all the above knowledge, data, information resources and organize meaningful access to them, and semantic web standards and technology tools will be used as a software basis

-

An approach to organizing universal programming environment, intended to form the departmental document-oriented data warehouse of the educational institution, is offered in the article. Available possibility of individual design of business logic that is generally characteristic for educational activities. The concept of specialized warehouse of semistructured data is based on the logical model “object-attribute-value”, which allows not only to store electronic documents with a different sets of attributes, but also to maintain the dynamics of these sets.-

Diagram-based intelligent tutoring systems

This work first presents two implementations of Intelligent Tutoring Systems (ITSs) on engineering undergraduate-level diagram education: StaticsTutor for free-body diagram and Thermo Cycle Tutor for refrigeration T-v diagram. Initial investigations on several groups of students have shown their educational effectiveness. Unlike text-based input, diagram has some intrinsic challenges that lead it hard to teach. One example is conceptual knowledge is highly interconnected with procedural knowledge. Learned from the two ITSs, we provided some general pedagogical guidelines for the future Diagram-based ITSs. Also, we learned classes can be used as a way of representing geometric shapes in diagrams. Thus, we extended our work to the generality of how the current approach can be applied to other domains. We chose a popular type of diagram, called Block Diagram, which contains geometric objects and lines/arrows in connecting them. We developed a methodology to represent a diagram’s information and an ontology of diagram evaluation processes to diagnose students\u27 diagrams. Our work contributes to the development of Diagram-based ITSs authoring tools

Instructional Strategies in Diagram-based ITSs: Lessons Learned from Two Tutoring Systems

Unlike text-based input to an intelligent tutoring system, a diagram is perceived as a whole state; the operation sequence is less important. Traditional step-wise coaching is not as appropriate in diagram-based intelligent tutoring systems (DITS). From two previous tutoring systems, StaticsTutor and Thermo Cycle Tutor, we propose cross-domain pedagogical guidelines for DITS. In particular, instruction needs to be mapped to a hierarchical understanding of the diagram, where each level focuses on different characteristics of the drawing. Also, instruction needs to address conceptual knowledge and procedure expertise separately. Some practical suggestions are described to achieve these goals, such as 1) different tolerance for error at different level of evaluation, 2) use of Q&A to resolve diagram ambiguity and 3) early loading of expertise that is important for avoiding difficult-to-fix diagrammatic states

DEVELOPMENT OF AN ONTOLOGY-BASED ADAPTIVE PERSONALIZED E-LEARNING SYSTEM

E-learning has fast become an active field of research with a lot of investments towards web-based delivery of personalized learning contents to learners. Some issues of e-learning arise from the heterogeneity and interoperability of learning content adapting to learner's styles and preferences. This has brought about the development of an ontology-based personalized learning system to solve this problem. This research developed an ontology-based personalized e-learning system that presents suitable learning contents to learners based on their learning style, preferences, background knowledge, and personal profile.&nbsp

Scenario Approach for Image Processing in Smart City

Modern city is described by fast change of a situations and large volume of available data about it. One of principal data types are images (satellite pictures, video from surveillance cameras, etc.). Fast manual analysis of such data is often complicated or impossible. Widespread practice is development of analysis system for each separate problem (for example identification of car identification numbers or QR-codes) that leads to a number of difficulties; in particular, it is difficult to integrate and modify such systems. In article the structure of raster image analysis system (both single images and a video stream) is proposed. The system is developed taking into account peculiarities of input data and requirements imposed by the smart city. As a basis of system the set of algorithms, that implements all image analysis stages (preliminary processing, construction of feature space and classification) is proposed. That algorithms are elements of data processing scenarios. Usage of scenario approach, based on subject domain ontology, allows to significantly simplify adaptation of image processing system to the peculiarities of subject domain without limitation of allowed algorithms set. A example of application of the developed system for real-world problem is given