GUIDELINES, IDEAS AND APPROACHES FOR AI EDUCATION IN SCHOOL. KNOWLEDGE STRUCTURING AND SEMANTIC MODELING

The strategic documents at European and national level set as a main goal for education the introduction of elements of artificial intelligence in the various educational levels and forms of training in a way appropriate for the learners. In the last two years, experimental training in artificial intelligence in high school has been implemented in Bulgaria. The report examines some problems and challenges in organizing and conducting this training in different types of schools, specialties and classes. Some guidelines are outlined and ideas for creating an appropriate curriculum and learning resources in the field of knowledge structuring and semantic modelling are shared. An approach to teacher and student training is proposed. The authors share their experience in teaching teachers and students and analyse the results of surveys and tests.

FORMATION OF COGNITIVE TOOLS AT UNIVERSITY STUDENTS IN THE COURSE OF COGNITIVE ACTIVITY IN TECHNOLOGICAL TRAINING

Статья посвящена проблеме формирования когнитивного инструментария студентов вуза в процессе познавательной деятельности в условиях технологического обучения. Когнитивная дидактика исходит из того, что каждый человек обладает индивидуальным набором инструментов (внешних и внутренних). Актуальность исследуемой проблемы связана с необходимостью решить вопрос об оптимальной переработке информации, получаемой обучающимися. Автором предлагается идея реализации и исследования мыслительных операций обучающихся в определенной последовательности: представление знаний → структурирование знаний → преобразование знаний во взаимосвязи с основными инструментами мышления как высшей ступени человеческого познания: понятием, суждением и умозаключением. Главным отличием когнитивной дидактики является то, что в ней особое внимание уделяется изучению и развитию познавательных структур и инструментария познания. В качестве методики проведения исследования предлагается использовать диагностику по Дж. Брунеру для определения типов мышления и уровня креативности. Установлено, что реализация использованной методики способствует исследованию базовых типов мышления обучаемых: предметного, образного, знакового и символического. Полученные сведения позволят каждому преподавателю перестроить методику обучения своей дисциплине с ориентацией на личностные особенности когнитивного инструментария каждого обучающегося в отдельности и всей группы в целом. The article is devoted to the formation of cognitive tools at university students in the process of cognitive activity in technological training. Cognitive didactics comes from the fact that each person has an individual set of tools (external and internal). The relevance of the problem under consideration is conditioned by the necessity to solve the problem of effective processing of information by students. The author proposes the idea of implementation and research of students’ mental operations in a specific sequence: representation of knowledge → structuring of the knowledge → transformation of the knowledge in connection with the main tools of thinking as the highest level of human cognition (concept, judgment and conclusion). The main distinction of cognitive didactics is the fact that it focuses on the study and development of cognitive structures and tools. The method employed in the study the diagnostics according to Jerome Bruner’s method to determine the types of thinking and levels of creativity. The author established that the implementation of the employed method contributes to the study of basic types of thinking of students: objective, figurative, sign-oriented and symbolic. The data obtained can help teachers to restructure the teaching methods of a specific discipline, taking into consideration some personal characteristics of cognitive tools of each student individually and throughout the group.

A Cognitive Category-Learning Model of Rule Abstraction, Attention Learning, and Contextual Modulation

We introduce the CAL model (Category Abstraction Learning), a cognitive framework formally describing category learning built on similarity-based generalization, dissimilarity-based abstraction, two attention learning mechanisms, error-driven knowledge structuring and stimulus memorization. Our hypotheses draw on an array of empirical and theoretical insights connecting reinforcement and category learning, and working memory. The key novelty of the model is its explanation of how rules are learned from scratch based on three central assumptions. (1) Category rules emerge from two processes of stimulus generalization (similarity) and its direct inverse (category contrast) on independent dimensions. (2) Two attention mechanisms guide learning by focusing on rules, or on the contexts in which they produce errors. (3) Knowing about these contexts inhibits executing the rule, without correcting it, and consequently leads to applying partial rules in different situations. We show that the model decisively outperforms the established category-learning models ALCOVE (Kruschke, 1992), SUSTAIN (Love, Medin, & Gureckis, 2004) and ATRIUM (Erickson & Kruschke, 1998) on data sets from benchmark studies, including cross-validations based on trial-wise eye-movements. Additionally, CAL's three free parameters, which measure abstraction, memorization and attention control, are related to abilities measured in working memory tasks in a theoretically meaningful way. We illustrate the model's explanatory scope by simulating several phenomena (peak shift, sample size, instruction effects, extrapolation), which were so far unexplained (or unexplained within a single model). We discuss CAL's relation to existing accounts, and its promise in understanding the role of attention control and working memory in category learning and related domains.

The ontological approach to Internet knowledge portals design

The paper presents the approach to Internet knowledge portals design based on ontologies. Internet knowledge portals provide users with access to heterogeneous loosely coupled data and information resources of various subject domains. Using such portals as a single access point greatly simplifies the work with information presented on the Internet. In the case of Internet portals representing engineering subject domains information their environment concentrate not only information resources and data, but also a large number of computing resources and web-services that are used to perform certain calculation tasks of engineering subject domains. The ontological approach to Internet knowledge portals design allows to represent and integrate heterogeneous information and computing resources in the process of such portals data and knowledge structuring and systematizing. It is proposed to use ontology as portal knowledge representation model. The Internet knowledge portal general ontology is represented by a system of four interconnected components. The structure of such a system is described, the basic elements of its ontologies, as well as the relations between them, are distinguished. The ontology elements are formalized that allows to organize and optimize semantic search through the Internet knowledge portals information space.

Philosophy in the Knowledge Structure Pyramid

Currently, and with almost lightspeed, new advances in both human-centered and technology-driven efforts have led to new methods in obtaining, structuring, and using knowledge. This chapter will look at a newer knowledge structuring effort, the knowledge pyramid (KP), attempting to bring in a philosophy-based term, understanding. Knowledge management (KM) has incorporated the philosophy term ontology as a knowledge structuring tool. The chapter will look at how knowledge sets gotten via knowledge elicitation/management can be used and shared to make any organization more effective. The author will consider how the philosophical concept, understanding, can be used in the on-going debate about the structure of KP. The author's goal is to explicate a new model for eliciting, structuring, using, evaluating knowledge for organizational betterment. This resultant paradigm also points the way to future KP debate and research.

Theoretical proposal of steps for the implementation of the Industry 4.0 concept

Goal: The purpose of this paper is to present a proposal of steps for the implementation of Industry 4.0 in the industrial context, considering management and operational aspects. The reason is to discuss that technological change is accompanied by many organizational implications, in which it is perceivable that some companies already experience strategic and operational turbulence due to the lack of understanding of the this structure’s complexity. Design / Methodology / Approach: This study assumes an exploratory character because the subject of analysis is still in the knowledge-structuring phase. In this sense, data was collected from the literature review. Results: A theoretical proposal for the Industry 4.0 implementation framework is presented in flow format. It is organized in steps that cover the strategic and operational aspects during the implementation flow. Limitations of the investigation: The limitations of this study are directly related to its theoretical nature and the difficulty of finding tools that help in the execution of each proposed stage. Practical implications: However, based on theoretical insights, a trajectory of a transformation model is proposed, thus this research intends to show clearly and direct how companies can introduce the aspects of Industry 4.0 to their own benefit. Originality / Value: In this study, a conceptual model is structured, and it indicates a potential of application because it contributes to support and encourage the adoption of technologies and concepts indicated in the Industry 4.0 literature in a structured way.