Artificial intelligence (AI) has become increasingly visible in higher education, making it important to understand how students in this context evaluate AI in general. Although students’ attitudes toward AI have been widely examined, less is k...
Background: This study examines the influence of AI-driven supply chains on the adoption of automation and robotics within Jordanian manufacturing firms, emphasizing the role of supply chain adaptability and agility as mediators and market turbulence...
As the educational landscape evolves, understanding and fostering student adaptability has become increasingly critical. This study presents a comparative analysis of XAI techniques to interpret machine learning models aimed at classifying student ad...
Artificial intelligence (AI) has been widely adopted in workplaces and has significantly influenced how employees perform their work. AI awareness may influence employees’ adaptation to AI-enabled workplaces and changing job demands. Grounded i...
This study investigates the adaptability of Artificial Intelligence (AI) agents in the Metaverse, focusing on their ability to enhance responsiveness, decision-making, and engagement through the proposed Adaptive Learning Model for AI Agents (ALMAA)...
Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG)-based hybrid AI systems are increasingly transforming higher education, yet it remains unclear whether they are adopted through similar or distinct technology adoption pathways. Th...
This exploratory cluster-randomized mixed-methods study examined reading development and learner experience across AI-adaptive, teacher-differentiated, and non-differentiated EFL reading instruction. Eighty-seven university-level EFL learners, classi...
This study addresses a notable gap in the climate change literature by examining the potential of artificial intelligence and machine learning (AI–ML) in urban climate change adaptation and sustainable development across major global continents. Whil...
Artificial Intelligence (AI) is increasingly reshaping how cultural heritage institutions design and deliver digital visitor experiences, particularly through adaptive Augmented Reality (AR) applications. However, most existing AR deployments in muse...
Using adaptive intelligence as a theoretical lens, the study investigates how L2 motivational selves are associated with AI-IDLE engagement through psychological capital (PsyCap) and L2 grit and whether these indirect associations vary with AI litera...
Climate change increases uncertainty in agricultural production and rural livelihoods, encouraging farms to pursue diversification strategies to buffer climate-related risks. Concurrently, the growing use of digital and AI-based climate decision-supp...
Background/Objectives: As artificial intelligence systems become increasingly embedded in everyday cognitive tasks, human–AI interaction is no longer limited to tool use but evolves into a dynamic process of mutual adaptation. While extensive r...
The rapid expansion of artificial intelligence (AI) in digital education has transformed gamification from a motivational strategy into a data-driven, adaptive learning paradigm. This systematic review conceptualizes AI-supported gamification as an i...
6 November 2024
AI Alignment is a term used to summarize the aim of making artificial intelligence (AI) systems behave in line with human intentions and values. There has been little consideration in previous AI Alignment studies of the need for AI Alignment to be a...
Many complex systems requires the use of controllers to allow an automated, self-adaptive management of components and resources. Controllers are software components that observe a system, analyse its quality, and recommend and enact decisions to mai...
The rapid transition to Industry 4.0/5.0 has widened the gap between graduates’ skill sets and labor market expectations; this study aimed to profile student competencies and align academic pathways with inclusive and adaptive AI-driven learnin...
This study addresses the critical global challenge of climate adaptation by assessing the inadequacies in current methodologies for estimating adaptation costs. Broad assessments reveal a significant investment shortfall in adaptation strategies, hig...
This study investigates how the integration of artificial intelligence (AI) transforms job practices within a leading European infrastructure company. Grounded in the Feeling Economy framework, the research explores the shift in task composition foll...
Vulnerability management (VM) is becoming increasingly important as organizations face growing cybersecurity threats. This study examines how organizations adapt their vulnerability management routines in response to evolving vulnerability signals th...
This paper reviews the literature on integrating AI in e-learning, from the viewpoint of cognitive neuropsychology, for Personalized Learning (PL) and Adaptive Assessment (AA). This review follows the PRISMA systematic review methodology and synthesi...
Extended Reality (XR) technologies have matured into powerful tools for training in high-stakes domains, from emergency response to search and rescue. Yet current systems often struggle to balance real-time AI-driven personalisation with the need for...
Artificial intelligence (AI)-supported decision systems can improve managerial decision-making, but their cognitive implications may depend on how information, explanations, alerts, time pressure, uncertainty, autonomy, and human control are configur...
Generative artificial intelligence (GenAI) has expanded opportunities for English learning beyond formal classroom settings. From an intelligence perspective, speaking in English as a foreign language (EFL) represents an applied domain in which learn...
Recent developments in large language models allow for real time, context-aware tutoring. AI Gem, presented in this article, is a layered architecture that integrates personalization, adaptive feedback, and curricular alignment into transformer based...
Adaptation through Artificial Intelligence (AI) creates individual-centered feedback strategies to reduce academic achievement disparities among students. The study evaluates the effectiveness of AI-driven adaptive feedback in mitigating these gaps b...
