This paper aims to examine a theoretical framework of digital society and the ramifications of the digital revolution. The paper proposes that more attention has to be paid to cultural studies as a means for the understanding of digital society. The approach is based on the idea that the digital revolution’s essence is fully manifested in the cultural changes that take place in society. Cultural changes are discussed in connection with the digital society’s transformations, such as blurring the distinction between reality and virtuality and among people, nature, and artifacts, and the reversal from informational scarcity to abundance. The presented study develops a general model of culture. This model describes the spiritual, social, and technological facets of culture. Such new phenomena as individualization, transparisation, and so-called cognification (intellectualization of the surrounding environment) are suggested as the prominent trends characterizing the above cultural facets.

This article explores the evolution of constructionism as an educational framework, tracing its relevance and transformation across three pivotal eras: the advent of personal computing, the networked society, and the current era of generative AI. Rooted in Seymour Papert’s constructionist philosophy, this study examines how constructionist principles align with the expanding role of digital technology in personal and collective learning. We discuss the transformation of educational environments from hierarchical instructionism to constructionist models that emphasize learner autonomy and interactive, creative engagement. Central to this analysis is the concept of an “expanded personality”, wherein digital tools and AI integration fundamentally reshape individual self-perception and social interactions. By integrating constructionism into the paradigm of smart education, we propose it as a foundational approach to personalized and democratized learning. Our findings underscore constructionism’s enduring relevance in navigating the complexities of technology-driven education, providing insights for educators and policymakers seeking to harness digital innovations to foster adaptive, student-centered learning experiences.

A method of a self-checking synchronous Finite State Machine (FSM) network design with low overhead is developed. Checkers are used only for FSMs, which output lines are at the same time output lines of the network. The checkers observe output lines of these FSMs. The method is based on reducing the problem to a self-checking synchronous FSM design. The latter is provided by applying a special description of FSM namely, so-called unate Programmable Logic Array (PLA^u) description. Single stuck-at fault on the FSM poles and gate poles are considered. PLA^u realization of FSM allows a factorized or multilevel logic synthesis. They both provide a unidirectional manifestation of the above mentioned faults on the output lines of the corresponding FSMs. This realization also gives rise to a transparency of each component FSM of the network for the faults. PLA^u realization is derived from the State Transition Graph (STG) description of FSMs with using the m-out-of-n encoding of its states and insignificant expanding the products of STG. The problem of replacing an arbitrary synchronous FSM network for the self-checking one with low overhead is discussed.

Generative Artificial Intelligence (GenAI) is revolutionising education, but in doing so, it is often seen simply as a tool for automation and efficiency. This paper challenges this narrow perspective, arguing that GenAI’s transformative potential lies in fostering Meta-AI skills—specialised metacognitive competencies for engaging AI as a cognitive partner. Our objective is to explore how GenAI reshapes learning environments and necessitates a pedagogical shift, hypothesising that traditional education paradigms are insufficient without Meta-AI skills to navigate GenAI’s dynamic outputs. Drawing on constructionist theory, we conceptually analyse seven phenomena: learners’ perceptions, reasoning transitions, scientific research paradigms, information processing shifts, tacit knowledge articulation, multimodal interactions, and early AI education.. The methodology involves synthesising theoretical and empirical literature to frame Meta-AI skills as essential for modern learning. Key results reveal that GenAI transforms education into interactive, exploratory spaces, shifting from symbolic to indexical processing and generalisation-based to situated reasoning. Multimodal GenAI enhances metacognitive awareness, while tacit knowledge exploration deepens self-reflection—outcomes requiring Meta-AI skills beyond conventional metacognition. Practically, educators can integrate these skills into curricula through scaffolded prompt engineering (e.g., refining AI queries), multimodal projects (e.g., creating cross-media narratives), and critical evaluation of AI outputs, empowering students to leverage GenAI effectively. We conclude that GenAI’s integration demands a reevaluation of pedagogy, with Meta-AI skills bridging theoretical shifts and practical applications.