Gamified e-learning platforms and Artificial Intelligence (AI)-driven adaptive learning systems can improve learner engagement, but existing solutions rarely combine the two, and few explain their adaptive decisions to learners. To address this gap,...
This paper introduces cognitive adaptivity as a novel framework for addressing human factors in cybersecurity during the Industry 5.0–6.0 transition, with a focus on hard-to-abate industries where digital transformation intersects sustainabilit...
In complex environments, Operators need to manage continuous, real-time information flows while handling unexpected situations within a limited timeframe. This can lead to high cognitive load, stress, fatigue, etc. To prevent such situations, Artific...
Artificial intelligence-enabled adaptive learning systems (AI-ALS) have been increasingly utilized in education. Schools are usually afforded the freedom to deploy the AI-ALS that they prefer. However, even before artificial intelligence autonomously...
Artificial intelligence (AI) is increasingly able to infer apparent fishing activity, vessel type, encounters, non-cooperative or otherwise low-visibility vessel presence, and other maritime patterns from Automatic Identification System (AIS), vessel...
Using adaptive learning technologies, personalized feedback, and interactive AI tools, this study investigates how these tools affect student engagement and what the mediating role of individuals’ digital literacy is at the same time. The study...
Small- and medium-sized enterprises (SMEs) operate under conditions of rapid change, competitive pressure and growing informational complexity, while their owner-managers often have limited time and cognitive bandwidth to interpret emerging strategic...
Background and objectives: Artificial intelligence (AI)-based adaptive learning has the potential to strengthen clinical decision-making and enhance quality of care at primary health centers. The present study assessed the perceptions, barriers, and...
The stochastic fluctuations of AI computational loads inject harmonic currents into the DC bus, amplifying bus voltage ripples and weakening the power quality. Existing strategies typically rely on high-gain control strategies to minimize harmonic ou...
Artificial intelligence systems increasingly mediate high-stakes human activities, yet urban navigation remains highly challenging for blind and visually impaired individuals. Although digital navigation technologies have significantly improved route...
Urban mobility has undergone and continues to undergo a profound transformation driven by the convergence of artificial intelligence (AI), the Internet of Things (IoT), and predictive analytics in recent years. These technologies are redefining adapt...
Depression poses a major worldwide health burden, necessitating advanced diagnostic tools based on reliable and authentic assessment. While multimodal AI systems offer promising results by integrating diverse data sources, existing approaches often r...
Coordinating multi-agent unmanned aerial vehicle (UAV) swarms is challenging in disaster scenarios where communications are dynamic, unreliable, and subject to UAV losses. While distributed artificial intelligence has enabled unprecedented levels of...
Automatic Identification System (AIS) trajectories provide valuable spatiotemporal information for maritime route structure mining, but robust extraction of key route nodes remains difficult because raw data are noisy, turning behaviors are easily ma...
This study combines Visible Light Communication (VLC) and Artificial Intelligence (AI) to optimize traffic signal control, reduce congestion, and enhance safety. Utilizing existing road infrastructure, VLC technology transmits real-time data on vehic...
The response forecasting of in-service complex electronic systems remains a challenge due to its uncertainty. An AI-based adaptive surrogate modeling method, including offline and online learning procedures, is proposed in this research for different...
The rapid proliferation of large language models has created significant opportunities for personalized education, yet existing systems rarely account for user competency as a determinant of interaction quality. This study introduces Persona in The L...
Traditional security methods fail to match the speed of evolving threats because Industrial Internet of Things (IIoT) technologies have become more widely adopted. A lightweight adaptive AI-based intrusion detection system (IDS) for IIoT environments...
Urban lighting systems contribute significantly to energy consumption and light pollution, raising environmental and societal concerns. This paper explores the potential of Artificial Intelligence (abbreviation: AI)-driven adaptive urban lighting as...
Artificial intelligence (AI) is spreading across educational, productive, and institutional settings, creating a need for governance approaches that can adapt to heterogeneous stakeholders. This study proposes an adaptive AI governance framework for...
Despite widespread adoption of cybersecurity awareness training (CSAT), a persistent knowledge–behaviour gap continues to undermine organisational security posture, particularly in resource-constrained and developing-country contexts. This 12-w...
Multi-stakeholder supply chains require decision mechanisms capable of simultaneously interpreting dynamic system states, coordinating conflicting stakeholder interests, and managing uncertainty across interconnected operational decisions. This study...
The growing adoption of artificial intelligence and autonomous decision-making systems in maritime operations introduces significant challenges related to safety, accountability, and human oversight. Although Human-in-the-Loop approaches are commonly...
This paper provides the modeling, implementation, and simulation of fractional-order processes associated with the production of the enriched 13C isotope due to chemical exchange processes between carbamate and CO2. To demonstrate and simulate the pr...
There are difficulties in obtaining accurate modeling of ship trajectories with traditional prediction methods. For example, neural networks are prone to falling into local optima and there are a small number of Automatic Identification System (AIS)...
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